Systems and methods for the recovery of hydrogen, energy, and minerals from geological environments

Abstract

A method for fracturing a subsurface rock formation for hydrogen production includes injecting a fluid comprising water into a subsurface rock formation under controlled conditions, generating fractures in the subsurface rock, and recovering hydrogen gas produced by subsurface rock after the generation of the fractures. The fluid is injected at a pressure below the breakdown pressure of the subsurface rock.

Description

Atty. Docket No.: GE0001PCT_8022-00200SYSTEMS AND METHODS FOR THE RECOVERY OF HYDROGEN, ENERGY, AND MINERALS FROM GEOLOGICAL ENVIRONMENTSCROSS-REFERENCE TO RELATED APPLICATIONS

[0001] The present application claims priority to U.S. Provisional Application No. 63 / 701,197 filed on September 30, 2024 and entitled, “SYSTEMS AND METHODS FOR THE RECOVERY OF HYDROGEN, ENERGY, AND MINERALS FROM GEOLOGICAL ENVIRONMENTS”, the entire disclosure of which is incorporated herein by reference.FIELD

[0002] This present disclosure relates generally to systems and methods for (e.g., in situ) production, stimulation, and / or recovery of hydrogen, geothermal energy, amorphous silica, rare earth minerals, metals, and / or other resources from subsurface rock formations and / or other geological environments.BACKGROUND

[0003] Hydrogen is a versatile fuel that produces no greenhouse gas emissions at its point of use and, hence, is a promising source of clean energy. While the use of hydrogen fuel produces no direct greenhouse gases, current methods of production of hydrogen such as natural gas reforming emit a significant amount of CO2, and, as a result, are significantly more CO2- intensive than combusting hydrocarbons themselves. Moreover, production of “green hydrogen”, such as hydrogen produced via electrolysis of water, is impractically expensive, and the transportation and degradation of such green hydrogen pose further challenges that reduce the viability of the widespread use of green hydrogen as an energy carrier.SUMMARY

[0004] In some embodiments, a method for fracturing of a subsurface rock formation for hydrogen production comprises injecting a fluid comprising water into a subsurface rock formation under controlled conditions, generating fractures in the subsurface rock, and recovering hydrogen gas produced by subsurface rock after the generation of the fractures. The fluid is injected at a pressure below the breakdown pressure of the subsurface rock.

[0005] In some embodiments, a method for production of hydrogen from geological formations comprises operating one or more wells in alternating injection and extraction cycles, modulating pressure as a function of time P(t), temperature T(t) as a function of time, or both during the alternating injection and extraction cycles, controlling pH as a function of time pH(t) during the alternating injection and extraction cycles, and recovering one of more productsAtty. Docket No.: GE0001PCT_8022-00200 during the extraction cycle. At least a first well of the one or more wells receives a fluid during the injection cycle, and the first well extracts fluid in the extraction cycle.

[0006] In some embodiments, a system for integrated hydrogen production from geological formations comprises: at least one well configured for alternating injection and extraction cycles, a pressure controller capable of maintaining pressures ranging from about 50 bar to about 4000 bar, a chemical injection unit for delivering pH control agents and reaction enhancers, a temperature control system for maintaining operating temperatures ranging from about 150°C to about 500°C, a gas separation and recovery equipment for capturing hydrogen gas, and a control system configured to execute the alternating injection and extraction cycles.

[0007] These and other features will be more clearly understood from the following detailed description taken in conjunction with the accompanying drawings and claims.BRIEF DESCRIPTION OF THE DRAWINGS

[0008] For a more complete understanding of the present disclosure, reference is now made to the following brief description, taken in connection with the accompanying drawings and detailed description:

[0009] FIG. 1 schematically illustrates a serpentinization reaction process in a subsurface formation according to some embodiments.

[0010] FIGS. 2A-2B schematically illustrate fracture structures according to some embodiments.

[0011] FIG. 3 schematically illustrate other fracture structures according to some embodiments.

[0012] FIG. 4A illustrates exemplary pressure pulse waveforms according to some embodiments.

[0013] FIG. 4B schematically illustrates weathering induced fractures according to some embodiments.

[0014] FIGS. 5A-5B illustrates exemplary pressure pulse waveforms according to some embodiments.

[0015] FIGS. 6A and 6B schematically illustrate alternating injection and extraction cycles (a "‘Huff and Puff’ process) that can be used to improve the extraction processes in Fe(2+)-rich environments according to some embodiments.

[0016] FIG. 7 schematically illustrates a wellbore structure with multiple wellbores and multiple fracture networks according to some embodiments.

[0017] FIG. 8 is a table of iron-rich minerals according to some embodiments.

[0018] FIG. 9 shows a schematic reaction process for dissolved Fe(2+) that can be recoveredAtty. Docket No.: GE0001PCT_8022-00200 from a formation and returned to the surface in the hydrothermal liquid column according to some embodiments.

[0019] FIGS. 10A-10C schematically illustrates systems for stimulation and recovery from mineral collections at or near the surface such as from mines such as diamond mines according to some embodiments.

[0020] FIG. 11 schematically illustrates reactions performed within a slurry filled pressurized vessel according to some embodiments.

[0021] FIG. 12 schematically illustrates a reactor and heat integration for thermally decomposing 3Fe(OH)2 to produce hydrogen and steam according to some embodiments.

[0022] FIG. 13 shows a plot of Gibbs free energy change for thermal decomposition of 3Fe(OH)2 as a function of temperature according to some embodiments.

[0023] FIG. 14 illustration a graph of pH dependence of the speciation of CO2 according to some embodiments.

[0024] FIG. 15 schematically illustrates an implementation of a netw ork environment for use in providing systems, methods, and architectures as described herein is shown and described.

[0025] FIG. 16 schematically illustrates an example of a computing device and a mobile computing device according to some embodiments.DETAILED DESCRIPTION

[0026] It is contemplated that systems, architectures, devices, methods, and processes of the claimed invention encompass variations and adaptations developed using information from the embodiments described herein. Adaptation and / or modification of the systems, architectures, devices, methods, and processes described herein may be performed, as contemplated by this description.

[0027] Throughout the description, where articles, devices, systems, and architectures are described as having, including, or comprising specific components, or where processes and methods are described as having, including, or comprising specific steps, it is contemplated that, additionally, there are articles, devices, systems, and architectures of the present invention that consist essentially of. or consist of. the recited components, and that there are processes and methods according to the present invention that consist essentially of, or consist of, the recited processing steps.

[0028] It should be understood that the order of steps or order for performing certain action is immaterial so long as the invention remains operable. Moreover, two or more steps or actions may be conducted simultaneously.Atty. Docket No.: GE0001PCT_8022-00200

[0029] The mention herein of any publication, for example, in the Background section, is not an admission that the publication serves as prior art with respect to any of the claims presented herein. The Background section is presented for purposes of clarity and is not meant as a description of prior art with respect to any claim.

[0030] Documents are incorporated herein by reference as noted. Where there is any discrepancy in the meaning of a particular term, the meaning provided in the Definition section above is controlling.

[0031] Headers are provided for the convenience of the reader - the presence and / or placement of a header is not intended to limit the scope of the subject matter described herein.

[0032] There is currently an effort to promote the harvesting of “geologic hydrogen"’ or “natural hydrogen” that is produced when water reacts with iron-rich rocks (i.e., via serpentinization). Challenges include identifying geologic sites with conditions - e.g., rock composition, pressure, temperature, porosity, etc. - that are favorable to the harvesting of hydrogen, and designing advanced systems for the stimulation and recovery of such hydrogen that are not cost-prohibitive.

[0033] Presented herein are systems and methods for the production (e.g.. in situ production) of geologic hydrogen, geothermal energy (heat), amorphous silica, rare earth minerals, metals and metal ores, and / or other resource(s), e.g., from geological environments such as subsurface rock formations. For example, presented herein are methods and systems for the use of artificial intelligence / machine learning (AI / ML) to simulate the complex thermodynamic and geochemical environments of rock formations to locate sites for, and / or design / optimize / control processes for, in-situ production and / or extraction of hydrogen, geothermal energy, amorphous silica, metals, and / or rare earth minerals.

[0034] Furthermore, presented herein are methods and systems for the use of AI / ML to locate to locate sites for, and / or design / optimize / control processes for, synergistic in-situ production and / or extraction of multiple resources selected from the following: (i) in-situ production and / or extraction of hydrogen, (ii) extraction of geothermal energy, (iii) extraction of amorphous silica, (iv) extraction of rare earth minerals, (v) ethylene production, (vi) ammonia production (e.g.. Haber-Bosch process), (vii) production of e-fuels (e.g.. via Fischer-Tropsch process) including e-ammonia, e-diesel, e-gasoline, e-kerosene, etc., e g., where part of the process heat is provided by electricity, (viii) enhanced biofuel production, (ix) production / extraction of direct reduced iron (DRI), e.g., for steel production, (x) syngas production, and (xi) cement / green cement production.

[0035] In certain embodiments, the computationally efficient AI / ML methods described hereinAtty. Docket No.: GE0001PCT_8022-00200 enable a very large number of candidate sites to be rapidly screened and ranked, e.g., in terms of their suitability / desirability for a given purpose. For example, presented herein are methods for creating and using a ML model, e.g., a large language model (LLM) and / or a Kolmogorov- Arnold Network (KAN), (i) to track evolution of reactants, products, and / or thermodynamic conditions in complex environments (e.g., tracking in-situ exothermic serpentinization environments based on geothermal well data), and / or (ii) to control / avoid deformation and / or induced seismicity, e.g., in processes for the production and / or extraction of hydrogen, geothermal energy, amorphous silica, and / or rare earth minerals.

[0036] In some aspects, presented herein are methods and systems for stimulating heat and resource (e.g., H2, geothermal energy, amorphous silica, iron and rare earth mineral ores) extraction processes in Fe(2 ,)-rich environments (e.g., subsurface geologic formations) by alternating injection and extraction cycles (Huff and Puff). This alternation can be achieved in a number of ways including by increasing and decreasing the water injection pressure in the well, generally about a mean pressure which is close to the lithostatic pressure at the depth at which the weathering process is taking place. The amplitude and period of these pressure increases and decreases may be controlled to facilitate increasing the surface area of rocks exposed to the fluid. The amplitude and period of these pressure increases and decreases may be controlled to facilitate increasing the rate at which resources are produced or transmitted from the rock formation to the surface.

[0037] Furthermore, presented herein are methods and systems for in-situ generation of hydrogen gas via brine injection into iron-rich formations (e g., banded iron formations (BTFs), e.g., iron-rich minnesotaite, magnetite, with adjacent silica-rich layers), with enhanced heat recovery and co-production of amorphous silica in-situ, e.g., featuring application of pressure modulated hydraulics and geochemical control.

[0038] Furthermore, presented herein are methods and systems for hydrogen production from repurposed diamond mines (e.g., Kimberlite or Lamproite pipes or dykes).

[0039] Furthermore, presented herein are methods and systems for co-production of geothermal energy’ and amorphous silica using serpentinization-enhanced high-alkalinity brines with supercritical CO2 injection.

[0040] Furthermore, presented herein are systems and methods for forecasting, evaluating, and / or remediating environmental hazards with stimulation and recovery’ of geologic hydrogen (e.g., as part of a system for geologic hydrogen, geothermal energy, amorphous silica, metal ores, rare earth minerals, and / or other resource production as presented herein).

[0041] In some aspects, presented herein are systems and methods for reaction-inducedAtty. Docket No.: GE0001PCT_8022-00200 fracturing (e.g., as part of a system for geologic hydrogen, geothermal energy, amorphous silica, metal ores and oxides, rare earth mineral, and / or other resource production as presented herein).

[0042] Furthermore, presented herein are methods for pH regulation using mixtures of CO2 and brine (e.g., in a system for geologic hydrogen, geothermal energy, amorphous silica, metal oxides, rare earth mineral, and / or other resource production as presented herein).

[0043] Furthermore, presented herein are methods for recovery of maximum value from geologic Fe2+in low pH environments (e.g., in a system for geologic hydrogen, geothermal energy, amorphous silica, rare earth mineral, and / or other resource production as presented herein).

[0044] In one aspect, the invention is directed to a method for the design and / or control of a process for production of hydrogen from a geologic environment (e.g., in situ production (e.g., extraction) of hydrogen from a subsurface rock formation), the method comprising: receiving, by a processor of a computing device, one or more inputs comprising data for one or more parameters (e.g.. measurements of the parameters and / or data from one or more existing databases, e.g., geothermal well data bases) related to the geologic environment (e.g. the subsurface rock formation); and using a machine learning module and the received input to produce one or more outputs relating to the design and / or control of the process for production of hydrogen from the geologic environment (e.g., the subsurface rock formation).

[0045] In certain embodiments, the received one or more inputs comprises data for one or more parameters at one or more depths (e g., as a funchon of 1 D, 2D, or 3D position) and / or at one or more times, said one or more parameters selected from the group consisting of (a) to (1) as follows: (a) temperature and / or thermal gradient profiles / data; (b) pressure and / or pressure profile; (c) concentration of species (e.g., salinity, Na+, Cl”, SiCh) in the geothermal fluid (e.g., said fluid comprising water); (d) mineral composition (e.g., iron content of the subsurface rock formation, e.g., Fe2+, e.g., identification and analysis of mineral formations enriched in Fe2+including but not limited to formations rich in the minerals or elemental combinations, e.g., Olivine, Grunerite (Fe?Si8O22(OH)2), Hercynite (FeAhO4), Siderite (FeCOs), Magnetite (FesO4), pyroxene, banded iron, greywackes, kimerlites, and / or basalt); (e) pH level; (I) oxidation state (e.g., oxidation-reduction potential, ORP); (g) gas composition (e.g., CO2, CH», H2S); (h) flow rate and / or enthalpy; (i) fracturing conditions (e.g., fracture density7, penetration, surface area estimates, fluid flow, and / or stress state); (j) porosity, permeability and / or structure: (k) silica activity; and (1) dissolution and / or solubility of H2.

[0046] In certain embodiments, the one or more outputs comprises one or more thermodynamicAtty. Docket No.: GE0001PCT_8022-00200 quantities selected from the group consisting of Gibbs free energy (AG), enthalpy (AH), entropy (AS), equilibrium constant (K), heat capacity (Cp), and reaction rate.

[0047] In another aspect, the invention is directed to a method for the design and / or control of an integrated process for the production of multiple resources from a geologic environment (e.g., in situ production (e.g., extraction) of multiple resources from a subsurface rock formation), the method comprising: receiving, by a processor of a computing device, one or more inputs comprising data for one or more parameters (e.g.. measurements of the parameters and / or data from one or more existing databases, e.g., geothermal well data bases) related to the geologic environment (e.g. the subsurface rock formation); and using a machine learning module and the received input to produce one or more outputs relating to the design and / or control of the process for production of the multiple resources from the geologic environment (e.g., the subsurface rock formation), wherein the multiple resources (or products derived from the multiple resources) comprises two or more members selected from the group consisting of members (i) through (v) as follows: (i) hydrogen, (ii) heat (e.g.. geothermal energy ), (iii) amorphous silica, (iv) metals and metal oxides, and (v) one or more rare earth minerals (e.g., any of the lanthanides, scandium, and / or yttrium) and wherein the machine learning module also produces one or more outputs relating to the design and / or control of a (further) process for production of one or more products derived from one or more of the multiple resources, e.g., wherein the one or more derived products comprises ethylene, ammonia (e.g., Haber- Bosch process), e-fuels (e.g.. via Fischer-Tropsch process) (e.g., e-ammonia, e-diesel, e- gasoline, or e-kerosene, e g., where part of the process heat is provided by electricity), biofuel (e.g., enhanced biofuel production), direct reduced iron (DRI) (e.g., for steel production), syngas, and cement / green cement).

[0048] In certain embodiments, the multiple resources comprise hydrogen (e.g., geologic hydrogen) and heat (e.g., geothermal energy) (e.g., wherein the integrated process synergistically reduces transportation costs, utilizes byproducts of processes, minimizes water usage, and / or incorporates water treatment) (e.g., wherein the integrated process comprises in- situ generation of hydrogen gas via brine injection into iron-rich formations, with enhanced heat recovery and / or co-production of amorphous sihca, e.g., featuring application of pressure modulated hydraulics and / or geochemical control).

[0049] In certain embodiments (of any of the aspects above), the machine learning module comprises a Kolmogorov-Arnold Network (KAN) (e.g., a multilayer KAN trained to produce the one or more outputs comprising one or more thermodynamic quantities selected from the group consisting of Gibbs free energy (AG), enthalpy (AH), entropy (AS), equilibrium constantAtty. Docket No.: GE0001PCT_8022-00200(K), heat capacity (Cp), and reaction rate).

[0050] In certain embodiments, the one or more inputs used by the KAN comprises one or more members selected from the group consisting of mineral composition (e.g., magnetite concentration), porosity, permeability, resistivity, fluid composition / chemistry, fluid saturation, temperature, pressure, hydrogen concentration, CO2 concentration, salinity of a circulating fluid, fracture density, and oxidation-reduction potential (ORP).

[0051] In certain embodiments (of any of the aspects above), the machine learning module comprises a language model (e g., a large language model, LLM) (e.g., wherein the language model comprises one or more members selected from the group consisting of an Adversarial Generative Network (GAN), a Variational Autoencoder (VAE), and a Transformer-based Model) (e.g.. wherein the language model is applied to geothermal well data bases).

[0052] In certain embodiments, the language model: (a) uses as input (i) sequences of chemical reactions and / or (ii) conditions that represent changes in the process (or the integrated process) based on well data; (b) tokenizes the input (e.g., breaks the chemical reactions into individual components such as reactants, products, and conditions, that can be understood by the language model); and (c) is trained to produce output data comprising predicted one or more thermodynamic quantities and / or reaction outcome.

[0053] In certain embodiments (of any of the aspects above), the machine learning module simulates reactive flow in a fluid-filled crack (e.g., analogous to shale gas fracking) to optimize pressure control (e.g., in a Huff and Puff product! on / inj ection system).

[0054] In certain embodiments (of any of the aspects above), the method further comprises determining, by the processor of the computing device, one or more process parameters relating to the design and / or control of the process for production of hydrogen from the geologic environment (e.g.. the subsurface rock formation), wherein determining the one or more process parameters comprises using one or more conventional process models (e.g., constitutive models based on the laws of physics) (e.g., chemical engineering, 3D mechanical modeling, mechanical engineering process simulators, multiphysics, and / or reactive transport simulators, e g., finite element models (FEM), and / or discrete element models (DEM)) (e.g., dynamic process / unit operation simulators for process design and / or process control, e.g.. simulators based on heat transfer, mass transfer, chemical reaction, and fluid dynamics fundamentals) (e.g., computer models that solve mass, momentum, energy', and / or species conservation equations, e.g., governing equations subject to boundary conditions / initial conditions) (e.g., one or more commercial process simulators such as CHEMCAD by Chemstations, Aspen Plus, Aspen HYSYS, DWSIM, PRO / II, ProSimPlus, SuperPro Designer,Atty. Docket No.: GE0001PCT_8022-00200 and gPROMS, as well as computational fluid dynamics simulators such as ANSYS CFX, ANSYS Fluent, ANSYS Multiphysics, COMSOL Multiphysics, FL0W-3D, STAR-CD, STAR-CCM+, OpenFOAM, AVL FIRE, and ANSYS Polyflow, and / or one or more mechanical simulation models such as Ansys, Simulink, SolidWorks Simulation, AnyLogic, and Altair OptiStruct, GoldSim, Autodesk CFD, Dassault DELMIA, Simcenter, NI Multisim, Realflow, Simio. Cadence Spectre, and Dassalut SIMULIA).

[0055] In some embodiments, the method comprises determining, by the processor of the computing device, using a digital twin (e.g., a digital twin of a particular geologic formation / site - a digital representation of a formation / site over time, e.g., updated with realtime data and / or data from conventional 3D and / or process simulation and, optionally, a machine learning module), (i) at least one of the one or more outputs relating to the design and / or control of the process for production of hydrogen from the geologic environment (e.g., the subsurface rock formation), and / or (ii) one or more process parameters relating to the design and / or control of the process for production of hydrogen from the geologic environment (e.g., the subsurface rock formation).

[0056] In certain embodiments (of any of the aspects above), the design of the process (or integrated process) comprises identification of one or more candidate sites for in-situ production (e.g., extraction or harvesting) of geologic hydrogen (e.g., wherein, in addition to Fe2+content of a formation at a candidate site, the machine learning module considers factors such as transportation availability and / or transportation costs, availability of a suitable water supply, and / or other practical factors).

[0057] In another aspect, the invention is directed to a process for in-situ generation of hydrogen gas from a subsurface geologic formation (e.g., and, optionally, production of geothermal heat and / or amorphous silica and / or a rare earth mineral), said process comprising injecting brine into the subsurface geologic formation (e.g., wherein the formation is iron-rich) (e.g., an ultramafic formation, a mafic formation containing Fe(2+)-rich minerals such as olivine (e. g., a troctolite), a banded iron formation (BIF), e.g., iron-rich hematite and / or magnetite, with adjacent silica-rich layers), recovering generated hydrogen gas, recovering heat produced from exothermic reaction, and. optionally, recovering amorphous silica (e.g.. wherein the process comprises applying pressure modulated hydraulics and geochemical control for enhanced chemical and heat recovery by facilitating dissolution of Fe(2+) from the rock formation). In some aspects, the heat produced from the exothermic reaction can be used to control a temperature of the fluid in the subsurface formation. Temperature can play a role in a number of processes including the temperature induced weathering (as described in moreAtty. Docket No.: GE0001PCT_8022-00200 detail herein) as well as the reaction rates for the reactions occurring in situ. The heat produced from the exothermic reactions can be used to obtain a desired temperature to induce the temperature induced weathering and / or modulate the rate at which the reactions occur.

[0058] In certain embodiments, the process comprises use of a machine learning module (e.g., any of the machine learning modules described herein) to perform at least one of (i) to (iii) as follows: (i) identify a site for the process, (ii) design the process, and (iii) control the process.

[0059] In certain embodiments, the process comprises applying pressure modulated in time and amplitude in a multitude of formation dependent, patterns, e.g. “pressure-wavelets” (e.g., including performing a Huff and Puff process). Other processes such as temperature modulation, and reaction chemistry to produce pressure variations in situ can also be used alone or in combination with pressure modulations. In some aspects, the temperature modulation and / or reaction chemistry can create stress within the subsurface rock on a localized level, which can contribute to the weathering effect.

[0060] In certain embodiments, the process comprises alternately injecting high pH and low pH brines in the rock formation to enhance dissolution of minerals from the rock (e.g., performing cyclic leaching).

[0061] In another aspect, the invention is directed to a process for in-situ generation of hydrogen gas from a repurposed diamond mine (e.g., a kimberlite and / or lamproite dyke or pipe), said process comprising injecting brine into the repurposed diamond mine and recovering generated hydrogen gas (e.g., and recovering heat produced from exothermic reaction, and, optionally, recovering amorphous silica and / or rare earth minerals) (e.g., wherein the process comprises applying pressure modulated in time and amplitude in one or more, formation dependent patterns (e.g., pressure-wavelets) and geochemical control for enhanced chemical and heat recovery by facilitating dissolution of Fe(2+)) (e.g., wherein the process comprises use of a machine learning module (e.g., as described herein) to perform at least one of (i) to (iii) as follows: (i) identify a site for the process, (ii) design the process, and (iii) control the process) (e.g., wherein the process comprises alternately injecting high pH and low pH brines in the repurposed diamond mine to enhance dissolution of minerals (e.g., performing cyclic leaching)) (e.g.. wherein the process comprises use of a machine learning module (e.g.. as described herein) to perform at least one of (i) to (iii) as follows: (i) identify a site for the process, (ii) design the process, and (iii) control the process).

[0062] In another aspect, the invention is directed to a process for forecasting, evaluating, and / or remediating environmental hazards with stimulation and recovery of geologic hydrogen (e.g., as part of a system for geologic hydrogen, geothermal energy, amorphous silica, rareAtty. Docket No.: GE0001PCT_8022-00200 earth mineral, and / or other resource production as presented herein), the process comprising performing one or more of (i) to (vii) as follows (e.g., using a machine learning module, e.g., as described herein): (i) management of volume changes accompanying the stimulation; (ii) management of friction and strength of stimulation regions; (iii) management of shapes of stimulated regions where changes in volume and / or strength occur; (iv) management of dimensions of stimulated regions where changes in volume and strength occur; (v) management of an interaction between a background stress field and stimulated regions where changes in volume and strength occur; (vi) management of interactions between and among stimulated regions where changes in volume and strength occur; and (vii) management of sequencing of stimulating regions such that stresses generated in subsequent stimulations are relieved in the previously stimulated regions where friction is slip strengthening and slip is aseismic.

[0063] In another aspect, the present disclose is directed to a process for the controlled fracturing of a subsurface rock formation (e.g., for stimulation and recovery of geologic hydrogen, e.g., as part ofa system for geologic hydrogen, geothermal energy, amorphous silica, rare earth mineral, and / or other resource production as presented herein), the process comprising injecting a fluid having controlled composition into the subsurface rock formation in a controlled manner (e.g., at controlled temperature, flow rates, and / or pressure cycles (pressure oscillations in time), such a way that the pressure is always larger than the least compressive stress and always less than or equal to the breakdown pressure of the formation). This process can be referred to in some contexts as “soft fracturing” or “weathering” where the pressure remains below the fracturing pressure of the formation rock itself, and the controlled application of pressure (e.g., in a cyclic manner) results in the formation of fractures. The resulting fractures or fracture network may be limited in extend, for example, extending tens of meters from the wellbore. In some aspects, the process can optionally be carried out by controlling conditions of the injected fluid using a machine learning module (e.g., wherein the process comprises use of a machine learning module (e.g., as described herein)).

[0064] In another aspect, the invention is directed to a process for co-production of geothermal energy and amorphous silica using serpentinization-enhanced high-alkalinity brine with supercritical CO2 injection, the process comprising circulating a high-pH, silica-rich brine through a geothermal reservoir, utilizing heat generated by serpentinization of iron-rich rock from a rock formation, injecting CO2 which may be supercritical CO2 to control pH and / or temperature, thereby improving efficiency of silica precipitation (e.g., and facilitating carbon sequestration), and collecting the amorphous silica (e.g., wherein the process comprises use ofAtty. Docket No.: GE0001PCT_8022-00200 a machine learning module (e.g., as described herein)). While described in some embodiments as using CO2 to control the pH of the injected brine, other pH control compositions such as hydroxides (e.g., sodium hydroxide, potassium hydroxide, etc.) and / or acids (e.g., mineral acids such as HC1, H2SO4, etc.) can also be used to achieve a desired pH in the brine.

[0065] In certain embodiments, the process comprises one or more of (i) to (viii) as follows: (i) a geothermal reservoir connected to a serpentinization zone comprising a region of the iron- rich rock formation undergoing serpentinization; (ii) a brine circulation loop that extracts high- pH silica-rich brine from the serpentinization zone; (iii) CO2 or supercritical CO2 injection into the brine in the rock formation (before being brought to the surface); (iv) a surface processing unit comprising a heat exchanger that extracts geothermal energy (e.g., for electricity generation or direct use); (v) collection of precipitated amorphous silica and other metal oxides (e.g., collection, filtration, and / or processing of the amorphous silica for industrial use); (vi) enhanced silica solubility in the brine, e.g., by maintaining high temperature and high pH, further enhanced by controlled injection of supercritical CO2; (vii) controlled cooling of the brine for precipitation of the silica; and (viii) extraction of geothermal energy from the brine (e.g., before brine is cooled for silica precipitation).

[0066] In another aspect, the invention is directed to a process (e.g., a process for production of geologic hydrogen, geothermal energy7, amorphous silica, rare earth minerals, metal oxides such as iron oxide, and / or other resource production as presented herein) comprising regulating pH of brine solutions by contacting the brine with CO2 (e.g., wherein the process comprises use of a machine learning module (e.g., as described herein)).

[0067] In another aspect, the invention is directed to a process for recovery' of enhanced value from geologic Fe2+in a low pH environment (e.g., in a system for geologic hydrogen, geothermal energy, amorphous silica, metal oxides such as iron oxide, rare earth mineral, and / or other resource production as presented herein), the process comprising using one or more acids and / or chelating agents to mobilize and / or stabilize Fe2+into solution (e.g., wherein the process comprises use of a machine learning module (e.g., as described herein)).

[0068] In another aspect, the disclosure is directed to a system comprising: a processor of a computing device; and a memory having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to perform any of the methods described herein.

[0069] Described herein are the following: (i) AI / ML modeling approaches, e.g.. geomapping of temperature (T) and brine compositions availability, integrated to geodatabases (based on available well data and geological studies); (ii) Identification and analysis of rock formationsAtty. Docket No.: GE0001PCT_8022-00200 enriched in Fe(2+) including but not limited to formations rich in the minerals or elemental combinations, Grunerite (FevSisCMOHty). Hercynite (FeAhO^, Siderite (FeCOty Magnetite (FesCh), Minnesotaite (Fe,Mg)3Si40io(OH)2, olivine, pyroxene, banded iron, greywackes, kimberlite, lamproite and basalts; (iii) Combining geothermal data for selection of appropriate T from thermal gradient information; (iv) Extrapolation and synthesis of estimates for geophysical data to predict unmapped and sparsely studied regions; (v) Extraction media selection - brine control (pH, silica activity, dissolution of H2. etc.) and availability for maximum profitability; (vi) Integration and use of site specific well and geophysical data to construct a “digital twin" of the specific formation for optimization of economic recovery; (vii) Observation and prediction of mechanical properties within the formation for frack technique selection; (viii) Observation and prediction of fracture densities and transmissivities; (ix) Prediction for guidance on drilling approach (vertical / horizontal); (x) Use of downhole, or surface sensors (e.g., this could use both existing geothermal wells and hydrogen wells). For example, a gravity gradiometer may be used for boreholes that w ould pick up “nearby” density contrasts. Borehole gravity and gravity gradiometry and magnetics are important measurements in the geophysics community - but borehole platforms for these measurements are largely nonexistent (most is airborne, ship based) to provide signals from completed or incomplete wells indicating, after a suitable analysis possibly involving the use of deterministic models or statistical inference (for example, using Al), that rocks are present at one or more depths that when stimulated (e.g.. when fracked, and / or exposed to water, or brine at a range of pH levels, and at a favorable pressure and / or temperature) are likely to evolve heat and hydrogen. Sensors may indicate gas composition (i.e., hydrogen, sulfur, helium), temperature, pressure, pH, or the presence of water or brine, or certain minerals, or metallic or non-metallic atomic species. Wells may be drilled for the purpose of surveying or searching for favorable production conditions, or may be drilled for other purposes such as geothermal exploration or production. Magnetotelluric (MT) measurements are sensitive to electrical conductivity structure, which depends on mineralogy, brine properties, fracture density, and the like. Time variations in electrical properties, magnetic properties, densities and permeabilities result from ongoing reactions. Seismic emission tomography can reveal fracture density both prestimulation and post-stimulation; (xi) Creating Al models trained with a combination of well drilling data (as noted above) and production data (H2, metals, pH, T, P, gases etc.) during production, e.g. a geophysics / Geochem-based Al data and analysis capability for reducing environments; (xii) Using the Al models of the previous step to achieve a desired rate of heat, hydrogen or mineral production from a stimulated well, or wells - i.e., obtaining P, T, pH,Atty. Docket No.: GE0001PCT_8022-00200 injection rates from the model that provide the desired rate, which may be adjusted to provide a maximum rate, or lower rate consistent with the level of demand for one or more products; (xiii) Model based Al outputs to include, for example, optimal time constants for time varying pressure, pH, temperature, water / rock ratio, and CO2 concentration; and (xiv) Model / Al that identifies specific geographic sites for securing of exploitation leases.

[0070] The systems and methods described herein can take into account a number of parameters such as the following specific non-hydrocarbon formation compositions, such as. formations including Magnetite, Siderite, Grunerite, Hercynite, Olivine, Pyroxene, Minnesotaite, Riebeckite; Specific formation access using: separate injection and recovery wells, vertical + / - horizontal; single bores semibatch / concentric verticals; and reactant stream delivery (P,T, conditions); specific thermal hydraulics, fracture, and thermal management: permeability imaging via signal processing of passive seismic; pressure and / or temperature modulation for fissure and fracture formation; delivery of specific stimulation input fluids; downhole heating (Shell Sure); specific stimulation fluids for high productivity: SCCO2, CO2, Acids (HC1, H2SO4, H2CO3), Bases (e.g., NaOH, Mg(OH)2,Ca(OH)2); provisions for CO2 by ay of injection as well as generation in situ by down-hole combustion for both heat and CO2; control of solubility of desired products, e.g. Li2CCh vs Na2CCh; brine control, H2 in solution vs. facilitate bubble formation; materials for surfactants and controls of surface tension, e.g., to maintain H2 in solution; mineral etching via media for dissolution of surface Fe3+. e.g., utilization of physical chemical processes to maintain permeability / porosity and accessibility to Fe2+; mineral grain and formation fracturing via physical chemical processes to maintain permeability / porosity and accessibility' to Fe2+; specific control for fluid delivery of stimulation fluids and product recovery: Modulation and measurement of the downhole pressure as a function of time, P(t) in frequency, amplitude, and phase (e.g. Huff and Puff). Use of measured pressure variation in time, P(t) to derive information on permeability, etc.; and pH(t), Water / Rock ration WRR(t) which together with P(t) improve or optimize the extraction of Fe(2+), reaction, and transport of products from the bulk rock to the extraction stream; and specific topside processing of output fluids in a georefinery: product discharge stream management subsystem: pressurized liquid or multiphase material stream management including pressure preservation and utilization and heat recovery for power production including steam cycle, thermoelectric, direct integration; gas phase product recovery subsystems including gas recovery (H2, He) and flash separation (topside or downhole), membranes, and drying, etc.; and mineral and reagent recovery’, separation, and utilization including membranes, electrochemical, metals, CO2 sequestration and separation with basicity,Atty. Docket No.: GE0001PCT_8022-00200 alkalis (Li, Mg, Ca ), and / or silicas.

[0071] Described herein are specific mineral collections containing large fractions of Fe2+, and specific chemical processing systems. The specific mineral collections containing large fractions of Fe2+can include, for example, mineral collections including olivine, pyroxene, magnetite, siderite, grunerite, hercynite, ultramafic formations, mafic formations including troctolites, and banded iron formations (BIFs). These may be present in an ore body or other deposit of overall low grade such that it cannot be economically mined for iron and steel making. Such ore bodies or other deposits may be at the surface (e. g., mine tailings or other waste disposal sites) or very close to the surface (e.g., open pit) or at depth, and therefore depending on the ore body, it may be appropriate to produce hydrogen and / or heat using either or both of the disclosed surface, or downhole methods. Co-existent alkali can be used to create high pH and conditions for carbonate and selected intermediates formation; and diamond mines and / or subsurface coal mines can be used or accessed through, iron rich rock.

[0072] The specific chemical processing systems can include reactors, heating systems, reactants and extraction media, and / or separation systems. The reactor conditions can include temperatures in arange of 125-400 °C and pressures in a range of 1-1.000 bar. Specific control of H2 and H2O activities to provide the reaction free energies that operate under hydrothermal conditions. The heating systems can include primarily electric, solar thermal, nuclear, and / or combustion-based heating. The heating systems can be integrated with existing topside facilities to produce heat, where the topside facilities can include, but are not limited to, thermal power plants, cement manufacturing, and / or metals processing (e.g. iron). Various types of heat recovery and integration can also be incorporated into the system.

[0073] Various types of reactants and extraction media are also disclosed such as water, steam, CO2 (->CO), and aqueous acids, bases, chelants, ionic strength enhancers, and / or oxidizers.

[0074] The separation systems can include any suitable separation units. For example, the separation system can include membrane separators, electrochemical separators, flashes for liquids, gas purification, and or mineral separations.

[0075] In some embodiments, the present disclosure can relate to systems and methods for forecasting, evaluating and remediating environmental hazards associated ith stimulation and recovery. The systems and methods described herein take into account internal deformation and stress caused by variations in fluid pressure in fractures and / or caused by large (e.g., about 35 %) volume changes due to chemical reactions (e.g., chemical reactions change strength and frictional properties of rocks), induced seismicity; surface deformation; fluid sourcing; and / or fluid disposal.Atty. Docket No.: GE0001PCT_8022-00200

[0076] Presented herein are systems and method for engineering hydrogen, energy, or other resource stimulation of geological environments, e.g., subsurface rock formations, that minimize the risk from internal deformation and induced seismicity of the geological environment. These include integration of field data, laboratory data, models, and field experiments. In certain embodiments, key parameters include friction, strength, fracture geometry, fracture length, volume changes, and measurements of seismic activity and deformation.

[0077] Components of these systems and methods include management of volume changes accompanying stimulation; management of friction and strength of stimulated regions; management of shapes of stimulated regions; management of dimensions of stimulated regions where changes in volume and strength occur; management of the interaction between the background stress field and the stimulated regions where changes in volume and strength occur; management of the interactions between and among the stimulated regions where changes in volume and strength occur, and / or management of the sequencing of stimulating regions such that the stresses generated in subsequent stimulations are relieved in the previously stimulated regions where the friction is slip strengthening and slip is aseismic.

[0078] With respect to the management of volume changes accompanying stimulation, the volume changes accompanying stimulation can be large in magnitude and either positive or negative, depending on the densities of the reactants and products. Which reactions occur depend on the mineralogy of the source rock, the composition of the stimulating brine, and the local conditions where the reaction is occurring (P, T, pH, oxygen rugacity, silica activity, etc.). In certain embodiments, a novel component of this integrated approach is to choose the source rocks, reactions, etc. with the risk tolerance of the accompanying infrastructure in mind.

[0079] With respect to the management of friction and strength of stimulated regions, the changes in frictional behavior and strength accompanying stimulation depend on the properties of the reactants and products. Which reactants and products are present depend on the mineralogy of the source rock, the composition of the stimulating brine, and the local conditions where the reaction is occurring (P, T, pH, oxygen fugacity, silica activity, etc.). In certain embodiments, a novel component of the integrated approach is to choose the source rocks, reactions, etc. with the risk tolerance of the accompanying infrastructure to induced earthquakes in mind.

[0080] With respect to the management of shapes of stimulated regions where changes in volume and strength occur, both the stresses generated in the surrounding medium and the strength of a stimulated region depend on its shape. For the same total volume change, theAtty. Docket No.: GE0001PCT_8022-00200 external stress state and the internal stresses are very different for, e.g., spherical vs pancakeshaped regions. These differences allow for management of stimulation to decrease risks.

[0081] With respect to the management of dimensions of stimulated regions where changes in volume and strength occur, the propensity for unstable slip, the distribution of internal and surface deformation, and other important factors depend on the dimensions of stimulated zones. Thus, distributing the same total stimulated volume over multiple zones will result in different behavior than concentrating it into a single region. In certain embodiments, this factor is important to consider in overall system design.

[0082] With respect to the management of the interaction betw een the background stress field and the stimulated regions where changes in volume and strength occur, the stresses in a stimulated region depend on the orientation of the region with respect to the background stress field. Choosing the orientation of stimulation appropriately can reduce risk of failure.

[0083] With respect to the management of the interactions between and among the stimulated regions where changes in volume and strength occur, the stresses from multiple closely spaced stimulated regions will interact. This interaction can be manipulated to minimize risks.

[0084] With respect to the management of the sequencing of stimulating regions such that the stresses generated in subsequent stimulations are relieved in the previously stimulated regions where the friction is slip strengthening and slip is aseismic, stimulation that leads to slipstrengthening frictional properties will produce regions that tend to deform aseismically. Appropriate sequences of stimulation provide a mechanism to reduce the risk of inducing earthquakes while still generating large volume changes.

[0085] In certain embodiments, it may be economically advantageous to co-locate H2 and heat production wells with one or more industrial processes in a combination that consumes substantially all of the produced quantities or heat, hydrogen and alkaline brines, thereby obviating, or eliminating the need to store or transport them to distant locations. This may involve one or several co-located industrial processes in any combination depending on the output levels and products obtained from the co-located production w ells, and the availability of raw materials that may be required. Other consumers of heat and hydrogen at such an industrial complex may include residential and commercial buildings, as well as electrical power generating equipment including fuel cells, engines and turbines. In certain embodiments, the production rates of heat and hydrogen may be adjusted based on an Al and / or other model, in order to closely match the instantaneous demand, thereby minimizing the cost of associated storage. The hydrogen production operation itself may consume a portion of the produced heat in order to achieve a desired rate of hydrogen production, and it may furtherAtty. Docket No.: GE0001PCT_8022-00200 consume further produced heat and hydrogen converted to electricity.

[0086] In addition to systems for production / extraction of hydrogen, geothermal energy, amorphous silica, and / or rare earth minerals from geological environments, other systems for integration in an onsite process include, for example, systems for ethylene production; ammonia production via the Haber-Bosch process; production of E-fuels (e.g., via Fischer- Tropsch process) including e-ammonia. e-diesel and e-gasoline, e-kerosene wherein at least some of the process heat is provided by electricity; enhanced biofuel production in which produced geothermal heat is used in cracking and refining, and / or geothermal hydrogen may be used to increase the amount of biofuel produced; DRI for steel production; syngas production for use in one or more of the co-located industrial processes, including electricity generation; and / or cement and green cement production

[0087] Certain embodiments described herein relate to the exploitation of the naturally occurring heat, minerals, and reduced form of iron, Fe(2+), that occur in many types of subsurface rock formed in the absence of oxygen. Fe(2+) has the potential to donate an electron in oxidation reactions and produce a number of important and valuable chemical products. The overall optimization provides an economic potential for a given geographic location based on the site-specific exploitation potential. The output provides specific sites that might be advantageously leased and once exploitation commences the output provides a prescription for exploitation for maximum value.

[0088] In some embodiments, the systems and methods described herein employ artificial intelligence / machine learning (AI / ML) models to make use of the enormous geochemical and geothermal data bases to identify locations with the highest economic potential to make use of the Fe(2+) oxidation to Fe(3+) and what specifically the most profitable product slate will be.

[0089] In some embodiments, a mixture of non-condensed phase reactants and promotors are made to contact the rock at a specific site with the mixture being guided by the predictive Al model provided with site specific information. A primary component of the non-condensed phase mixture is water, which can act to dissolve the minerals including Fe(2+) into solution for further processing. Specific conditions that are controlled include pressure as a function of time (P(t)). pH as a function of time (pH(t)), and concentration / dilution as a function of time (e.g., Water-to-rock ratio, WRR(t)). In certain embodiments, the periodicity of these controlled time dependent processes are a critical parameter that is informed by the Al formation model.

[0090] Specific sites (formations) with specific minerals and specific available hydrations inform the specific products whether they are hydrogen ions from water accepting the Fe2electron from oxidation to form hydrogen or other electron acceptors and base. In the presenceAtty. Docket No.: GE0001PCT_8022-00200 of reduction potential and carbon dioxide, in other embodiments, hydrocarbon products and oxygenates (formic acid, etc.) can be generated as the commercial product.

[0091] In some aspects, the present disclosure relates to a process for fracture generation in a subsurface formation using a variety of techniques. In some instances, this process uses the standard process for generating fractures in the subsurface to control fluid flow for hydrocarbon and geothermal production, hydrofracturing. In hydrofracturing, a mixture of fluid and solids is injected into the subsurface at a pressure high enough to overcome the preexisting stress caused by the weight of the overburden. Fluid pressures reach as high as ~ 100 MPa in hydrofracturing, exceeding the breakdown pressure of the rock formation.

[0092] In some instances, the present disclosure introduces an alternative method for fracturing of the rock formation to increase the surface area of rock exposed to brine. This method can be accomplished by a combination of stresses generated by pressure variations of the brine, temperature variations of the brine, and / or temperature and volume changes resulting from chemical reactions in the rock formation (e. g., serpentinization). The various changes can occur below the breakdown pressure of the rock itself. Because rock formations are made up of grains of minerals of varying shapes and sizes and with different and anisotropic elastic compliances and thermal expansivities, separated by weak grain boundaries, modulation of the brine pressure, P(t), and temperature T(t) in frequency, amplitude, and phase can fatigue (e.g., weather) the rock formation, leading to a controlled fracture growth at stresses below the short- time breakdown pressure or fracture strength. This controlled fracturing results in intricate fracture distributions with surface areas much larger than that of conventional hydrofracks, which are generated by pressures greater than the breakdow n pressure of the formation and are largely uncontrolled based on the use of a pressure above the breakdown pressure of the formation in the hydrofracturing process.

[0093] In some aspects, the present disclosure relates to fracturing technologies for the production of hydrogen and other resources from geological formations. A new method for controlled fracturing of rock can be used that results from the volume changes that accompany the reaction of water with iron-rich rocks in the subsurface, that is, "reaction-based" or "‘reaction-induced” fracturing. The fracturing processes disclosed herein can occur at below the bulk fracturing pressures, which allows the fractures to occur on a localized and controlled extent within the formation. In some aspects, the fracturing techniques use serpentinization- induced fracturing processes and cyclical huff and puff production systems. Other techniques such as the application of sub-fracturing pressures in a cyclic manner can generate fractures and micro-fractures suitable for the generation of hydrogen. The fracturing process can resultAtty. Docket No.: GE0001PCT_8022-00200 in an increase in the surface area of the formation available for reaction with water and other chemicals to produce hydrogen in-situ. The hydrogen generate can be in solution within the water and / or free hydrogen that can then be recovered as a hydrogen product at the surface.

[0094] The volume changes associated with the reaction based fracturing reactions can be very large, up to ~ 50% increase in volume in some serpentinization reactions. The accompanying crystallization pressures are 200 - 1500 MPa in amplitude - far greater than the pressures driving hydrofracturing. These pressures are generated locally, not far away at the well head as in hydrofracturing. Controlled reaction-induced fracturing is both more powerful and more controllable than hydrofracturing, providing a new process for controlling fracturing in the subsurface.

[0095] For serpentinization at the scale of individual olivine grains, reaction-induced fracturing is the mechanism by which water penetrates into and reacts with grain interiors, accompanied by an enormous increase in reactive surface area. This process is show n schematically in FIG.1. In some aspects, a serpentinization process can be used to create fractures. The serpentinization process leverages geochemical reactions to create enhanced permeability networks within target formations. The serpentinization reaction involves the conversion of olivine-rich rocks according to the reaction:3(Mg,Fe)2SiO4 + 4FLO 2Mg3Si2O5(OH)4+ Fe3O4+ Hz

[0096] This reaction exhibits thermodynamic properties that enable controlled fracturing applications. In various embodiments, the process may utilize formations containing olivine concentrations ranging from about 10 wt% to about 95 wt% (broad range), preferably from about 30 wt% to about 80 wt% (intermediate range), and most preferably from about 50 wt% to about 70 wt% (specific range).

[0097] The chemistry of the fluid can be controlled to promote stimulation in order to tune the rate at which fractures occur, the extent to which the fractures occur, and the rate at which the resulting surface area produces hydrogen. Reaction-induced volume changes in localized stimulated regions will have large effects on the state of stress in the surrounding regions. By controlling the shapes of these localized stimulated regions, the fracture propagation between and among these regions can also be controlled, providing control of the fracture pattern and fluid flow' paths to and from the stimulated regions.

[0098] Specifically, the serpentinization process generates substantial volume changes that serve as the driving force for reaction-induced fracturing. In various embodiments, volume increases range from about 5% to about 60%, from about 20% to about 50%, or about 35% toAtty. Docket No.: GE0001PCT_8022-00200 about 45%, with some instances showing up to 50% volume changes compared to approximately 1% in conventional extraction methods.

[0099] The associated density reduction provides additional fracturing mechanisms, with initial rock densities ranging from about 2.8 g / cm3to about 4.0 g / cm3, from about 3.2 g / cm3to about 3.6 g / cm3, or about 3.4 g / cm3, transforming to final densities ranging from about 2.0 g / cm3to about 3.0 g / cm3, from about 2.3 g / cm3to about 2.7 g / cm3, or about 2.5 g / cm3.

[0100] The serpentinization process can exhibit exothermic characteristics that contribute to self-sustaining fracturing mechanisms. Per cubic meter of serpentinite formation, the process generates thermal energy ranging from about 4 MJ to about 10 MJ, from about 5.5 MJ to about 7.5 MJ. or about 6.6 MJ, depending on the specific composition of the formation and extent of the reaction. Under adiabatic conditions, this energy generation produces temperature increases ranging from about 150°C to about 400°C, from about 200°C to about 320°C, or about 260°C, creating enhanced reaction kinetics and improved fracturing efficiency.

[0101] The reaction-induced fracturing process generates crystallization pressures on a localized scale that substantially exceed conventional hydrofracturing techniques, where the bulk pressure in the formation (e.g.. at a distance away from the reaction) can remain below a fracturing pressure. Crystallization pressures range from about 100 MPa to about 2000 MPa, from about 150 MPa to about 1600 MPa, or from about 200 MPa to about 1500 MPa, compared to approximately 100 MPa in conventional hydrofracturing systems. These elevated pressures are generated locally at reaction sites rather than remotely at subsurface locations, providing enhanced controllability through localized chemical reactions rather than distant pressure applications. The localized pressure generation enables fracture propagation control while still providing permeability enhancement.

[0102] The reaction-induced fracturing process can create self-propagating fracture networks through controlled swelling from serpentinite conversion. Near fracture tips, olivine experiences preferential conversion to serpentinite, with inj ected brines draw n tow ard areas of highest tensile stress concentration. The process maintains fracture tip advancement through sustained chemical reaction at the advancing fracture front. Operating temperatures for fracture propagation range from about 150 °C to about 500 °C, from about 200 °C to about 400 °C, or from about 250 °C to about 350 °C. Operating pressures range from about 50 bar to about 4000 bar, from about 100 bar to about 3000 bar, or from about 150 bar to about 1000 bar.

[0103] Hydrogen-producing reactions between water and other minerals (e. g., minnesotaite) result in large volume decreases. Engineering such volume decreases via stimulation of a localized region is equivalent to providing negative pressures in hydrofracturing, opening up aAtty. Docket No.: GE0001PCT_8022-00200 new mechanism for generation and control of fractures. This process allows the rates and surface areas of the fractures and fracture network to be controlled, resulting from engineering the fluid composition, temperature, and the like. Other reactions that do not involve production of hydrogen can also lead to large changes in volume, both expansion and contraction. Stimulating these other reactions provides an additional mechanism for controlling fracturing.

[0104] The process can be improved through the introduction of additional reaction surface area, for example, through the formation of fractures. The processes described herein can be used to create the surface area. In addition to, or as an alternative to, the reaction induced fracturing, additional fracturing processes can use pressure variations to produce the fracture network, where the injection pressures can change over time and can remain below the breakdown pressure of the rock itself. In some embodiments, the peak pressure(s) used with the pressure based weathering process can remain below about 0.95 times the breakdown pressure of the rock (Pbreakdown), below about 0.9 Pbreakdown, below about 0.85 Pbreakdown, or below about 0.8 Pbreakdown. The pressure can be cycled between a minimum pressure and a maximum pressure within the weathering process.

[0105] A comparison between traditional hydrofracturing and the weathenng process described herein is shown in FIGS. 2A and 2B. In a conventional hydraulic fracture process, a single large fracture is formed from injection through a w ell bore a high pressure brine at a constant flowrate well above the rock break down stress as shown in FIG. 2A. The hydrofracturing process well above the breakdown pressure is mostly an uncontrolled process. As shown in FIG. 2B, a dense fracture network (high fracture density) can be formed for effective serpentinization. This can be created by applying cyclic pulse injections using pressure and / or temperature variations. This has two important effects: 1) as the number of cycles increases the break down stress of the formation is substantially lowered, thereby creating many more fractures at lower injection pressures; and 2) cyclic fluid injection enhances the hydraulics of the fractured formation, increasing the permeability of the resulting fracture network which is useful for serpentinization. Overall this is a fully controlled process with low or no induced seismicity risk. The frequency of the pressure oscillation can be on the order of 10s of minutes to hours, and is overlapping with the pressure cyclic stimulation of the hierarchal fracturing process caused by the serpentinization.

[0106] This process is further shown in FIG. 3. Cyclic pressure induced weathering (e.g., fatigue) progressively damages the rock by applying a cyclic pressure process causing a larger process zone activating many crack tips formed by cyclic stress changes. The applied pressure can oscillate above the minimum stress and below the breakdown stress or pressure.Atty. Docket No.: GE0001PCT_8022-00200

[0107] In some aspects, both pressure and temperature variations can be applied (as described in more detail below), as shown in FIGS. 4A and 4B. In this embodiment, pressure induced weathering may be further enhanced by applying temperature oscillations. The pressure and temperature oscillations can be in-phase or out of phase, and in some aspects, the temperature oscillations can be out of phase with the pressure cycles so it expands the thermal stress. This can cause fractures to shrink in other areas of the fracture of the already formed fracture wall behind the active pressure cyclic damage zone. The result is a fracture network having increased surface area for reactions as described in more detail herein. Any of the oscillations as described herein (e.g., pressure, temperature, flow rate, etc.) can be controlled using one or more controllers, including both Al and traditional control systems as described herein.

[0108] As shown in FIG. 5A and 5B, the pressure waveforms can take various shapes such as a triangular waveform (e.g., as shown in FIG. 5 A), semi-sinusoidal waveforms (e.g., as shown in FIG. 5B), sinusoidal waveforms, step functions, and the like. The average cycle time can be between about 0.5 hours to about 10 days, or between about 1 hour to about 48 hours. The mean pressure can be maintained at a sufficient level to maintain the fractures that are formed in an accessible state, which can allow for further fracture formation during the process. The process can result in fractures forming at the grain boundaries, which can produce a significant surface area increase at the fracture faces. The w eathering process can be continued during the various processes described herein to continually eather the rock and provide access to the grain surfaces for extraction and reaction.

[0109] In some aspects, a pressure induced weathering process can comprise selecting a mean pressure close, but less than as described herein, to the breakdown pressure of the rock, and modulating the injection fluid pressure about the selected mean pressure. In some aspects, a low frequency modulation can be used to extract water along with heat and hydrogen and other products from the formation (hours to weeks). Higher frequencies can be used to accelerate the weath ering of the formation and thereby increase the production of hydrogen, heat and other products. In some aspects, a single modulation frequency can be chosen as to enable extraction and accelerate weathering and this may be in the range of minutes to hours. In some aspects, the sum of the modulated and static pressures may exceed, or preferably not exceed, the breakdow n pressure (e.g., the fracture strength of the rock).

[0110] The frequency of the pressure variations can be changed over time. For example, the frequency of the pressure variation can be initially selected to accelerate the pressure induced weathering process. The selected frequency can take into account the required input energy to pressurize the fluid and the extent of the fluid injection, which can control the extent of theAtty. Docket No.: GE0001PCT_8022-00200 fractures into the formation. Once the fractures are formed, the frequency can be modified to allow for a cyclic flow of fluid from the formation (e.g., as part of solution mining disclosed herein) or continue the weathering process. The cyclic pressure variations can be continued during any of the processes described herein.[OHl] In some embodiments, the injected fluid can use temperature variations over time alone or in conjunction with the reaction induced fracturing and / or pressure induced weathering to create fractures in the rock. As with the pressure induced weathering, the injected fluid temperature can be varied using any suitable temperature profiles to create thermal stress in the rock while also affecting the chemistry within the formation (e.g., solubilities, reaction rates, etc.). The cyclic stress can create fractures that can lead to an increased surface area available for reactions. In some aspects, the use of temperature cycles can result in differential thermal expansion that can initiate the grain boundary fractures, which then be grown using continued thermal cycling with or without pressure induced weathering and / or reaction induced fracturing.

[0112] In some aspects, alternating injection and extraction cycles ("‘Huff and Puff’ process) can be used to improve the extraction processes in Fe(2+)-rich environments. This process is shown schematically in FIGS. 6A and 6B. The huff and puff production process can use a single well with alternating injection and production, dual well configurations where Well A and Well B operate in alternating cycles - when Well A injects, Well B extracts, and vice versa, and / or a multi-well system where at least one well is injecting a fluid and at least one well is producing a fluid. In a multi-well configuration, the different wells can be cycled over time to change the injection and production profiles. Cycle durations can range from about 0.5 hours to about 48 hours, from about 2 hours to about 24 hours, or from about 6 hours to about 12 hours. The alternating cycle approach enables optimal pressure maintenance and enhanced mass transfer compared to continuous flow systems.

[0113] The system can use multiple time-dependent variables to improve the production efficiency using one or more controllers. Pressure modulation can follow predetermined profiles where pressure as a function of time (P(t)) in the formation ranges from about the magnitude of the least compressive stress to about the breakdown pressure, from about the magnitude of the least compressive stress to about 90% of the breakdown pressure, or from about the magnitude of the least compressive stress to about 80% of the breakdow n pressure (specific range). The pH control as a function of time (pH(t)) represents a controllable parameter, with pH values ranging from about 2 to about 13, from about 4 to about 11, or from about 6 to about 9. The pH modulation prevents reaction suppression while maintainingAtty. Docket No.: GE0001PCT_8022-00200 dissolution kinetics. Water-to-rock ratio optimization (WRR(t)) controls reaction stoichiometry’ and mass transfer efficiency. Water-to-rock ratios range from about 0. 1 to about 5.0, from about 0.2 to about 2.0, or from about 0.3 to about 1.0.

[0114] The system can use chemical injection protocols as described in more detail herein including carbonates (e.g., NaHCCE), carbon dioxide (CO2), supercritical carbon dioxide (sCCh). and engineered brines, carbonate concentrations can range from about 0.01 M to about 1.0 M, from about 0.05 M to about 0.5 M, or from about 0.1 M to about 0.3 M. Supercritical CO2 injection rates can range from about 10 kg / hr to about 1000 kg / hr, from about 50 kg / hr to about 500 kg / hr, or from about 100 kg / hr to about 300 kg / hr, enabling precise pH control and enhanced reaction kinetics.

[0115] The resulting fractures an exhibit a higher surface area available for reaction to produce hydrogen in situ. Surface area improvements through reaction-induced fracturing can creates increased permeability7ranging from about 1015m2to about 1010m2, from about 1014m2to about 10-" m2, and or from about 1013m2to about 1012m2.

[0116] In solution mining, brines having varying compositions can be used to recover minerals from the formation. Solution mining can be used to recover metals, rare earths, and other species resulting from any water-rock reaction that has negative Gibbs Free Energy accompanied by a density7change of greater than a few percent. In some aspects, the solution mining processes disclosed herein can be used in a process unrelated to hydrogen production (e.g.. it may not be a co-product of a hydrogen recovery process), but rather may be the primary product of a process involving a rock that may, or may not be suitable for hydrogen production. The rate of extraction can be increased by the increase of surface area resulting from the fracturing driven by a weathering process using any of the processes described herein. The production rate from solution mining may be further increased by adjustment of the pH and temperature to increase the rate of chemical dissolution of the rock matrix and desired species. The species going into solution as a result may be produced with the water and subsequently separated at the surface.

[0117] In some aspects, high and low pH brines can be alternately injected into the mineral deposit to enhance the dissolution of minerals from the rock. A system for solution mining in shown schematically in FIG. 7. As shown, a first wellbore 302 and a second wellbore 312 can extend into a subsurface rock formation. The first wellbore 302 can be in fluid communication with a first fracture network 304, and the second wellbore 312 can be in fluid communication with a second fracture network 314. First and second brine controllers 306, 316, respectively, can be used to control the composition of the brine injected into the first and second fractureAtty. Docket No.: GE0001PCT_8022-00200 networks 304, 314. The brine used in the injection can have compositions as described in more detail herein. The controllers 306. 316 can also control the pressures and injection / production cycles for each of the fracture networks 304, 314. In some embodiments, the fracture networks 304, 314 are not in fluid communication with regard to the fractures themselves, and the solution mining can occur individually in each fracture network. In this embodiment, fluid injected into a fracture network can be cycled and extracted from the same fracture network. In some embodiments, the first and second fracture networks 304, 314 can be in fluid communication based on the fractures forming a communication pathway. In this embodiment, a fluid injected into one fracture network can pass to the second fracture network for extraction, and the process can be reversed in a cycle fashion as described herein.

[0118] This cyclic processing takes advantage of the alternating chemical reactions that occur under different pH conditions to improve the recovery of the target mineral. For example, in high pH brines (alkaline), the brines can be used to dissolve minerals containing potassium or sodium by increasing their solubility at high pH levels. In low pH brines (acidic), the acids help to dissolve other minerals, especially those that are more soluble at lower pH, such as those containing calcium, magnesium, and some metal oxides.

[0119] In some aspects, the solution mining can occur in formations that have been subjected to the fracturing or weathering processes described herein. For example, the first fracture network 304 and / or the second fracture network 314 can be formed using a weathering process as described herein. This can allow the solution mining process to access the rock formation surfaces for increased extraction. In some instances, the fractures can close or result in restrictions that limit the fluid access to the rock face. To compensate for this scenario, the solution used for solution mining can be supplied at a mean pressure sufficient to maintain the fractures in an accessible state, which can allow the solution mining process to proceed at or above a desired reaction rate (e.g., based on a reaction rate per unit volume of rock). The pressure can be modulated as described herein during the solution mining process to maintain the fractures and / or create new fractures during the process. The pressure can be maintained below the hydrostatic fracturing pressure of the formation during the weather and solution mining process.

[0120] The alternating of high and low pH cycles can create conditions where different minerals are more readily dissolved and extracted in each cycle. This leads to a more efficient and thorough leaching process, allowing more of the target mineral to be recovered.

[0121] Cyclic leaching in solution mining relates to a huff and puff process in the following way. While the processes target different materials (oil in Huff and Puff, minerals in solutionAtty. Docket No.: GE0001PCT_8022-00200 mining), the alternating nature of the cycles is a similarity. In Huff and Puff, gases like CO2 or natural gas are injected (Huff) to increase oil mobility, followed by a production phase (Puff) where the oil flows back to the surface. In cyclic leaching for solution mining, alternating pH cycles (high pH and low pH) are injected into the deposit. In each cycle, minerals are dissolved into the brine, which is then pumped out to the surface for processing.

[0122] There are advantages of cyclic leaching in solution mining. For example, the process can result in improved hydrogen, heat, and mineral recovery. In some aspects, the recovered products such as hydrogen and minerals can be stored in the product storage 320 for transportation through an offtake 322. Alternating between different chemical environments (high and low pH) allows more thorough dissolution of a range of minerals, enhancing recovery compared to using a single pH solution. In particular for hydrogen production, the pH increases with more production of hydrogen which slows down the reaction and eventually suppresses the reaction. This would then require lowering the pH and possibly adding a catalyst possibly with an optional surfactant, as the process is driven by surface area. This means that alternating cycles may be optimal to clean or coat the reacting rock to optimize production. This can rely on careful temperature control as well as pressure. Mineral recovery (e.g., metals like Fe, Cu. U, Al, Co and / or Ni) may be used as tell-tales regarding how well the reaction picks up again. Continuous data may be obtained during the process (e.g., Temp, pH, pressure, H2 saturation, and / or composition), and fed as input to a neural network to estimate improvements of the free energy and reaction rates.

[0123] The process can also allow for selective leaching. In this process different pH levels can selectively dissolve specific minerals, which helps in selectively recovering the desired mineral while minimizing contamination from others. The process can also aid in the prevention of scaling and precipitation. Cyclic leaching prevents the build-up of scale or precipitates in the well, which can happen when certain minerals re-precipitate under constant pH conditions. Alternating pH breaks up these deposits, keeping the flow channels clear.

[0124] While described as occurring in the rock in the formation, solution mining can also be used with surface facilities. In this process, iron-rich water obtained from the rock can be produced to the surface where the hydrogen producing reactions can be performed above ground. For example, the surface facility can contain reactors that can receive the produced iron-rich water and react the produced water with minerals under controlled conditions to produce hydrogen. Any suitable reactions can be carried out at the surface using the produced reactants from the formation.

[0125] Once fractured, the chemistry within the formation can use the available elements toAtty. Docket No.: GE0001PCT_8022-00200 generate hydrogen and other products. Ferrous iron (Fe2+) in iron-rich rocks represents a significant chemical potential that can be harnessed through various processes. As shown in FIG. 8, minerals such as Olivine (Mg, Fe)2SiO4, Fayalite Fe2SiO4, Ferrosilite FeSiOs, Grunerite Fe?Si8O22(OH)2, and Magnetite Fes Or are abundant in the Earth’s crust and contain substantial amounts of Fe2+, making them suitable candidates for energy -related applications. Further, Fe+2is found in other geologic formations including certain sandstones where the same approaches described below are applicable.

[0126] Described herein are two novel strategies for utilizing the chemical potential of Fe2+by use of controlled acidic environments to efficiently extract Fe2+, for use, for example, in the systems and methods described herein. Utilization may be performed in acidic or, in some cases, controlled alkaline media. The two strategies include in situ hydrogen generation, and ex situ conversion via leaching and transport to the surface. In situ hydrogen generation can facilitate subsurface reactions that generate hydrogen by leveraging the redox properties of Fe2+in iron-rich rocks. Ex situ conversion via leaching and transport to the surface can allow for extraction of Fe2+from iron-rich minerals through chemical leaching for subsequent applications in surface conversion systems.

[0127] Table 1 presents the reactions involved in both approaches, including associated voltages and comments on their applications:Table 1: Key Fe2+ Reactions in In Situ and Ex Situ MethodsMethod Rejctisn Cotataetits

[0128] Specific acids and chelating agents for Fe2+extraction and mobilization are described below. The extraction of Fe2+from iron-rich rocks can be facilitated by the use of acids andAtty. Docket No.: GE0001PCT_8022-00200 chelating agents that can mobilize and stabilize Fe2+into solution. Acids facilitate the dissolution of Fe2+from iron-rich minerals by protonating and breaking down the mineral structure. Certain acids can be used to acidify the extraction fluid including, but not limited to, 1) carbonic acid from dissolution of CO2 in water, 2) sulfuric acid (H2SO4), 3) hydrochloric acid (HC1), 4) nitric acid (HNO3), and 5) organic acids such as acetic acid (CH3COOH).

[0129] Chelating agents form stable complexes with Fe2+, preventing its precipitation and enhancing its solubility. These include, for example, 1) Ethylenediaminetetraacetic Acid (EDTA), 2) low cost, organic chelators derived from citric, oxalic acid, and / or aldonic acids, 3) phosphates, and / or 4) amino acids including histidine.

[0130] In situ methods can involve generating hydrogen directly within subsurface geological formations through natural or engineered chemical reactions. A primary process utilized is serpentinization, which alters iron-rich minerals to produce hydrogen gas. There are other similar processes in different rocks.Table 2: Serpentinization Reaction of Fe2+in Iron-rich MineralsMineral Serpentinization ReaetionOlivineGrunerite

[0131] In subsurface environments, maintaining high pressure ensures that water remains in the liquid phase even at elevated temperatures (e.g., 350 °C). This high-pressure condition significantly affects the activity of water («H2O) and hydrogen («H2) in the system. In high- pressure liquid water, the activity of water remains high, facilitating continuous hydrothermal reactions. In contrast, steam (gas phase) has lower water activity, which can limit reaction kinetics and mass transfer. Dissolved hy drogen (H2) in high-pressure liquid water exhibits different solubility and activity compared to evolved hydrogen gas. The solubility of H2 is low and the activity is lower than in the gas phase which shifts the equilibrium favorably.

[0132] To improve hydrogen production in situ under geothermal conditions, suitable fluid mixtures can be used to enhance reaction kinetics, stabilize reactive intermediates, and facilitate efficient mass transfer. In some aspects, the fluid mixtures can comprise supercritical water, an oxidizing agent, an ionic strength enhancer, and a chelating agent. The oxidizing agent can comprise any component or compound capable of oxidizing compounds under geothermal conditions. In some aspects, the oxidizing agent can comprise molecular oxygen, though other components such as hydrogen peroxide can also be used. The ionic strength enhancer can comprise any salts that are soluble under the geothermal conditions. TheAtty. Docket No.: GE0001PCT_8022-00200 chelating agents can comprise any of those disclosed herein.

[0133] The following are example fluid mixtures for in-situ extraction:

[0134] Mixture A: Citrate-Buffered Oxidizing Solution that can include: supercritical water at 350°C; 0.1 M Sodium citrate (NasCeHsO?) to chelate Fe2+; 0.05 M Oxygen (from air) as an oxidizing agent; and 1 M Sodium chloride (NaCl) to enhance ionic strength. In this mixture, the citrate stabilizes Fe2+, oxygen facilitates oxidation, and sodium chloride improves mass transfer, collectively improving hydrogen production.

[0135] Mixture B: Oxalate-Enriched Ionic Solution that include supercritical water at 350°C; 0.1 M Sodium oxalate (Na2C2O4) to chelate Fe2+; 0.05 M Sodium hypochlorite (NaOCl) as an oxidizing agent; 1 M Sodium chloride (NaCl) for ionic strength. In this mixture, oxalate effectively chelates Fe2 t. while sodium hypochlorite and sodium chloride contribute to reaction efficiency and hydrogen yield.

[0136] Mixture C: Citrate and Bicarbonate Combined Solution that includes supercritical water at 350°C; 0.05 M Sodium citrate (NasCeHsCh) for Fe2+stabilization; 0. 1 M Sodium bicarbonate (NaHCOs) as a pH buffer; 0.05 M Oxygen (from air) as an oxidizing agent; and 1 M Sodium chloride (NaCl) to enhance ionic strength. In this mixture, combining citrate with sodium bicarbonate ensures both Fe2+stabilization and pH buffering, while oxygen and sodium chloride optimize reaction conditions for maximum hydrogen production.

[0137] To improve hydrogen generation, the fluid mixtures can be injected into subsurface iron-rich rock formations under controlled geothermal conditions. In some embodiments, the process can comprise preparing the fluid mixture, injecting the fluid mixture into the subsurface formation, allowing the mixtures to react, and recovering the hydrogen produced.

[0138] The process can begin with the preparation of the fluid mixture. This step can comprise mixing the selected low-cost additives with water and dissolve CO2 to form carbonic acid or other acid selected. The concentrations of the other components including the chelating agents, oxidizing agents, and salts cam then be adjusted according to the chosen fluid mixture.

[0139] The mixture can then be injection into the subsurface formation. In this step, the prepared fluid mixtures can be injected into wells (e.g., geothermal wells, etc.) to reach iron- rich rock formations in conjunction with potential rock fracturing protocols. A sufficient volume of the mixture can be injected to provide a saturation of the rock matrix to maximize contact between the fluid and reactive minerals.

[0140] Once injected, the formation heat loss can be controlled and the injection temperature can be maintained around 300-400 °C. or about 350 °C and pressure within 10-20 bar to sustain supercritical water conditions. Continuous or pulsed injection methods can be used to improveAtty. Docket No.: GE0001PCT_8022-00200 mass transfer and reaction kinetics.

[0141] The hydrogen produced can be present as dissolved hydrogen and / or some amount of free hydrogen. The hydrogen can be captured in-situ and / or the fluid can be produced to the surface where the hydrogen can be liberated using a pressure reduction. A gas collection system can be used to capture the generated hydrogen gas.

[0142] Ex situ methods can also be used. Ex situ methods rely on mobilization of Fe2+from iron containing mineral, rock, soil, sandstones, and other geologic formations containing Fe2+, either at the surface or in the subsurface, stabilizing the ions, and transporting the Fe2+to the surface for exploiting the chemical potential at the surface.

[0143] Among the many possible uses of Fe2+at the surface are electrochemical processes to exploit the mobilized iron. In this embodiment, a variety of reactions can be used, including those listed in Table 3 below:

[0144] In all of these electrochemical processes the cell potential is positive indicating that the free energy change favors the production of the products including direct generation of electricity'. Depending on the site and availability of oxidants for Fe2+a specific process many be selected. There are also non-electrochemical processes that can make use of the Fe2+including the following listed in Table 4:Atty. Docket No.: GE0001PCT_8022-00200Table 4: Uses of Fe2+in non-electrochemical processes

[0145] These reactions oxidize the Fe2+without the need of an electrochemical cell to produce valuable chemicals including NEU and H2 as well as reducing pollutants sulfites and nitrates.

[0146] In this embodiment a focus is on acidic media used to mobilize Fe2+. Acid leaching is the most straightforward method for extracting Fe2+. It involves treating the ore with a strong acid to dissolve Fe2+ions into the solution. The source material may be crushed or fracked in situ to increase the surface area. The material is contacted with an acidic aqueous solution under controlled temperature and pressure conditions to leach the Fe2+. The ions are dissolved into the solution forming soluble complexes.

[0147] Redox leaching may also be used to leverage redox reactions to enhance the dissolution of Fe2+. For example, introducing oxidizing agents (e.g., hydrogen peroxide, oxygen) to facilitate the oxidation of Fe2+to Fe3+, increasing solubility. Leaching can also be carried out using redox components, which are similar to acid leaching but with the added redox component to improve extraction efficiency. Redox leaching also allows for the oxidized Fe species to be stabilized to prevent precipitation.

[0148] Electrochemical leaching uses electrical current to drive the dissolution of Fe2+. An anode and cathode is placed in contact with the ore slurry. A current to oxidize Fe2+is applied at the anode, enhancing its solubility. Fe2+is dissolved and can be collected at the cathode or maintained in solution.

[0149] Combining appropriate acids with chelating agents creates a suitable environment for efficient Fe2+extraction and stabilization. The following are exemplary fluid compositions.Atty. Docket No.: GE0001PCT_8022-00200

[0150] In a first example, the mixture can comprise sulfuric acid and citrate. In this embodiment, the mixture can comprise sulfuric acid (H2SO4) in a concentration between about 0.25 to 1 M, or about 0.5 M; sodium citrate (NasCeHsO?) in a concentration between about 0.01 to about 0.5 M, or about 0.1 M; and water (H2O) as the balance of the mixture. This mixture has the advantage of being cost-effective and efficient for Fe2+extraction. The citrate stabilization prevents Fe2+precipitation, and the mixture is suitable for large-scale operations due to low reagent costs. Within this mixture and its use. the pH can be maintained around 2- 3 to allow for Fe2+solubility and citrate chelation. The mixture should also be used with corrosion-resistant materials to handle sulfuric acid.

[0151] In a second example, the mixture can comprise hydrochloric acid and oxalate. In this embodiment, the mixture can comprise hydrochloric acid (HC1) in a concentration of between about 0.1 to about 0.5 M, or about 0.3 M; sodium oxalate (Na2C2O4) in a concentration from about 0.01 to about 0.2 M, or about 0.05 M; and water (H2O) as the balance of the mixture. This mixture has the advantage of providing enhanced solubility of Fe2+through oxalate complexation, where the oxalate serves dual functions as a chelating and reducing agent. Within this mixture and its use, the pH can be controlled to around 1.5-2.5 to prevent the formation of insoluble iron oxalates. Monitoring can be used to address potential chloride ion pollution in effluents.

[0152] In a third example, the mixture can comprise nitric acid and citrate. This mixture can comprise nitric acid (HNO3) in a concentration of between about 0. 1 to about 0.5 M, or about 0.2 M; sodium citrate (NasCeHsO?) in a concentration of between about 0.5 M to about 0.25 M, or about 0. 15 M, and water being the balance.

[0153] Elevated temperatures can enhance reaction kinetics, increasing Fe2+extraction rates. In some aspects, temperature ranges from 50 - 350 °C can be utilized. Implementation of heat exchangers to recover and reuse thermal energy within the process can be deployed for energy efficiency. High-pressure conditions can improve mass transfer rates, facilitating the dissolution of Fe2+. The transport liquid containing chelate and acid can be recycled for greater process efficiency.

[0154] In some embodiments, the present disclosure relates to methods and systems for identifying minerals, rock formations, and / or chemistries for producing economic value. This can include, in some aspects, Al driven models to identify thermodynamic conditions to leverage multiple resource extraction processes specifically for hydrogen and geothermal processes.

[0155] A large part of the economics of geological extraction processes depends on the earlyAtty. Docket No.: GE0001PCT_8022-00200 recognition of where exactly a given subsurface environment is located in the in-situ geochemical environment. For hydrocarbon production, this is less important as most oil / gas fluids above a certain American Petroleum Institute (API) gravity are generally very valuable. This is much more varied for example for geothermal heat extraction, hydrogen extraction and amorphous silica extraction, and rare earth extraction processes. These extractions are currently considered in isolation, and engineering solutions focus on one resource extraction process discarding others - as optimization of a more integrated engineering process is almost impossible to make. This is largely the result of insufficient knowledge of the in-situ geochemical environment from which these resources are to be extracted. However, both engineering and computational (Al driven) data analysis can make this possible.

[0156] Synergies exist between hydrogen extraction via serpentinization and specific forms of geothermal heat extraction leading to an engineering extraction process that leverages both. To do this systematically requires an understanding of the thermodynamics of the in-situ geochemical environment. This insight is new and so far unexplored. Presented herein, in a certain embodiment, is an AI / ML method to specifically allow improvement and / or optimization among several engineering solutions for various extraction processes - starting, for example, with geothermal and hydrogen extraction processes.

[0157] In some instances, the geochemical environments that are considered are strongly reducing and usually in low-activity silica environments (and usually, as well, in low-sulphur and oxygen environments). Furthermore, in certain of the engineering extraction processes described herein, like the geothermal, hydrogen extraction, amorphous silica extraction, rare earth mineral extraction, and / or other resource extraction, that can be economically improved or optimized, are dependent on interfacial processes of water (brine) in contact with iron containing rocks (minerals) - adjacent to silica / quartz containing rock layers - that have a high Fe(2+) content that may get transformed into Fe(3+), which in a strongly reducing environment allows reduction of water to hydrogen. In many cases, the hydrogen generation processes are exothermic and sometimes (as is the case for olivine, extremely exothermic) leads to significant increases of temperature, mechanically swelling and altering the host rock with significant fracturing. Furthermore, by natural processes induced by other components like pyroxenes in the host rock, the alkalinity of the brine initially at lower pH can increase up to pH > 10, thereby suppressing the hydrogen generation process. In general, the chemical processes described herein are far from equilibrium. Thus, the geochemical environment is quite complex, and it is difficult to simulate the richness of this environment and hence the many shifts in reaction equilibria which determine how extraction processes may be optimized. For example, thereAtty. Docket No.: GE0001PCT_8022-00200 are several “chemical swings’" possible-controlled by temperature, pressure, enthalpy, pH and operating in mechanically changing rock conditions (with thermal and reaction-induced stresses and fracturing processes, that may control the selectivity and reaction rates).

[0158] In certain embodiments, the thermodynamics of such complex systems can be explored to decide what among the many opportunities of economically viable extraction, optimization of some of these would look like. This understanding does not yet exist. The thermodynamics for hydrogen production only exists in earnest for deep sea vent systems occurnng in mid ocean ridge environments which is indeed simpler but more importantly also in different water / rock ratios (w / r > 0.2) and hence does not apply to much tighter deeper rock formations. Furthermore, such understanding is not coupled to geomechanical parameters such as fracture growth, and fluid flow in stressed rock strata, which impacts the thermodynamics.

[0159] Such systems cannot be reliably simulated in lab environments which may therefore give misleading insight of what actually happens in the subsurface. Hence, the systems and methods described herein access the extant data in well and mining databases of up to now different unrelated businesses such as oil and gas, geothermal energy’, surface and subsurface mining, nuclear waste disposal, and brine extraction.

[0160] In certain embodiments, the systems analyze the thermodynamics of in-situ conditions via a novel data driven Al method specifically designed for analysis of well data fluid samples, rock formation sampling, as well as flow, temperature, and pressure measurements. In certain embodiments, a language model is implemented, for example, a combination of Adversarial Generative Networks, Variational Autoencoders, and Transformer-based Models applied to the many geothermal well data bases. These databases exist in the private and public domain and have been built up over many decades across the globe, for example in the US, Australia, East Africa, and India, for geological settings where the geochemistry described above is known to exist.

[0161] Some preliminary attempts to apply Al data driven approaches to understand the thermodynamics in specific offshore environments have started to emerge - here, in certain embodiments, this is applied to onshore geological settings, e.g., Cratonic and Orogenic (Mobile) Belt environments in which hard rock heat extraction, serpentinization environments at depths of between 1 - 7 km depth and banded iron formations w here perhaps iron ore mining occurs at outcrops can have overlapping geochemical settings. Focusing on geothermal and mining environments to acquire engineering parameters may provide substantial insights in the complex controlling systems as these environments may for example also show some hydrogen production via serpentinization.Atty. Docket No.: GE0001PCT_8022-00200

[0162] To derive thermodynamic properties using a language model of chemical reactions based on data from geothermal wells, a structured approach can be followed that integrates machine learning with principles from thermodynamics, chemistry, and geothermal energy systems. In certain embodiments, this is done by understanding the data from geothermal wells, creating a language model for chemical reactions, extracting thermodynamic data, and applying machine learning and models to improve or optimize the system(s).

[0163] To start, geothermal wells provide a wealth of data, such as temperature and pressure profiles at various depths, concentration of chemicals (e g., Na+, Ch, SiCL) in the geothermal fluid, pH levels and oxidation states, gas composition (e.g., CO2, CH4, H2S), flow rates and enthalpy data, and / or fracking conditions (penetration, surface area estimates, fluid flow and stress state). These parameters influence the chemical reactions and thermodynamic properties of the system, so the data needs to be pre-processed to derive meaningful chemical and thermodynamic relationships.

[0164] Next a language model for chemical reactions can be created. A language model for chemical reactions leams how reactants, products, and conditions (temperature, pressure) evolve. This can be structed using input data, tokenization. and sequence learning.

[0165] The input data can be used to create sequences of reactions and conditions that represent changes in the system based on well data. For example, geothermal reactions at different depths might be represented by reactions between minerals and water under varying temperatures and pressures. Tokenization can be used to break chemical reactions into individual components (reactants, products, conditions) that can be understood by the language model. Sequence learning can be used to train the model to predict outcomes of reactions (products, Gibbs free energy changes, enthalpy, etc.) based on inputs.

[0166] Thermodynamic data can then be extracted and used with the system. Thermodynamic data can include thermodynamic quantities, and the language model can be trained to output key thermodynamic properties, such as Gibbs free energy (AG) for chemical reactions, enthalpy (AH), entropy (AS), equilibrium constants (K) under vary ing conditions, heat capacity (Cp) at different stages of reactions, and / or coupling of these parameters as a function of the fracture system. Using historical geothermal well data as training, the language model can learn to associate particular geothermal conditions (temperature, pressure, chemical composition) with these thermodynamic quantities.

[0167] Machine Learning can then be used to improve or optimize the system. A machine learning framework can be applied to improve or optimize the chemical reactions and match observed geothermal well data to theoretical thermodynamic values. These focus on specificAtty. Docket No.: GE0001PCT_8022-00200 the effects of fracturing on reactive transport of fluids. For example, when applied to exothermic serpentinization environments, this may lead to an understanding how best to frack and create larger surface area to enhance accessibil i ty of water exposed to the rock as well as achieving and controlling a self-sustaining serpentinization, e.g., avoiding clogging, or changes in the chemistry that would arrest hydrogen generation.

[0168] In FIG. 1, an illustrative frack-based stimulation is shown. Near the tip, the olivine starts to swell accompanying conversion into serpentinite. The injected brine is drawn to the fracture tip. The tensile stress is highest at the tip, and the pressure in the fracture may be (very ) high. As this process is exothermic, it may be self-sustaining, provided that the pH and temperature are controlled.

[0169] This model of reactive flow in a small fluid filled crack is in some ways analogous to shale gas production through fracturing shale layers where large open fractures are created to enhance surface area. Techniques in operation in hard-rock geothermal settings borrowing from shale gas fracking may be combined to optimize pressure control in the fracks, further increasing the complexity and surface area of fracture systems (e.g.. in a Huff and Puff dual production / injection system as disclosed herein). Controlling fracture engineering with chemical / physical parameters learned from wells is known to effectively improve production enabling conditions. In some aspects the application of the methods described above to increase the rate of production by increasing the area of contact between the brine and rock would be expected to lead to rates of production of between 0. 1 kT / year per well and 10 kT / year per well.

[0170] Using data from different geothermal w ells, the model can be trained to predict changes in thermodynamic properties as a function of depth, temperature, pressure, and chemical composition.

[0171] The model can then be validated and tested using real-world measurements from different geothermal systems to validate the model's predictions. The model can be used for various analysis. In some aspects, the model can be used to address inverse problems where the model is used to deduce the conditions (e.g., temperature, pressure) from observed chemical equilibria.

[0172] Once the language model is trained, it can be used to: predict the thermodynamic behavior of geothermal systems in particular aspects of reactive transport under various conditions, which is essential for energy extraction and geothermal reservoir management. This may then suggest specific laboratory experiments to calibrate and test optimization. The model can also be used to model chemical scaling and precipitation (e.g., silica or carbonateAtty. Docket No.: GE0001PCT_8022-00200 deposition) which is a major issue in geothermal systems, optimize geothermal energy extraction by predicting how changes in fluid chemistry or temperature will affect the efficiency of heat extraction, and / or improve or optimize the fracturing and fluid circulation process.

[0173] In certain embodiments, the machine learning modules described herein comprise one or more Kolmogorov-Arnold Networks (KANs). For example, presented herein are methods and systems for the use of a KAN model to simulate the complex thermodynamic and geochemical environments of in-situ rock formations to locate sites for, and / or design / optimize / control processes for, in-situ, integrated generation of heat and hydrogen from Fe(2+)-rich subsurface geologies. In particular, the use of a KAN architecture provides synergistic benefits in learning thermodynamics from specific well data.

[0174] In particular, there are recent new insights into the uses of KANs which are based on a deep mathematical theorem that has led to the insights that activation functions and weights in conventional multilayer (> 3 layers) networks can actually be replaced by linear expansions of univariate functions usually b-splines. These are of particular relevance as they are better suited to describe physical processes up to now described by partial differential equations (PDEs). Providing multi-layer KANs with data of which the underlying chemistry / physics is believed to be governed by systems of PDEs may therefore be a more practical way to leam what such relations are than conventional neural networks (NNs). KANs leam more transparently and also lead to much more compact NNs that are more insightful in what the underlying physics / chemistiy actually is described by in terms of NNs. Thus, KANs are particularly advantageous to leam thermodynamics from data - in particular, when the thermodynamics describe a non-equilibrium state, as in subsurface geologies relevant to the in situ hydrogen and heat extraction processes described herein.

[0175] Architecturally, KANs, based on the Kolmogorov-Arnold representation theorem, are designed to represent any continuous function by decomposing multivariable functions into sums and compositions of univariate functions. Instead of learning the complex multivariate interactions directly as in conventional networks. KANs leam transformations on individual variables before recombining them.

[0176] The decision boundaries in KANs tend to follow the structure of the decomposition of multivariate functions into univariate components. Because of this, KANs may have simpler, more interpretable decision surfaces, especially in tasks where the underlying function can be effectively represented as a sum or composition of univariate functions. This structure might not lead to as flexible or intricate boundaries as those formed by conventional networks in veryAtty. Docket No.: GE0001PCT_8022-00200 complex datasets, but it provides more structured and interpretable decisions. For example, these decision graphs tend to be of lower dimension and with fewer but deeper minima.

[0177] Key differences between KANs and conventional NNs in decision graphs have to do with their flexibility, interpretability, complexity, and computational efficiency. With respect to flexibility, conventional neural networks may be more flexible due to the complex interaction between multiple variables across different layers. That is, decision boundaries can adapt to highly intricate and nonlinear datasets. However, while KANs are universal approximators, their decomposition into simpler, univariate transformations may lead to decision boundaries that reflect the simpler, structured nature of these transformations. This can be beneficial for interpretability without the extreme flexibility seen in deep conventional networks. With respect to interpretability, conventional NNs have decision boundaries that are harder to interpret because of the “black box” nature of their many-layered networks. Complex layers and weights create decision boundaries that might not correspond to clear, understandable patterns. By contrast, because KANs decompose the decision-making process into simpler parts (e.g., univariate functions), their decision boundaries may be more interpretable and understandable, especially for tasks where such decomposition naturally reflects the underlying structure of the problem. With respect to complexity and computational efficiency, conventional neural networks have decision boundaries that can be highly complex, but this comes at the cost of increased computational resources and risk of overfitting. By contrast, KANs are often more computationally efficient due to their structured, simpler transformations, which can result in simpler decision graphs while still maintaining strong approximative power for many tasks.

[0178] The following describes application of MLs (e.g., KANs, etc.) to geothermal environments (e.g., subsurface geological formations) using geothermal well data, according to various embodiments. KANs can be applied to leam / recover the thermodynamics from well data in geothermal environments, after which the KANs may be used in models of the thermodynamics in subsurface formations to locate sites for, and / or design / optimize / control processes for, in-situ, integrated generation of heat and hydrogen from Fe(2+)-rich subsurface geologies. For example, one embodiment focuses on the Gibbs free energy. This provides a hook into synergies with geothermal heat extraction and optimizes the production by optimizing a Huff and Puff system.

[0179] For example, the following well data parameters can be useful for building a model that can be used to locate sites for and design / control processes for in situ hydrogen production (e.g., for serpentinization and hydrogen production) and / or heat production (and / or otherAtty. Docket No.: GE0001PCT_8022-00200 resource extraction) from subsurface geologies.

[0180] Mineral composition (rock type) including any specific compositions. Peridotite composition (rich in olivine and pyroxene) can be important for serpentinization. The concentration of olivine ((Mg,Fe)2SiO4) and pyroxene in the rock formation can be identified. The more olivine, the more potential for serpentinization. The mineral composition (e.g., concentration of olivine) can be derived from X-ray diffraction (XRD) or gamma-ray logs and mineralogical studies.

[0181] Porosity, permeability, and / or resistivity of the formation can be used. High porosity enables water to permeate the rock and drive serpentinization. Serpentinization leads to a decrease in porosity as the reaction progresses and new minerals (e.g., serpentine, magnetite) form. A key aspect of this disclosure is the use of brine pressure to keep the fracture network open, thus controlling the porosity and permeability via pressure within a desirable range for hydrogen production within a reacting rock volume. It is therefore advantageous to be able measure porosity and permeability both before and during our process to establish and maintain high rates of production. Porosity may be measured using density logs, sonic logs, or neutron porosity logs, for example. Similarly, permeability controls the ability of fluids (e.g., water, hydrogen) to flow through the rock. Lower permeability may indicate that serpentinization has progressed, sealing fractions and reducing fluid flow. Permeability may be measured from core samples, down-hole pressure tests, or inferred from well log data. Resistivity indicates fluid content and type in the pore spaces. Serpentinized rock generally has different resistivity than unsaturated rock, and resistivity changes can indicate the presence of conductive fluids (like hydrogen). Resistivity may be measured using resistivity logs.

[0182] Fluid chemistry and / or fluid saturation can also be used. Fluid chemistry parameters include pH (potential of hydrogen), oxidation-reduction potential (ORP), and major ion concentrations (e.g., Mg2+, Fe2+, H+, H2, CO2). Especially important is the concentration of Fe2+in the fluid, as its oxidation to Fe3+during serpentinization produces hydrogen. This data can be collected through fluid sampling or inferred from chemical sensors and geochemical modeling. Fluid saturation is the fraction of pore space fdled with water and possibly hydrogen gas. This may be important for understanding how much fluid is available for the serpentinization process. Fluid saturation may be derived from resistivity' or nuclear magnetic resonance (NMR) logs.

[0183] Formation conditions such as temperature, volume, and / or pressure can also be used. Serpentinization is temperature-dependent, with higher temperatures (e.g., 200-350°C) favoring more rapid reactions. Tracking the thermal gradient is crucial for understanding theAtty. Docket No.: GE0001PCT_8022-00200 serpentinization rate. Temperature may be measured using temperature logs. Volume changes may be measured using borehole strain meters or other techniques. Subsurface pressure affects the rate of serpentinization and hydrogen solubility. Higher pressures at depth can increase the likelihood and rate of serpentinization reactions. Pressure data may be collected via pressure sensors and / or inferred from well depth and fluid density7.

[0184] Various components concentrations can also be used. For example, hydrogen concentration and / or CO2 concentration can be used in the models. Direct measures of dissolved or free hydrogen gas in the fluid can be obtained. This is an important parameter to determine, as concentration of hydrogen is a key indicator of ongoing serpentinization. Hydrogen concentration may be measured through downhole fluid sampling and gas chromatography. Carbon dioxide (CO2) competes with serpentinization processes by reacting with olivine to form carbonate minerals, which can influence hydrogen generation. CO2 concentration can be measured through fluid sampling or inferred from CO2 sensors.

[0185] The composition and formation of reaction products and minerals can also be used. Magnetite forms as a byproduct of serpentinization, and its presence indicates the extent of the reaction. Magnetite can also serve as a proxy for estimating hydrogen generation. Magnetite content can be inferred from magnetic susceptibility logs or mineralogical analyses. The salinity7of the circulating fluids can affect the reaction kinetics of serpentinization, as saltwater has different chemical properties than freshwater. Salinity can be measured using fluid sampling or inferred from resistivity logs.

[0186] The physical properties of the formation can also be used. Serpentinization often occurs along fractures in the rock, which allow water to penetrate. The volume changes accompanying serpentinization can create additional fracturing, as well as decreasing the seismic velocities. Tracking the density and orientation of fractures can provide insights into the pathways for fluid flow and reaction zones. Fracture density and extent of serpentinization can be inferred from borehole imaging logs, core analysis, travel time tomography and passive seismic surveys.

[0187] The Oxidation-Reduction Potential (ORP) can also be used. The redox state of the fluid directly influences hydrogen production. More reducing conditions (lower ORP) favor the formation of hydrogen. The ORP can be measured with electrochemical sensors in the well.

[0188] To determine the Gibbs free energy there can be an assessment of the composition of mineral that would be driving most of the serpentinization (e.g., olivine composition, as well as the amount of pyroxenes (e.g., more or less than 20% or other similar decision point)). Moreover, the temperature (T), Pressure (P), Fluid composition, concentration of certainAtty. Docket No.: GE0001PCT_8022-00200 components, the mineralogy, and / or the hydrogen concentration can be important to the determination of Gibbs free energy. Higher temperatures can lower the Gibbs free energy, making the reaction more favorable. Temperature logs provide direct input for this variable. Subsurface pressure influences the solubility of gases like hydrogen and the overall reaction energetics. Well pressure measurements provide data on the pressure measurements. The concentration of H2O, CO2, and Fe2 / Fe3in the fluid affects the Gibbs free energy. Fluid chemistry data, especially pH. redox conditions (ORP). and ion concentrations, can be useful. The presence of minerals like olivine and pyroxene, which may drive the reaction, influences the energetics. Gibbs free energy changes as the concentration of hydrogen increases during the reaction. Well data that captures hydrogen content helps track the progression of the reaction.

[0189] Any suitable source of data can be used to obtain data to train the models. For example, the following databases can also be used to train a KAN model. Thermodynamic data and models: Thermodynamic databases such as SUPCRT92 (e g., as described in Johnson et al., SUPCRT92: A software package for calculating the standard molal thermodynamic properties of minerals, gases, aqueous species, and reactions from 1 to 5000 bar and 0 to 1000°C”, Computers & Geosciences, Vol. 18, Issue 7, Aug. 1992, pp. 899-947) and PHREEQC (e.g., as described by the United States Geological Survey (USGS), https: / / www.usgs.gov / software / phreeqc-version-3), contain thermodynamic properties (including Gibbs free energy) for the minerals and fluids involved in serpentinization. These can be integrated into the model. A KAN can model the complex relationship between the well data parameters (e.g., temperature, pressure, fluid chemi sin ) and Gibbs free energy changes, learning from historical data and / or simulations. The KAN may be trained to predict Gibbs free energy from these variables, acting as an efficient function approximator.

[0190] The following are inputs that can be used, in an illustrative embodiment, for modeling Gibbs free energy. For example, well data can be compiled into the following to model Gibbs free energy changes, and to learn from the databases mentioned above.Table 5: Inputs that may be used for modeling Gibbs free energyAtty. Docket No.: GE0001PCT_8022-00200

[0191] Reaction rates can be estimated using a KAN. The illustrative embodiment proceeds to use a KAN to estimate reaction rates, for example, initially using a simple Arrhenius equation or other mathematical expression. The degree to which the model is trained, for example, using some of the databases mentioned above can be important.

[0192] There are various advantages of using KAN for reaction rate prediction. Reaction rates often depend on nonlinear combinations of variables (e g., temperature, pressure, pH, and fluid chemistry). KANs are well-suited for modeling these nonlinear dependencies, as they decompose complex multivariable functions into simpler univariate transformations. KANs can generalize easier (or at least are more transparent to extrapolation) to different environments and geological conditions, allowing them to predict reaction rates for new, unseen well data. Once trained, KANs can predict reaction rates quickly, making them suitable for real-time monitoring or prediction in active wells.

[0193] The methods and systems disclosed herein can be used for simulation and recovery’ of various compositions from subsurface formations. This can include tuning geochemical reactions at the interface of iron-rich sedimentary rocks, including sandstones and BIFs, mafic rocks such as troctolites or mafic rocks such as peridotite.

[0194] The processes an include the oxidation of iron (e.g., oxidation of Fe2+ to Fe3+) and hydrogen generation. In certain embodiments, water (e.g., brine) is injected into an iron-rich layer (e.g., olivine), and hydrogen is produced (e g., by conversion of olivine to serpentine + magnetite + hydrogen).

[0195] The dissolution of iron (Fe2+) can also occur with hydrogen generation. When brine is injected into the iron-rich layer (e.g.. minnesotaite, hematite, and / or magnetite), the interaction of water with iron minerals could lead to the formation of Fe3+(ferric iron, e.g., in magnetite)Atty. Docket No.: GE0001PCT_8022-00200 and the generation of hydrogen gas (H2) through reactions such as the following:9Mg2SiO4 + 3Fe2SiO4+ 14H2O 6Mg?Si2O5(OH)4+ 2FesO4 + 2H2

[0196] The generation of hydrogen gas creates a reducing environment, which can alter the chemistry of the brine and impact the dissolution of silica. In the presence of reducing conditions and Fe2+, the silica (S1O2) in the adjacent silica-rich layers might become more soluble, especially if the brine has a slightly elevated pH due to the presence of dissolved Fe2+and other 10ns. The oxidation of iron and the hydrogen produced could influence the local pH and create conditions conducive to silica dissolution.SiO2(silica)+H2O+Fe2+^ H4SiO4(soluble silica species )+SiO2(silica)+H2O+Fe2— THSiCH (soluble silica species)

[0197] As the brine becomes saturated with dissolved silica (H4SiO4 or Si(OH)4), any subsequent changes in temperature, pH, or pressure as the fluid moves away from the reaction zone or is brought to the surface could lead to the precipitation of amorphous silica rather than its re-crystallization as chert.

[0198] Certain conditions can favor the formation of amorphous silica. For example, the pH and redox conditions can affect the formation of amorphous silica. For effective silica dissolution, the pH of the brine can be around pH 9-11. The interaction with Fe2+could help maintain or slightly elevate the pH, promoting silica dissolution. A reducing environment (low oxygen levels, presence ofH2) could prevent the re-oxidation of iron, allowing Fe2+to continue reacting and possibly facilitating the dissolution of more silica. The injection and reaction processes could create pressure and temperature conditions that enhance the dissolution of silica. As the brine cools or is depressurized, amorphous silica may precipitate out of solution. The natural geothermal gradient could provide the heat to keep the silica in solution while it is being transported through the fractures.

[0199] The efficiency of the silica reaction process depends on the reaction kinetics between the brine, iron minerals, and silica. The reaction might require sufficient contact time within the fractures for the reactions to proceed to the point where significant silica dissolution occurs. Achieving conditions that favor the precipitation of amorphous silica rather than crystalline silica can rely on control of the cooling and pH adjustment process as the brine is extracted. The success of this approach depends on creating an effective fracture network that maximizes the interface between the iron-rich and silica-rich layers. As noted above, fracturing operations and pressure modulation can be designed to ensure that the brine can circulate effectively through these layers.

[0200] This process has a number of advantages including in-situ species generation. TheAtty. Docket No.: GE0001PCT_8022-00200 process leverages the in-situ generation of hydrogen and Fe2+, which can enhance silica dissolution without the need for additional chemical additives. If the conditions are controlled, this process can provide a novel method for producing amorphous silica in situ, potentially at lower temperatures and with fewer chemical inputs than traditional methods.

[0201] In some aspects, the application of pressure and / or temperature modulated hydraulics and geochemical control can result in enhanced chemical and heat recovery’ by facilitating the dissolution of Fe(2+) from the rock formation. In certain embodiments, the utilization of heat and Fe(2+) from subsurface formations for chemical production including hydrogen can include, i) accessing the Fe(2+), ii) creating conditions that facilitate oxidation of the Fe(2+) to Fe(3+) and the use of the electron for the generation of chemical products including H2, and iii) the recovery of the produced hydrogen or other chemical products. The parameters that can be selected / controlled include temperature, pressure, pH, redox conditions, and brine composition. Two methods for exploiting Fe(2+) from subsurface formations for hydrogen production can be used include, 1) the extraction of Fe(2+) from the host rock and oxidation to Fe(3+) in the subsurface for the production of hydrogen or other chemical products in the subsurface, and 2) the extraction of Fe(2+) from the host rock and the facilitation of transport of the Fe(2+) to the surface for use in producing chemical products including hydrogen.

[0202] A formation rich in Fe(2+) can be identified using methods disclosed herein and in a formation with a temperature of between 100 °C and 400 °C. The formation can be accessed by way of vertical and / or horizontal drilling such that access by a fluid stream is possible. The fluid stream can contain primarily water and, perhaps, salts.

[0203] The pressure can be maintained such that the water remains a liquid within the formation and the conditions are controlled to increase the dissolution rate of the Fe(2+) into solution. The solubility can depend on the temperature and ionic composition, but can be approximately 200-300 mg / liter at 250 °C. The conditions that can be controlled are primarily pH, which can be maintained at approximately’ 4-6 by dissolution of CO2 to form carbonic acid. The pH can be maintained as being acidic to prevent the precipitation of siderite (FeCCh). The CO2 may be dissolved into the liquid at the surface or injected with the liquid. Several ions can be used to stabilize the Fe(2+) in solution including C1-, SCfi2-and low concentrations of CO32-. Alternatively, if the extraction solution is allowed to become basic, Fe(2) can be stabilized and likely precipitates as Fe(OH)2 which is minimally soluble in basic conditions.

[0204] In some aspects, the delivery , control, and monitoring of the hydraulic pressure to the formation can be useful. Pumping systems familiar to those in the field can be used to deliver fluid and generate sufficiently high pressures to fracture the rock, either rapidly or slowly. InAtty. Docket No.: GE0001PCT_8022-00200 some embodiments, a time varying pressure and / or temperature can be deployed to the formation with several elements to the temporal sequence including: a fracturing period (rapid or slow / controlled) and an infusion / effusion period. In some cases, a low-pressure period is introduced whereby nucleation of hydrogen gas bubbles can occur. Further, in certain embodiments, modulation of the pressure, P(t), pH(t), water / rock ratio (WRR(t)) to improve or optimize access (fracturing) dissolution / precipitation, nucleation of gas bubbles can be used.

[0205] Generation of H2 in the subsurface the environment in and around dissolved Fe(2+) may present oxidizing conditions facilitating hydrogen generation. In formations where it is expected that both Fe(2+) and Fe(3+) will dissolve, the reaction, Fe2++ Fe3++ H2O Fe(OH)3 + H2, will produce hydrogen. Where nitrates are available, the reaction, Fe2++ NOi Fe3++ N2 + H2. will produce hydrogen. In manganese rich formations the reaction. 2Fe2++ MnO2+ 2H2O —> 2Fe3++ Mn2++ H2. will produce hydrogen. Oxygen can minimized or be introduced at several points in the extraction to facilitate the key reaction, 4Fe(2+) +4H2O+O2^4Fe(?+)+2H2+4OH .

[0206] In another embodiment as shown in FIG. 9, dissolved Fe(2+), can be recovered from the formation and returned to the surface in the hydrothermal liquid column. At the surface, conditions can be controlled to favor one or more hydrogen generating reactions including:3Fe(OH)2+ H2O -> Fe3O4+ 4H24Fe(2+) +4H2O+O2^4Fe(3+)+2H2+4OHThis produces both hydrogen and iron(3+) or other mineral hydroxides as commercial products.

[0207] Also disclosed herein are systems and methods for stimulation and recovery from mineral collections at or near the surface. For example, hydrogen can be produced from mines such as diamond mines. This process is shown in FIGS. 10A-10C. Most diamond mines are in kimberlite or lamproite dykes or pipes, deep carrot like structures that may extend tens of km into the subsurface. Of these, kimberlite pipes or dykes are most common. Kimberlite pipes are volcanic formations that are the primary' source of diamonds. They originate from deep within the Earth's mantle and are brought to the surface through explosive volcanic activity. The chemical composition of kimberlite is highly variable but typically consists of a mix of silicate minerals, oxides, and other components. The minerals can include, but are not limited to olivine, phlogopite, clinopyroxene, serpentine, garnet spinels, ilmenite, carbonates, or any combination thereof.

[0208] Olivine includes one of the most abundant minerals in kimberlite, and is a compound having (Mg, Fe)2SiO4. It is usually rich in magnesium, with some iron. The iron contentAtty. Docket No.: GE0001PCT_8022-00200 decreases as the diamond content increases, making diamond productivity a potentially important screening tool. Phlogopite is a type of mica ( Mg3(AlSi3Oio)(OH)2), and is often present in smaller quantities. Clinopyroxene (Diopside) is common in kimberlites, and clinopyroxenes like CaMg(Si2Oe) are silicate minerals rich in calcium and magnesium. Serpentine is a mineral formed by the alteration of olivine during weathering and hydration. Garnet (Pyrope) is rich in magnesium and iron, and has a formula of (Mg.FejsAL SiO^. Garnets are often found as xenocrysts in kimberlite pipes, especially the variety known as pyrope.

[0209] Various oxides can also be present. Spinel groups can include minerals like chromite and magnetite. Chromite has the formula FeC^Ch, and magnetite is FesC . Ilmenite, FeTiOs. an iron-titanium oxide, is another common oxide found in kimberlite pipes. Carbonates such as kimberlite often contain carbonate minerals like calcite (CaCCh) or dolomite (CaMg(CC>3)2), especially in altered and weathered sections of the pipe. The major elements in kimberlite rocks ty pically include: SiCh (Silica): Ranges from 25% to 35%, MgO (Magnesium Oxide): Often as high as 20% to 40%, CaO (Calcium Oxide): Around 10%. FeO (Iron Oxide): Typically around 5% to 13%. AI2O3 (Aluminum Oxide): Low. around 2% to 4%, T1O2 (Titanium Oxide): Usually 1% to 3%, and Na?© and IGO (Sodium and Potassium Oxides): Small amounts, around l% to 2%.

[0210] Kimberlite diamond mines are relevant for hydrogen engineering. First, it is the composition of olivine, a magnesium-iron silicate, that is often found in kimberlite pipes and ultramafic rocks, which are associated with diamond-bearing formations. Hence pumping in water possibly with a carbon mineral as a source for CO2 may trigger efficient serpentinization to produce hydrogen and which may be scalable in relatively simple ways.

[0211] Using an existing diamond mine to stimulate hydrogen generation could offer easier experimental engineering advantages, especially if the mine contains the right geological conditions and infrastructure. Existing mines have existing underground infrastructure. Diamond mines, especially those in kimberlite and lamproite pipes, are ty pically very7deep, providing direct access to the Earth’s mantle-derived rocks. This is beneficial because it avoids the need for expensive new drilling operations, which are required in other projects for subsurface access. In addition, many existing mines already have ventilation and gas monitoring systems in place, which could be repurposed for handling the extraction of hydrogen and ensuring safe conditions for the generation process.

[0212] The use of existing mines also allows for access to iron-rich minerals and control of the chemistry. Some diamond-bearing rocks, especially kimberlite, contain olivine and other iron-Atty. Docket No.: GE0001PCT_8022-00200 rich minerals (e.g., spinel), which can participate in water-rock reactions like serpentinization. When water interacts with iron-rich minerals, hydrogen gas can be produced. This process could be stimulated in an old diamond mine, taking advantage of the rock types present. While kimberlite isn't as olivine-rich as typical ultramafic rocks used for serpentinization, it can still contain enough Fe2+-bearing minerals to potentially contribute to hydrogen generation, particularly if enhanced with the right techniques or catalysts which may be easier and better controllable injected. For example, injection of CO2 may accelerate serpentinization but equally may allow for control of the pH of the brine. This may be easier in an old mine than by drilling wells. Kimberlites also contain clay minerals which are ductile, potentially allowing deformation without inducing seismic events. Further, a significant fraction of diamond mines is in areas with an increased (e.g., > 30 deg / km) thermal gradient. This opens up possible synergies with geothermal energy recovery which would have several advantages. It could be used in tandem with hydrogen production technologies, providing a dual energy source from a single site. The geothermal heat could enhance chemical reactions that produce hydrogen, improving the overall efficiency of the process.

[0213] Known diamond mines are located in Africa including Botswana (Jwaneng), South Africa (Cullinan, Venetia), Namibia (offshore mining), Angola; Russia including the Mirny and Udachny mines in the Sakha Republic, Canada including the Diavik and Ekati mines in the Northwest Territories, Australia including the Argyle mine in Western Australia; Brazil including the Minas Gerais region, and India including the Parma region.

[0214] The ones that have an increased geothermal potential include those in East Africa where both geothermal resources (in the Great Rift Valley) and diamond mining activities (e.g., Tanzania) are found; Western Australia, which has geothermal potential (Argyle mine), and Canada where there is some geothermal potential in British Columbia, though the diamond mines are further north.

[0215] In India there are several diamond mines but none are in geothermal active areas. These include Panna, Madhya Pradesh, which is the most active diamond mining region in India today, with reserves found along the Vindhy a Range. Panna is operated by the National Mineral Development Corporation (NMDC). India also includes Golconda, Andhra Pradesh / Telangana (Deccan Plateau). Historically, this region produced some of the world’s most famous diamonds, but active mining in Golconda has long ceased.

[0216] In addition to diamond mines, hydrogen can be produced from near surface iron(2+) enriched rock. In near surface formations or mined collections of banded iron, grunerite, ferrosilite, fayalite the Fe(2+) content can be as high as 50% by mass. This can include mineAtty. Docket No.: GE0001PCT_8022-00200 tailings. A two step process can be used including first extracting the Fe(2+) efficiently from selected host rocks with high Fe(2+) concentrations by first acid leaching in an anoxic environment, and then increasing the pH to precipitate Fe(OH)2. A number of common and low-cost recoverable acids may be used including oxalic, sulfuric, nitric, and hydrochloric acids.

[0217] For example, with Grunerite Fe7SisO22(OH)2 HC1 acid leaching results in liberation of Fe(2+).Fe7Si8O22(OH)2+ 14 HC1 -> 7 Fe(2+) + 8SiO2+ 14H2O

[0218] After extraction, use of the mineral derived bases, e.g., Ca / Mg / Na hydroxides can precipitate Fe(OH)2 from which H2 can be obtained hydrothermally at pressures from 10-100 bar and temperatures 200-350 °C, where the Fe(2+) is oxidized to either FeO(OH) or FesC3Fe(OH)2+ H2O - Fe3O4+ 4H2

[0219] In some embodiments, the reactions are performed within a slurry filled pressurized vessel (e.g., as shown in FIG. 11) while in other embodiments an existing artificial cavity' (mine shaft, coal mine) capable of maintaining hydrostatic pressure can be utilized. In some embodiments, the 3Fe(OH)2 can be thermally decomposed in a heat integrated reactor producing hydrogen and steam, as shown schematically' in FIG. 12.

[0220] Importantly, this reaction can be performed under mild-low cost conditions, P=l-10bar and T =100-700 C with the Gibbs free energy change <0 over all conditions. In this case H2 and steam are produced in the gas phase.

[0221] FIG. 13 shows a plot of Gibbs free energy' change for thermal decomposition of 3Fe(OH)2as a function of temperature. Further, in certain embodiments, oxidizing magnetite (FesC ) to form hematite (Fe2O?) could release additional hydrogen.

[0222] In some embodiments, the present disclosure relates to systems and methods for forecasting, evaluating, and remediating environmental hazards with stimulation and recovery. While earthquakes are conventionally associated with natural tectonic and volcanic forcings, there is increasing awareness and understanding of earthquakes triggered or induced by human activities. These activities include mining, production of conventional hydrocarbons, hydrofracking, geothermal energy' production, and wastewater disposal by injection into the subsurface. Most induced earthquakes are so small that they are not felt at the surface. However, occasionally large, damaging earthquakes are triggered. In addition to causing moderate damage to infrastructure, the resulting public opposition has led to the shutdown of energy production (e. g., Groningen natural gas, Basil geothermal) and hyperawareness of theAtty. Docket No.: GE0001PCT_8022-00200 risks of inj ecting or extracting fluids into or out of the subsurface. Thus, any viable integrated system for utilization of geologic hydrogen must address the risks of induced earthquakes.

[0223] Fault slip is triggered when the shear stress on a fault exceeds the strength of the fault. Fault strength is determined by the product of the friction coefficient and the effective normal stress, which presses the two sides of the fault together. This effective normal stress is the difference between the stress transmitted through the rock formation, which pushes the faces together, and the fluid pressure on the fault, which forces the faces apart.

[0224] Induced earthquakes are typically caused by two coupled processes. Injecting or producing fluids can affect fault strength locally and directly by increasing or decreasing the fluid pressure on the fault. In addition, the associated volume changes from poroelastic and thermoelastic deformation are propagated substantial distances through the rock, increasing or decreasing the normal and shear stresses acting on faults.

[0225] Whether fault slip is stable and aseismic, or unstable, generating seismic radiation, depends on the evolution of the coefficient of friction with fault slip. If friction increases with slip (typically "‘soft’' minerals, e. g., clays, brucite, serpentinite), fault slip is stable. If friction decreases with slip (typically “hard” minerals, e. g., quartz, calcite, olivine), fault failure can be a runaway process, leading to a seismic event. Seismic slip also requires a sufficiently long fault to allow the instability to grow7; fracture length is an important parameter.

[0226] Examples of seismic activity attributed to an increase in fluid pressure on faults include Oklahoma and Italy (both wastewater injection) and Basil (geothermal stimulation). Examples of situations in w hich earthquakes have been attributed to volume changes include Groningen, California, Alberta and Spain. In addition to triggering seismic events, internal deformation caused by volume changes due to production and injection can damage infrastructure. For example, well casings can be bent and displaced. These internal volume changes also cause deformation of Earth’s surface, causing vertical and horizontal motions which can damage infrastructure. For example, subsidence at the Groningen Field, Netherlands.

[0227] The typical changes in volume associated with injection and production of fluids has been of order 1%. The changes in volume associated with stimulation to produce hydrogen can be on the order of 40%. Thus, forecasting and managing seismic activity is crucial to development of integrated processes, systems and methods involving rock-water reactions.

[0228] Presented herein are methods for engineering stimulation that minimize the risk from internal deformation, surface deformation, and induced seismicity. These include integration of field data, laboratory data, numerical models and field experiments. In certain embodiments, key parameters include friction, strength, fracture geometry, fracture length, volume changes,Atty. Docket No.: GE0001PCT_8022-00200 and measurements of seismic activity and deformation. In certain embodiments, features of the embodiments can include one or more of a management of volume changes accompanying stimulation, management of friction and strength of stimulated regions, a management of shapes of stimulated regions where changes in volume and strength occur, a management of dimensions of stimulated regions where changes in volume and strength occur, a management of the interaction between the background stress field and the stimulated regions where changes in volume and strength occur, a management of the interactions between and among the stimulated regions w here changes in volume and strength occur, and / or a management of the sequencing of stimulating regions such that the stresses generated in subsequent stimulations are relieved in the previously stimulated regions where the friction is slip strengthening and slip is aseismic

[0229] In some aspects, the processes can include the management of volume changes accompanying stimulation. The volume changes accompanying stimulation can be large in magnitude and either positive or negative, depending on the densities of the reactants and products. Which reactions occur depend on the mineralogy of the source rock, the composition of the stimulating brine, and the local conditions where the reaction is occurring (P. T, pH. oxygen fugacity, silica activity, etc ). A novel component of our integrated approach is to choose the source rocks, reactions, etc. with the risk tolerance of the accompanying infrastructure in mind.

[0230] In some aspects, the processes can include the management of friction and strength of stimulated regions. The changes in frictional behavior and strength accompanying stimulation depend on the properties of the reactants and products. Which reactants and products are present depend on the mineralogy of the source rock, the composition of the stimulating brine, and the local conditions where the reaction is occurring (P, T, pH, oxygen fugacity’, silica activity, etc.). A novel component of our integrated approach is to choose the source rocks, reactions, etc. with the risk tolerance of the accompanying infrastructure to induced earthquakes in mind. While described in some aspects as using Al to control portions of the process, the various processes described herein can also be controlled using traditional sensors, controllers (e.g., logic controllers, supervisory controllers, programmable logic controllers, and the like), and equipment (e.g., pumps, heat exchangers, etc.).

[0231] In some aspects, the processes can include the management of shapes of stimulated regions where changes in volume and strength occur. Both the stresses generated in the surrounding medium and the strength of a stimulated region depend on its shape. For the same total volume change, the external stress state and the internal stresses are very different for, e.Atty. Docket No.: GE0001PCT_8022-00200 g., spherical vs pancake-shaped regions. These differences allow for management of stimulation to decrease risks.

[0232] In some aspects, the processes can include the management of dimensions of stimulated regions where changes in volume and strength occur. The propensity for unstable slip, the distribution of internal and surface deformation, and other important factors depend on the dimensions of stimulated zones. Thus, distributing the same total stimulated volume over multiple zones will result in different behavior than concentrating it into a single region. This factor is important to consider in overall system design.

[0233] In some aspects, the processes can include the management of the interaction between the background stress field and the stimulated regions where changes in volume and strength occur. The stresses in a stimulated region depend on the orientation of the region with respect to the background stress field. Choosing the orientation of stimulation appropriately can reduce risk of failure.

[0234] In some aspects, the processes can include the management of the interactions between and among the stimulated regions where changes in volume and strength occur. The stresses from multiple closely spaced stimulated regions will interact. This interaction can be manipulated to minimize risks.

[0235] In some aspects, the processes can include the management of the sequencing of stimulating regions such that the stresses generated in subsequent stimulations are relieved in the previously stimulated regions where the friction is slip strengthening and slip is aseismic. Stimulation that leads to slip-strengthening frictional properties will produce regions that tend to deform aseismically. Appropriate sequences of stimulation provide a mechanism to reduce the risk of inducing earthquakes while still generating large volume changes.

[0236] In some embodiments, the present disclosure relates to the integration of products and processes into onsite chemical and material processes. This can include methods and systems for the co-production of geothermal energy and amorphous silica using serpentinization- enhanced high-alkalinity brines with supercritical CO2 injection.

[0237] In this embodiment, co-production of resources (e.g., geothermal energy and amorphous silica) from subsurface geological formations is improved by controlling the quality of subsurface brines via serpentinization reactions, temperature, pH (via injection of carbon dioxide CO2 or supercritical carbon dioxide, SCO2), and optimizing geothermal heat. Amorphous silica is a form of silica that can be used in a cement making process avoiding high temperatures. Amorphous silica was used by the Romans in the form of volcanic ash from an active volcanic region, the Campi Flegrei near Naples (near a town called Pozzuoli). TheAtty. Docket No.: GE0001PCT_8022-00200 reaction, since then referred to as the Pozzolanic reaction allowed the Romans to make cement of Portland quality but avoiding high temperature.

[0238] The idea relates to the fields of geothermal energy production, material science, and carbon sequestration. Specifically, it pertains to methods and systems for the co-production of geothermal energy and amorphous silica, utilizing subsurface brines enriched through serpentinization processes and optimized geothermal conditions, enhanced by the injection of supercritical CO2.

[0239] Thus, in this example, presented herein is an integrated method and system for the efficient co-production of geothermal energy and amorphous silica using subsurface brines enriched through serpentinization processes, with the added enhancement of supercritical CO2 injection. The method involves circulating high-pH, silica-rich brines through geothermal reservoirs, utilizing the heat generated by serpentinization of iron-rich (for example, certain mafic or ultramafic) rocks, and controlling conditions for the precipitation of amorphous silica at the surface. Supercritical CO2 can be injected into the system to control the pH and temperature, thereby improving the efficiency of silica precipitation and facilitating carbon sequestration.The system leverages the natural exothermic reaction of serpentinization, which heats the brines and increases their pH, allowing for the dissolution of significant amounts of silica. The brines, further enhanced by the controlled injection of supercritical CO2, are transported to the surface, where cooling and pH adjustments induce the precipitation of high-purity amorphous silica. The geothermal energy extracted during this process is used for electricity generation or other energy' needs, making the system highly efficient and sustainable. In some aspects, the system can include a geothermal reservoir and serpentinization zone, a brine circulation loop, supercritical CO2 injection, a surface processing unit, and / or silica recovery and processing.

[0240] In some aspects, the system includes a geothermal reservoir geologically connected to an iron-rich rock formation undergoing active serpentinization. The reservoir can operate at temperatures ranging from 80 °C to 150 °C, facilitating both energy production and silica dissolution.

[0241] The system can feature a circulation loop that extracts high-pH, silica-rich brines from the serpentinization zone. These brines, heated by contact with iron-rich rocks and enriched with dissolved silica due to the high alkalinity (pH 11-13), are then enhanced by the injection of supercritical CO2.

[0242] Supercritical CO2 can be injected into the brines before they are brought to the surface.Atty. Docket No.: GE0001PCT_8022-00200The CO2 controls the pH, facilitating the dissolution of additional silica and optimizing conditions for its eventual precipitation. The injection also helps manage the temperature, ensuring that the cooling process for silica precipitation is controlled.

[0243] At the surface, the brines pass through a surface processing unit that can comprise a heat exchanger that extracts geothermal energy for electricity7generation or direct use. The cooled brines, now adjusted by the effects of supercritical CO2, are directed to a silica precipitation unit, where further cooling and pH adjustments induce the formation of high- purity amorphous silica.

[0244] In the silica recovery and processing unit, the precipitated amorphous silica can be collected, filtered, and processed for industrial use. The remaining brine, now depleted of silica and potentially7sequestering CO2 in the form of carbonates, can be reinjected into the subsurface to sustain the serpentinization process and continue CO2 sequestration.

[0245] The process and system can allow for enhanced silica dissolution and precipitation. The system can improve or enhance silica solubility in the brine by maintaining high temperatures and high pH levels, further enhanced by the controlled injection of supercritical CO2. The CO2 injection helps fine-tune the pH, enhancing the dissolution of silica and improving the efficiency of its precipitation. Controlled cooling can be used for precipitation. As the brine cools from geothermal temperatures to ambient conditions, silica precipitates out of solution as amorphous silica. Supercritical CO2 injection allows for precise control over the cooling and pH reduction, leading to higher yields and purity of the precipitated silica.

[0246] In some aspects, the processes and system can be used for the co-production of geothermal energy. Geothermal energy can be extracted from the brines before they are cooled for silica precipitation or metal ore recovery. The system uses heat exchangers and turbines to convert the thermal energy into electricity or to supply heat for industrial processes. The integration of silica production with geothermal energy extraction, combined with the environmental benefits of CO2 sequestration, enhances the overall efficiency^ of the system, making it more economically viable and environmentally sustainable.

[0247] The system can have a number of benefits. The system efficiently utilizes geothermal resources, high-iron (e.g., mafic or ultramafic) rock formations, and CO2, reducing waste and maximizing the output of valuable products. The injection of supercritical CO2 into the system not only enhances silica production but also sequesters carbon in the form of stable carbonates, contributing to climate change mitigation. The process can also be designed to minimize environmental impact by managing the chemistry of the brines, preventing groundwater contamination, and ensuring sustainable resource extraction through continuous circulation andAtty. Docket No.: GE0001PCT_8022-00200 reinjection of the brine.

[0248] The resulting system and processes can be used in a variety of industries. For example, in the construction industry', the amorphous silica produced can be used as a pozzolanic additive in cement, enhancing the strength and durability' of concrete. In geothermal power plants, the system can be integrated into existing geothermal power plants to co-produce energy' and silica, improving the economic returns of geothermal operations. In carbon sequestration projects, the system's ability to sequester CO? in mineral form makes it valuable for carbon capture and storage (CCS) initiatives, potentially creating a carbon-neutral or carbon-negative process.

[0249] Thus, in certain embodiments, presented herein is an integrated system for the coproduction of geothermal energy and amorphous silica, comprising a geothermal reservoir in geological connection with an ultramafic rock formation undergoing serpentinization, a circulation loop for extracting and transporting high-pH, silica-rich brines, and a surface processing unit for energy extraction and silica precipitation, wherein supercritical CO2 is inj ected to enhance the efficiency of silica precipitation.

[0250] In certain embodiments, presented herein is a method for enhancing the dissolution and precipitation of silica in subsurface brines by injecting supercritical CO2, which controls the pH and temperature of the brines, facilitating the controlled precipitation of amorphous silica.

[0251] In certain embodiments, presented herein is a process for generating geothermal energy7from silica-rich brines extracted from a serpentinization zone, wherein the brines are injected with supercritical CO2, cooled after energy extraction to induce silica precipitation, and the resulting silica is recovered for industrial use.

[0252] In certain embodiments, presented herein is a sustainable method for continuous extraction and reinjection of brines in a geothermal-serpentinization system, wherein the brines are cyclically enriched with silica and used for both energy production and material extraction, and supercritical CO2 is injected to sequester carbon in the form of stable carbonates.

[0253] In certain embodiments, presented herein is a method for carbon sequestration in a geothermal and serpentinization-enhanced system, wherein supercritical CO2 is injected into subsurface brines to promote the formation of stable carbonates while simultaneously enhancing the production of amorphous silica.

[0254] In certain embodiments, the systems and methods described above are integrated with brine generation from desalination. In certain embodiments, the methods and systems are utilized for off-shore applications.

[0255] In certain embodiments, conditions such as brine composition, temperature (T), pressure (P), pH, and / or surfactants are adjusted to minimize the consumption of water.Atty. Docket No.: GE0001PCT_8022-00200

[0256] In certain embodiments, a facility comprising injection and recovery wells and above ground processing facilities is located close to a body of water (e.g., a lake or river) including, for example, a salt water body such as the ocean, to provide water for injection. In certain embodiments, the facility is located in proximity to available ground water to provide water for injection. In certain embodiments, fresh water and / or salt water may be used to induce serpentinization. In certain embodiments, the method comprises using some of the energy produced from an initial reaction using fresh water to drive a thermal desalination process, or electrically-powered desalination process to reduce (possibly to zero) the salt content of injected water to an optimal range for hydrogen production. In certain embodiments, the method includes managing hazards such as seismicity, surface deformation, and / or leakage.

[0257] The present disclosure is also directed to systems and methods that make use of the regulation of pH using mixtures of CO2 and brine, as described herein. CO? speciation in brines occurs through the formation of bicarbonate and carbonate ions, with the release of protons, as demonstrated by the following reactions:CO2+ H2O HCO3 + H+HCO3 + H+COf

[0258] CO2 speciation in brines is highly dependent on the pH of the solution, with significant shifts in the forms of CO2 present as pH changes. Under acidic conditions (pH < 6), CO2 tends to remain as molecular CO2 and carbonic acid. As the pH increases toward 6-10, the equilibrium speciation shifts, and bicarbonate (HCCL ) becomes the dominant form. At even higher pH levels (above 10), carbonate (CO? ) becomes the predominant species wftile bicarbonate concentration decreases. This shifting speciation strongly influences CO2 solubility, with more CO2 being dissolved as pH increases. In brine systems, the presence of high ionic strength, along with factors such as temperature and pressure, can further modify the equilibrium by affecting CO2 solubility and the stability of different carbonate species. An illustration of pH dependence of this speciation is show n in FIG. 14. The addition of CO2 into brines can be an effective method for regulating pH. Brine-CCh mixtures, will be engineered to have optimal pH conditions that promote H2 generation while also sequestering CO2 as carbonates and reducing the risk of side reactions (e.g., methane formation).

[0259] Certain embodiments described herein make use of computer algorithms in the form of software instructions executed by a computer processor. In certain embodiments, the softw are instructions include a machine learning (ML) module, also referred to herein as artificial intelligence (Al) software. As used herein, a machine learning module refers to a computerAtty. Docket No.: GE0001PCT_8022-00200 implemented process (e.g., a software function) that implements one or more specific machine learning techniques, e.g.. artificial neural networks (ANNs). e.g., convolutional neural networks (CNNs), random forest, decision trees, support vector machines, and the like, in order to determine, for a given input, one or more output values. In certain embodiments, the input comprises image data and / or alphanumeric data which can include 2D and / or 3D datasets, numbers, words, phrases, or lengthier strings, for example. In certain embodiments, the one or more output values comprise image data (e.g. 2D and / or 3D datasets) and / or values representing numeric values, words, phrases, or other alphanumeric strings.

[0260] In certain embodiments, machine learning modules implementing machine learning techniques are trained, for example, using datasets that include categories of data described herein. Such training may be used to determine various parameters of machine learning algorithms implemented by a machine learning module, such as weights associated with layers in neural networks. In certain embodiments, once a machine learning module is trained, e.g., to accomplish a specific task such as identifying certain response strings, values of determined parameters are fixed and the (e.g., unchanging, static) machine learning module is used to process new data (e.g.. different from the training data) and accomplish its trained task without further updates to its parameters (e.g., the machine learning module does not receive feedback and / or updates). In certain embodiments, available input data includes training data and validation data, e.g., where the validation data is separate and non-overlapping with the training data. For example, in certain embodiments, training data is used during the training process to optimize a model, whereas validation data is used to check the accuracy of the model while operating on previously unseen data. In certain embodiments, training data is divided into batches (e.g., portions) that is sequentially used (e.g., in random order) as sets of inputs to train a model. In certain embodiments, a model is trained multiple times (e.g., epochs) on the entire set of training data. In certain embodiments, machine learning modules may receive feedback, e.g., based on user review of accuracy, and such feedback may be used as additional training data, to dynamically update the machine learning module. In certain embodiments, two or more machine learning modules may be combined and implemented as a single module and / or a single software application. In certain embodiments, two or more machine learning modules may also be implemented separately, e.g., as separate software applications. A machine learning module may be software and / or hardw are. For example, a machine learning module may be implemented entirely as software, or certain functions of a ANN module may be carried out via specialized hardware (e.g.. via an application specific integrated circuit (ASIC) and / or field programmable gate arrays (FPGAs)).Atty. Docket No.: GE0001PCT_8022-00200

[0261] In certain embodiments, machine learning modules implementing machine learning techniques may be composed of individual nodes (e.g. units, neurons). A node may receive a set of inputs that may include at least a portion of a given input data for the machine learning module and / or at least one output of another node. A node may have at least one parameter to apply and / or a set of instructions to perform (e.g., mathematical functions to execute) over the set of inputs. In certain embodiments, node instructions may include a step to provide various relative importance to the set of inputs using various parameters, such as weights. The weights may be applied by performing scalar multiplication (e.g., or other mathematical function) between a set of inputs values and the parameters, resulting in a set of weighted inputs. In certain embodiments, a node may have a transfer function to combine the set of w eighted inputs into one output value. A transfer function may be implemented by a summation of all the weighted inputs and the addition of an offset (e.g., bias) value. In certain embodiments, anode may have an activation function to introduce non-linearity into the output value. Non-limiting examples of the activation function include Rectified Linear Activation (ReLu), logistic (e.g., sigmoid), hyperbolic tangent (tanh), and softmax. In certain embodiments, anode may have a capability of remembering previous states (e.g.. recurrent nodes). Previous states may be applied to the input and output values using a set of learning parameters.

[0262] In certain embodiments, the machine learning module comprises a deep learning architecture composed of nodes organized into layers. For example, a layer is a set of nodes that receives data input (e.g.. weighted or non-weighted input), transforms it (e.g., by carrying out instructions, e.g., applying a set of functions e g., linear and / or non-linear functions), and passes transformed values as output (e.g., to the next layer). In certain embodiments, the set of nodes in a particular layer may share the same parameters and instructions without interacting with each other. A machine learning module may be composed of at least one layer (e.g., ordered). Examples of types of layers include convolutional layers (e.g., layers with a kernel, a matrix of parameters that is slid across an input to be multiplied with multiple input values to reduce them to a single output value); fully connected (FC) layers (e.g. all nodes are connected to all outputs of the previous layer); recurrent layers, long / short term memory (LSTM) layers, gated recurrent unit (GRU) layers (e.g.. nodes with the various abilities to memorize and apply their previous inputs and / or outputs); batch normalization (BN) layers (e.g., layers that normalize a set of outputs from another layer, allowing for more independent learning of individual layers); activation layers (e.g., layers with nodes that only contain an activation function); and / or (un)pooling layers (e.g., layers that reduce (increase) dimensions of an input by summarizing (splitting) input values in defined patches).Atty. Docket No.: GE0001PCT_8022-00200

[0263] In certain embodiments, the performance of a machine learning module may be characterized by its ability to produce an output data with specific accuracy. To achieve specific accuracy, a training process is performed to find optimal parameters, such as weights, for each node in each layer of the machine learning module. In certain embodiments, the training process of a machine learning module may involve using output data to calculate an objective function (e.g., cost function, loss function, error function) that needs to be optimized (e.g.. minimized, maximized). For example, a machine learning objective function may be a combination of a loss function and regularization parameter. The loss function is related to how well the output is able to predict the input. The loss function may take various forms, like mean squared error, mean absolute error, binary' cross-entropy, categorical cross-entropy, for example. The regularization term may be needed to prevent overfitting and improve generalization of the training process. Examples of regularization techniques include LI Regularization or Lasso Regression, L2 Regularization or Ridge Regression, and Dropout (e.g., dropping layer outputs at random during training process).

[0264] In certain embodiments, objective function optimization of a machine learning module may involve finding at least one (e.g., all) of the present global optima (e.g.. as opposed to local optima). In certain embodiments, the algorithm for objective function optimization follows principles of mathematical optimization for a multi-variable function and relies on achieving specific accuracy of the process. Examples of objective function optimization algorithms include gradient descent, nonlinear conjugate gradient, random search. Levenberg-Marquardt algorithm, limited-memory Broyden-Fietcher-Goldfarb-Shanno algorithm, pattern search, basin hopping method, Kry lov method, Adam method, genetic algorithm, particle swarm optimization, surrogate optimization, and simulated annealing.

[0265] In certain embodiments, the machine learning modules comprise neural networks, e.g., graph neural networks (GNNs), with nodes (vertices) and edges. In certain embodiments, the machine learning modules comprise one or more Multi-Layer Perceptrons (MLPs), e.g., neural networks with fixed activation functions on nodes and learnable weights on edges. In certain embodiments, the machine learning modules comprise one or more Kolmogorov-Arnold Networks (KANs). e.g., neural networks with learnable activation functions on edges and sum operation on nodes.

[0266] In certain embodiments, the machine learning modules comprise one or more generative Al modules. Rather than depending on use of predetermined weights and rules, generative Al leverages complex neural networks and algorithms to understand patterns and produce output that mimic human creativity. Examples of generative Al modules includeAtty. Docket No.: GE0001PCT_8022-00200 image synthesis models (e.g., DALL-E3, DALL-E2, Imagen 3 in Gemini, Craiyon, and the like) and text generation models (e.g., ChatGPT, GPT-4, and the like).

[0267] In certain embodiments, the machine learning modules comprises one or more imagebased segmentation neural networks. Illustrative examples of segmentation neural networks include, for instance, Deep Image Matting (DIM), Semantic Segmentation methods (U-Net, DeepLab Series), Mask R-CNN. Chroma Keying CNNs, RefmeNet, and MODNet.

[0268] In certain embodiments. Al used to generate alphanumeric text responsive to a user query and / or a set of input data may comprise (and / or utilize) one or more large language models (LLMs) (e.g., wherein the one or more LLMs comprise(s) one or more members selected from the group consisting of BERT (Google) (or other transformer-based models), Falcon 40B. Galactica, GPT-3 (Generative Pre-trained Transformer. OpenAI), GPT-3.5 (OpenAI), GPT-4 (OpenAI), LaMDA (language model for dialogue applications, Google), Llama (large language model Meta Al) (Meta), Orca LLM (Microsoft), PaLM (Pathways Language Model), Phi-1 (Microsoft), StableLM (Stability Al), BLOOM (Hugging Face), RoBERTa (Meta), XLM-RoBERTa (Meta), NeMO LLM (Nvidia), XLNet (Google), Generate (Cohere). GLM-130B (Hugging Face), and Claude (Anthropic)) (e.g.. wherein the one or more LLMs comprise(s) one or more members selected from the group consisting of an autoregressive LLM, autoencoding LLM, encoder-decoder LLM, bidirectional LLM, Finetuned LLMs, and multimodal LLMs).

[0269] As shown in FIG. 15. an implementation of a network environment 400 for use in providing systems, methods, and architectures as described herein is shown and described. In brief overview, referring now to FIG. 15, a block diagram of an exemplary cloud computing environment 400 is shown and described. The cloud computing environment 400 may include one or more resource providers 402a, 402b. 402c (collectively. 402). Each resource provider 402 may include computing resources. In some implementations, computing resources may include any hardware and / or software used to process data. For example, computing resources may include hardw are and / or software capable of executing algorithms, computer programs, and / or computer applications. In some implementations, exemplary’ computing resources may include application servers and / or databases with storage and retrieval capabilities. Each resource provider 402 may be connected to any other resource provider 402 in the cloud computing environment 400. In some implementations, the resource providers 402 may be connected over a computer network 408. Each resource provider 402 may be connected to one or more computing devices 404a, 404b. 404c (collectively, 404), over the computer network 408.Atty. Docket No.: GE0001PCT_8022-00200

[0270] The cloud computing environment 400 may include a resource manager 406. The resource manager 406 may be connected to the resource providers 402 and the computing devices 404 over the computer network 408. In some implementations, the resource manager 406 may facilitate the provision of computing resources by one or more resource providers 402 to one or more computing devices 404. The resource manager 406 may receive a request for a computing resource from a particular computing device 404. The resource manager 406 may identify one or more resource providers 402 capable of providing the computing resource requested by the computing device 404. The resource manager 406 may select a resource provider 402 to provide the computing resource. The resource manager 406 may facilitate a connection between the resource provider 402 and a particular computing device 404. In some implementations, the resource manager 406 may establish a connection between a particular resource provider 402 and a particular computing device 404. In some implementations, the resource manager 406 may redirect a particular computing device 404 to a particular resource provider 402 with the requested computing resource.

[0271] FIG. 16 shows an example of a computing device 500 and a mobile computing device 550 that can be used to implement the techniques described in this disclosure. The computing device 500 is intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The mobile computing device 550 is intended to represent various forms of mobile devices, such as personal digital assistants, cellular telephones, smartphones, and other similar computing devices. The components shown here, their connections and relationships, and their functions, are meant to be examples only, and are not meant to be limiting.

[0272] The computing device 500 includes a processor 502, a memory’ 504. a storage device 506, a high-speed interface 508 connecting to the memory 504 and multiple high-speed expansion ports 510, and a low-speed interface 512 connecting to a low-speed expansion port 514 and the storage device 506. Each of the processor 502, the memory 504, the storage device 506, the high-speed interface 508, the high-speed expansion ports 510, and the low-speed interface 512, are interconnected using various busses, and may be mounted on a common motherboard or in other manners as appropriate. The processor 502 can process instructions for execution within the computing device 500, including instructions stored in the memory 504 or on the storage device 506 to display graphical information for a GUI on an external input / output device, such as a display 516 coupled to the high-speed interface 508. In other implementations, multiple processors and / or multiple buses may be used, as appropriate, alongAtty. Docket No.: GE0001PCT_8022-00200 with multiple memories and types of memory. Also, multiple computing devices may be connected, with each device providing portions of the operations (e.g.. as a server bank, a group of blade servers, or a multi-processor system). Thus, as the term is used herein, where a plurality of functions are described as being performed by “a processor”, this encompasses embodiments wherein the plurality of functions are performed by any number of processors (one or more) of any number of computing devices (one or more). Furthermore, where a function is described as being performed by "‘a processor”, this encompasses embodiments wherein the function is performed by any number of processors (one or more) of any number of computing devices (one or more) (e.g., in a distributed computing system).

[0273] The memory 504 stores information within the computing device 500. In some implementations, the memory 504 is a volatile memory unit or units. In some implementations, the memory 504 is a non-volatile memory unit or units. The memory 504 may also be another form of computer-readable medium, such as a magnetic or optical disk.

[0274] The storage device 506 is capable of providing mass storage for the computing device 500. In some implementations, the storage device 506 may be or contain a computer-readable medium, such as a floppy disk device, a hard disk device, an optical disk device, or a tape device, a flash memory or other similar solid state memory device, or an array of devices, including devices in a storage area network or other configurations. Instructions can be stored in an information carrier. The instructions, when executed by one or more processing devices (for example, processor 502), perform one or more methods, such as those described above. The instructions can also be stored by one or more storage devices such as computer- or machine-readable mediums (for example, the memory' 504, the storage device 506, or memory on the processor 502).

[0275] The high-speed interface 508 manages bandwidth-intensive operations for the computing device 500, while the low-speed interface 512 manages lower bandwidth-intensive operations. Such allocation of functions is an example only. In some implementations, the high-speed interface 508 is coupled to the memory 504, the display 516 (e.g., through a graphics processor or accelerator), and to the high-speed expansion ports 510, which may accept various expansion cards (not shown). In the implementation, the low-speed interface 512 is coupled to the storage device 506 and the low-speed expansion port 514. The low-speed expansion port 514, which may include various communication ports (e.g., USB, Bluetooth®, Ethernet, wireless Ethernet) may be coupled to one or more input / output devices, such as a keyboard, a pointing device, a scanner, or a networking device such as a switch or router, e.g., through a network adapter.Atty. Docket No.: GE0001PCT_8022-00200

[0276] The computing device 500 may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a standard server 520, or multiple times in a group of such servers. In addition, it may be implemented in a personal computer such as a laptop computer 522. It may also be implemented as part of a rack server system 524. Alternatively, components from the computing device 500 may be combined with other components in a mobile device (not shown), such as a mobile computing device 550. Each of such devices may contain one or more of the computing device 500 and the mobile computing device 550, and an entire system may be made up of multiple computing devices communicating with each other.

[0277] The mobile computing device 550 includes a processor 552, a memory 564, an input / output device such as a display 554, a communication interface 566, and a transceiver 568, among other components. The mobile computing device 550 may also be provided with a storage device, such as a micro-drive or other device, to provide additional storage. Each of the processor 552, the memory 564, the display 554, the communication interface 566, and the transceiver 568, are interconnected using various buses, and several of the components may be mounted on a common motherboard or in other manners as appropriate.

[0278] The processor 552 can execute instructions within the mobile computing device 550, including instructions stored in the memory 564. The processor 552 may be implemented as a chipset of chips that include separate and multiple analog and digital processors. The processor 552 may provide, for example, for coordination of the other components of the mobile computing device 550, such as control of user interfaces, applications run by the mobile computing device 550, and wireless communication by the mobile computing device 550.

[0279] The processor 552 may communicate with a user through a control interface 558 and a display interface 556 coupled to the display 554. The display 554 may be, for example, a TFT (Thin-Film-Transistor Liquid Crystal Display) display or an OLED (Organic Light Emitting Diode) display, or other appropriate display technology. The display interface 556 may comprise appropriate circuitry' for driving the display 554 to present graphical and other information to a user. The control interface 558 may receive commands from a user and convert them for submission to the processor 552. In addition, an external interface 562 may provide communication with the processor 552, so as to enable near area communication of the mobile computing device 550 with other devices. The external interface 562 may provide, for example, for wired communication in some implementations, or for wireless communication in other implementations, and multiple interfaces may also be used.

[0280] The memory 564 stores information within the mobile computing device 550. TheAtty. Docket No.: GE0001PCT_8022-00200 memory' 564 can be implemented as one or more of a computer-readable medium or media, a volatile memory unit or units, or a non-volatile memory’ unit or units. An expansion memory 574 may also be provided and connected to the mobile computing device 550 through an expansion interface 572, which may include, for example, a SIMM (Single In Line Memory Module) card interface. The expansion memory' 574 may provide extra storage space for the mobile computing device 550, or may also store applications or other information for the mobile computing device 550. Specifically, the expansion memory 574 may include instructions to carry out or supplement the processes described above, and may7include secure information also. Thus, for example, the expansion memory7574 may be provide as a security7module for the mobile computing device 550. and may be programmed with instructions that permit secure use of the mobile computing device 550. In addition, secure applications may be provided via the SIMM cards, along with additional information, such as placing identifying information on the SIMM card in a non-hackable manner.

[0281] The memory may include, for example, flash memory and / or NVRAM memory’ (nonvolatile random access memory), as discussed below. In some implementations, instructions are stored in an information carrier. The instructions, when executed by one or more processing devices (for example, processor 552), perform one or more methods, such as those described above. The instructions can also be stored by one or more storage devices, such as one or more computer- or machine-readable mediums (for example, the memory 564, the expansion memory 574. or memory on the processor 552). In some implementations, the instructions can be received in a propagated signal, for example, over the transceiver 568 or the external interface 562.

[0282] The mobile computing device 550 may communicate wirelessly through the communication interface 566. which may include digital signal processing circuitry where necessary'. The communication interface 566 may provide for communications under various modes or protocols, such as GSM voice calls (Global System for Mobile communications), SMS (Short Message Service), EMS (Enhanced Messaging Service), or MMS messaging (Multimedia Messaging Service), CDMA (code division multiple access), TDMA (time division multiple access), PDC (Personal Digital Cellular). WCDMA (Wideband Code Division Multiple Access), CDMA2000, or GPRS (General Packet Radio Service), among others. Such communication may occur, for example, through the transceiver 568 using a radio-frequency. In addition, short-range communication may occur, such as using a Bluetooth®, Wi-Fi™, or other such transceiver (not shown). In addition, a GPS (Global Positioning System) receiver module 570 may provide additional navigation- and location-Atty. Docket No.: GE0001PCT_8022-00200 related wireless data to the mobile computing device 550, which may be used as appropriate by applications running on the mobile computing device 550.

[0283] The mobile computing device 550 may also communicate audibly using an audio codec 560, which may receive spoken information from a user and convert it to usable digital information. The audio codec 560 may likewise generate audible sound for a user, such as through a speaker, e.g., in a handset of the mobile computing device 550. Such sound may include sound from voice telephone calls, may include recorded sound (e.g.. voice messages, music fdes, etc.) and may also include sound generated by applications operating on the mobile computing device 550.

[0284] The mobile computing device 550 may be implemented in a number of different forms, as shown in the figure. For example, it may be implemented as a cellular telephone 580. It may also be implemented as part of a smart-phone 582, personal digital assistant, or other similar mobile device.

[0285] Various implementations of the systems and techniques described here can be realized in digital electronic circuitry, integrated circuitry, specially designed ASICs (application specific integrated circuits), computer hardware, firmware, software, and / or combinations thereof. These various implementations can include implementation in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, coupled to receive data and instructions from, and to transmit data and instructions to. a storage system, at least one input device, and at least one output device.

[0286] These computer programs (also known as programs, software, software applications or code) include machine instructions for a programmable processor, and can be implemented in a high-level procedural and / or object-oriented programming language, and / or in assembly / machine language. As used herein, the terms machine-readable medium and computer-readable medium refer to any computer program product, apparatus and / or device (e.g., magnetic discs, optical disks, memory', Programmable Logic Devices (PLDs)) used to provide machine instructions and / or data to a programmable processor, including a machine- readable medium that receives machine instructions as a machine-readable signal. The term machine-readable signal refers to any signal used to provide machine instructions and / or data to a programmable processor.

[0287] To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user and a keyboard and aAtty. Docket No.: GE0001PCT_8022-00200 pointing device (e.g., a mouse or a trackball) by which the user can provide input to the computer. Other kinds of devices can be used to provide for interaction with a user as well; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form, including acoustic, speech, or tactile input.

[0288] The systems and techniques described here can be implemented in a computing system that includes a back end component (e.g., as a data server), or that includes a middleware component (e g., an application server), or that includes a front end component (e.g., a client computer having a graphical user interface or a Web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back end. middleware, or front end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network (LAN), a wide area network (WAN), and the Internet.

[0289] The computing system can include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other.

[0290] In some implementations, certain modules described herein can be separated, combined or incorporated into single or combined modules. Any modules depicted in the figures are not intended to limit the systems described herein to the software architectures shown therein.

[0291] Elements of different implementations described herein may be combined to form other implementations not specifically set forth above. Elements may be left out of the processes, computer programs, databases, etc. described herein without adversely affecting their operation. In addition, the logic flows depicted in the figures do not require the particular order shown, or sequential order, to achieve desirable results. Various separate elements may be combined into one or more individual elements to perform the functions described herein.

[0292] Having described various systems, processes, and techniques, certain aspects as disclosed herein can include, but are not limited to:

[0293] In a first aspect, a method for the design and / or control of a process for production of hydrogen from a geologic environment (e.g., in situ production (e.g., extraction) of hydrogen from a subsurface rock formation) comprises: receiving, by a processor of a computing device, one or more inputs comprising data for one or more parameters (e.g., measurements of the parameters and / or data from one or more existing databases, e.g., geothermal well data bases)Atty. Docket No.: GE0001PCT_8022-00200 related to the geologic environment (e g. the subsurface rock formation); and using a machine learning module and the received input to produce one or more outputs relating to the design and / or control of the process for production of hydrogen from the geologic environment (e.g., the subsurface rock formation).

[0294] A second aspect can include the method of the first aspect, wherein the received one or more inputs comprises data for one or more parameters at one or more depths (e.g.. as a function of ID, 2D. or 3D position) and / or at one or more times, said one or more parameters selected from the group consisting of (a) to (1) as follows: (a) temperature and / or thermal gradient profiles / data; (b) pressure and / or pressure profile; (c) concentration of species (e.g., salinity. Na+, Ch, SiCh) in the geothermal fluid (e.g., said fluid comprising water); (d) mineral composition (e.g., iron content of the subsurface rock formation, e.g., Fe21. e.g., identification and analysis of mineral formations enriched in Fe2+including but not limited to formations rich in the minerals or elemental combinations, e.g., Olivine, Grunerite (Fe?SisO22(OH)2), Hercynite (FeA12O4), Siderite (FeCOi). Magnetite (FeiCh). pyroxene, banded iron, greywackes, kimerlites, and / or basalt); (e) pH level; (f) oxidation state (e.g.. oxidation-reduction potential, ORP); (g) gas composition (e.g., CO2. CH4. H2S); (h) flow rate and / or enthalpy; (i) fracturing conditions (e.g., fracture density, penetration, surface area estimates, fluid flow, and / or stress state); (j)porosity and / or structure; (k) silica activity; and (1) dissolution and / or solubility of H2.

[0295] A third aspect can include the method of the first or second aspect, wherein the one or more outputs comprises one or more thermodynamic quantities selected from the group consisting of Gibbs free energy (AG), enthalpy (AH), entropy (AS), equilibrium constant (K), heat capacity (Cp), and reaction rate.

[0296] In a fourth aspect, a method for the design and / or control of an integrated process for the production of multiple resources from a geologic environment (e.g., in situ production (e.g., extraction) of multiple resources from a subsurface rock formation) comprises: receiving, by a processor of a computing device, one or more inputs comprising data for one or more parameters (e.g., measurements of the parameters and / or data from one or more existing databases, e.g., geothermal well data bases) related to the geologic environment (e.g. the subsurface rock formation); and using a machine learning module and the received input to produce one or more outputs relating to the design and / or control of the process for production of the multiple resources from the geologic environment (e.g., the subsurface rock formation), wherein the multiple resources (or products derived from the multiple resources) comprises two or more members selected from the group consisting of members (i) through (iv) as follows: (i) hydrogen, (ii) heat (e.g., geothermal energy), (iii) amorphous silica, and (iv) one orAtty. Docket No.: GE0001PCT_8022-00200 more rare earth minerals (e.g., and wherein the machine learning module also produces one or more outputs relating to the design and / or control of a (further) process for production of one or more products derived from one or more of the multiple resources, e.g., wherein the one or more derived products comprises ethylene, ammonia (e.g., Haber-Bosch process), e-fuels (e.g., via Fischer-Tropsch process) (e.g., e-ammonia, e-diesel, e-gasoline, or e-kerosene, e.g., where part of the process heat is provided by electricity), biofuel (e.g., enhanced biofuel production), direct reduced iron (DRI) (e.g., for steel production), syngas, and cement / green cement)).

[0297] A fifth aspect can include the method of the fourth aspect, wherein the multiple resources comprises hydrogen (e.g., geologic hydrogen) and heat (e.g., geothermal energy) (e.g., wherein the integrated process synergistically reduces transportation costs, utilizes byproducts of processes, minimizes water usage, and / or incorporates water treatment) (e.g., wherein the integrated process comprises in-situ generation of hydrogen gas via brine injection into iron-rich formations, with enhanced heat recovery and / or co-production of amorphous silica, e.g., featuring application of pressure modulated hydraulics and / or geochemical control).

[0298] A sixth aspect can include the method of any one of the first to fifth aspects, wherein the machine learning module comprises a Kolmogorov-Arnold Network (KAN) (e.g., a multilayer KAN trained to produce the one or more outputs comprising one or more thermodynamic quantities selected from the group consisting of Gibbs free energy' (AG), enthalpy (AH), entropy (AS), equilibrium constant (K), heat capacity (Cp), and reaction rate).

[0299] A seventh aspect can include the method of the sixth aspect, wherein the one or more inputs used by the KAN comprises one or more members selected from the group consisting of mineral composition (e.g., magnetite concentration), porosity7, permeability7, resistivity7, fluid composition / chemistry, fluid saturation, temperature, pressure, hydrogen concentration, CO2 concentration, salinity of a circulating fluid, fracture density, and oxidation-reduction potential (ORP).

[0300] An eighth aspect can include the method of any7one of the first to seventh aspects, wherein the machine learning module comprises a language model (e.g., a large language model, LLM) (e.g.. wherein the language model comprises one or more members selected from the group consisting of an Adversarial Generative Network (GAN), a Variational Autoencoder (VAE), and a Transformer-based Model) (e.g., wherein the language model is applied to geothermal w7ell data bases).

[0301] A ninth aspect can include the method of the eight aspect, wherein the language model: (a) uses as input (i) sequences of chemical reactions and / or (ii) conditions that represent changes in the process (or the integrated process) based on well data; (b) tokenizes the inputAtty. Docket No.: GE0001PCT_8022-00200(e.g., breaks the chemical reactions into individual components such as reactants, products, and conditions, that can be understood by the language model); and (c) is trained to produce output data comprising predicted one or more thermodynamic quantities and / or reaction outcome.

[0302] A tenth aspect can include the method of any one of the first to ninth aspects, wherein the machine learning module simulates reactive flow in a fluid-filled crack to optimize pressure control (e.g., in a Huff and Puff dual production / inj ection system).

[0303] An eleventh aspect can include the method of any one of the first to tenth aspects, further comprising determining, by the processor of the computing device, one or more process parameters relating to the design and / or control of the process for production of hydrogen from the geologic environment (e g., the subsurface rock formation), wherein determining the one or more process parameters comprises using one or more conventional process models (e.g., constitutive models based on the laws of physics) (e.g., chemical engineering, 3D mechanical modeling, and / or mechanical engineering process simulators, e.g., finite element simulations) (e.g., dynamic process / unit operation simulators for process design and / or process control, e.g., simulators based on heat transfer, mass transfer, chemical reaction, and fluid dynamics fundamentals) (e.g.. computer models that solve mass, momentum, energy, and / or species conservation equations, e.g., governing equations subject to boundary conditions / initial conditions) (e.g., one or more commercial process simulators such as CHEMCAD by Chemstations, Aspen Plus, Aspen HYSYS, DWSIM, PRO / II, ProSimPlus, SuperPro Designer, and gPROMS. as well as computational fluid dynamics simulators such as ANSYS CFX, ANSYS Fluent, ANSYS Multiphysics, COMSOL Multiphysics, FLOW-3D, STAR-CD, STAR-CCM+, OpenFOAM, AVL FIRE, and ANSYS Polyflow, and / or one or more mechanical simulation models such as Ansys, Simulink, SolidWorks Simulation, AnyLogic, and Altair OptiStruct, GoldSim, Autodesk CFD, Dassault DELMIA, Simcenter, NI Multisim, Realflow, Simio, Cadence Spectre, and Dassalut SIMULIA).

[0304] A twelfth aspect can include the method of any one of the first to eleventh aspects, further comprising determining, by the processor of the computing device, using a digital twin (e.g., a digital twin of a particular geologic formation / site - a digital representation of a formation / site over time, e.g., updated with real-time data and / or data from conventional 3D and / or process simulation and, optionally, a machine learning module), (i) at least one of the one or more outputs relating to the design and / or control of the process for production of hydrogen from the geologic environment (e.g., the subsurface rock formation), and / or (ii) one or more process parameters relating to the design and / or control of the process for production of hydrogen from the geologic environment (e.g., the subsurface rock formation).Atty. Docket No.: GE0001PCT_8022-00200

[0305] A thirteenth aspect can include the method of any one of the first to twelfth aspects, wherein the design of the process (or integrated process) comprises identification of one or more candidate sites for in-situ production (e.g., extraction or harvesting) of geologic hydrogen (e.g., wherein, in addition to Fe2+ content of a formation at a candidate site, the machine learning module considers factors such as transportation availability and / or transportation costs, availability of a suitable water supply, and / or other practical factors).

[0306] In a fourteenth aspect, a process for in-situ generation of hydrogen gas from a subsurface geologic formation (e g., and, optionally, production of geothermal heat and / or amorphous silica and / or a rare earth mineral), comprises injecting brine into the subsurface geologic formation (e.g., wherein the formation is iron-rich) (e.g., mafic rock formation, an ultramafic rock formation, a banded iron formation (BIF). e.g., iron-rich hematite and / or magnetite, with adjacent silica-rich layers), recovering generated hydrogen gas, recovering heat produced from exothermic reaction, and, optionally, recovering amorphous silica (e.g., wherein the process comprises applying pressure modulated hydraulics and geochemical control for enhanced chemical and heat recovery by facilitating dissolution of Fe(2+) from the rock formation).

[0307] A fifteenth aspect can include the process of the fourteenth aspect, comprising use of a machine learning module (e.g., as recited in any of the first to thirteenth aspects) to perform at least one of (i) to (iii) as follows: (i) identify a site for the process, (ii) design the process, and (iii) control the process.

[0308] A sixteenth aspect can include the process of the fourteenth or fifteenth aspect, comprising alternating injection and extraction cycles applying pressure and / or temperature modulated in time and amplitude in a multitude of formation dependent patterns to cause growth of dense fracture networks with complex topology (e.g., performing a Huff and Puff process).

[0309] A seventeenth aspect can include the process of any one of the fourteenth to sixteenth aspects, comprising alternately injecting high pH and low' pH brines in the rock formation to enhance dissolution of minerals from the rock (e.g., performing cyclic leaching).

[0310] In an eighteenth aspect, a process for in-situ generation of hydrogen gas from a repurposed diamond mine (e.g., a kimberlite and / or lamproite dyke or pipe), comprises injecting brine into the repurposed diamond mine and recovering generated hydrogen gas (e.g., and recovering heat produced from exothermic reaction, and, optionally, recovering amorphous silica and / or rare earth minerals) (e.g., wherein the process comprises applying pressure modulated hydraulics and geochemical control for enhanced chemical and heat recovery byAtty. Docket No.: GE0001PCT_8022-00200 facilitating dissolution of Fe(2+)) (e.g., wherein the process comprises use of a machine learning module (e.g.. as recited in any of the first to thirteenth aspects) to perform at least one of (i) to (iii) as follows: (i) identify a site for the process, (ii) design the process, and (iii) control the process) (e.g., wherein the process comprises alternately injecting high pH and low pH brines in the repurposed diamond mine to enhance dissolution of minerals (e.g., performing cyclic leaching)) (e.g., wherein the process comprises use of a machine learning module (e.g., as recited in any of the first to thirteenth aspects) to perform at least one of (i) to (iii) as follows: (i) identify a site for the process, (ii) design the process, and (iii) control the process).

[0311] In a nineteenth aspect, a process for forecasting, evaluating, and / or remediating environmental hazards with stimulation and recovery of geologic hydrogen (e g., as part of a system for geologic hydrogen, geothermal energy, amorphous silica, rare earth mineral, and / or other resource production as presented herein), comprises performing one or more of (i) to (vii) as follows (e.g., using a machine learning module, e.g., as recited in any of the first to thirteenth aspects): (i) management of volume changes accompanying the stimulation; (ii) management of friction and strength of stimulation regions; (iii) management of shapes of shapes of stimulated regions where changes in volume and / or strength occur; (iv) management of dimensions of stimulated regions where changes in volume and strength occur; (v) management of an interaction between a background stress field and stimulated regions where changes in volume and strength occur; (vi) management of interactions between and among stimulated regions where changes in volume and strength occur; and (vii) management of sequencing of stimulating regions such that stresses generated in subsequent stimulations are relieved in the previously stimulated regions where friction is slip strengthening and slip is aseismic.

[0312] In a twentieth aspect, a process for controlled fracturing of a subsurface rock formation (e.g., for stimulation and recovery of geologic hydrogen, e.g., as part of a system for geologic hydrogen, geothermal energy, amorphous silica, rare earth mineral, and / or other resource production as presented herein), comprises injecting a fluid having controlled composition into the subsurface rock formation in a controlled manner (e.g., at controlled temperature, flow rates, pressure, and / or temperature) (e.g.. controlling conditions of the injected fluid using a machine learning module) (e.g., wherein the process comprises use of a machine learning module (e.g., as recited in any of the first to thirteenth aspects)).

[0313] In a twenty first aspect, a process for co-production of geothermal energy and amorphous silica using serpentinization-enhanced high-alkalinity brine with supercritical CO2 injection, comprises circulating a high-pH, silica-rich brine through a geothermal reservoir,Atty. Docket No.: GE0001PCT_8022-00200 utilizing heat generated by serpentinization of iron-rich rock from a rock formation, injecting supercritical CO2 to control pH and / or temperature, thereby improving efficiency of silica precipitation (e.g., and facilitating carbon sequestration), and collecting the amorphous silica (e.g., wherein the process comprises use of a machine learning module (e.g., as recited in any of the first to thirteenth aspects)).

[0314] A twenty second aspect can include the process of the twenty first aspect, wherein the process comprises one or more of (i) to (viii) as follows: (i) a geothermal reservoir connected to a serpentinization zone comprising a region of the iron-rich rock formation undergoing serpentinization; (ii) a brine circulation loop that extracts high-pH silica-rich brine from the serpentinization zone; (iii) supercritical CO2 injection into the brine in the rock formation (before being brought to the surface); (iv) a surface processing unit comprising a heat exchanger that extracts geothermal energy (e.g., for electricity7generation or direct use); (v) collection of precipitated amorphous silica (e.g., collection, filtration, and / or processing of the amorphous silica for industrial use); (vi) enhanced silica solubility in the brine, e.g., bymaintaining high temperature and high pH, further enhanced by controlled injection of supercritical CO2; (vii) controlled cooling of the brine for precipitation of the silica; and (viii) extraction of geothermal energy from the brine (e g., before brine is cooled for silica precipitation).

[0315] In a twenty third aspect, a process (e.g., a process for production of geologic hydrogen, geothermal energy, amorphous silica, rare earth mineral, and / or other resource production as presented herein) comprises regulating pH of brine solutions by contacting the brine with CO2 (e.g., wherein the process comprises use of a machine learning module (e.g., as recited in any of the first to thirteenth aspects)).

[0316] In a twenty fourth aspect, a process for recovery of enhanced value from geologic Fe2+in a low pH environment (e.g., in a system for geologic hydrogen, geothermal energy, amorphous silica, rare earth mineral, and / or other resource production as presented herein), comprises using one or more acids and / or chelating agents to mobilize and / or stabilize Fe2+into solution (e.g., wherein the process comprises use of a machine learning module (e.g., as recited in any of the first to thirteenth aspects)).

[0317] In a twenty fifth aspect, a system comprises: a processor of a computing device; and a memory7having instructions stored thereon, wherein the instructions, when executed by the processor, cause the processor to perform the method of any one of the first to thirteenth aspects.

[0318] In a tw enty sixth aspect, a method for fracturing of a subsurface rock formation forAtty. Docket No.: GE0001PCT_8022-00200 hydrogen production, comprises: injecting a fluid comprising water into a subsurface rock formation under controlled conditions, wherein the fluid is injected at a pressure below the breakdown pressure of the subsurface rock; generating fractures in the subsurface rock; and recovering hydrogen gas produced by subsurface rock after the generation of the fractures.

[0319] A twenty seventh aspect can include the method of the twenty sixth aspect, wherein injecting the fluid comprises injecting the fluid to induce serpentinization reactions, wherein the subsurface rock formation comprises a Fe2+-containing mineral, wherein generating the fractures comprises generating reaction-induced fracturing through volume changes accompanying the serpentinization reactions, and wherein recovering the hydrogen gas comprises recovering the hydrogen gas produced by the serpentinization reactions.

[0320] A twenty eighth aspect can include the method of the twenty seventh aspect, wherein the Fe2+-containing mineral is selected from the group consisting of olivine, fayalite, grunerite, siderite, ferrosilite, and combinations thereof

[0321] A twenty ninth aspect can include the method of the twenty seventh or twenty eighth aspect, wherein the volume changes range from about 1% to about 60%.

[0322] A thirtieth aspect can include the method of the any one of the twenty seventh to twenty ninth aspects, wherein the volume changes range from about 10% to about 50%.

[0323] A thirty first aspect can include the method of the any one of the twenty seventh to thirtieth aspects, wherein the serpentinization reactions generate crystallization pressures ranging from about 100 MPa to about 2000 MPa.

[0324] A thirty’ second aspect can include the method of the any one of the twenty’ seventh to thirty’ first aspects, wherein the serpentinization reactions cause density changes from an initial density ranging from about 2.8 g / cm3to about 4.0 g / cm3to a final density ranging from about 2.0 g / cm3to about 3.0 g / cm3., with corresponding large volume changes.

[0325] A thirty’ third aspect can include the method of the thirty second aspect, wherein the initial density' ranges from about 3.2 g / cm3to about 3.6 g / cm3and the final density ranges from about 2.3 g / cm3to about 2.7 g / cm3.

[0326] A thirty fourth aspect can include the method of the any one of the twenty seventh to thirty third aspects, wherein the serpentinization reactions generate thermal energy ranging from about 4 MJ to about 10 MJ per cubic meter of serpentinite formation.

[0327] A thirty’ fifth aspect can include the method of the any one of the twenty seventh to thirty fourth aspects, wherein the thermal energy generation produces temperature increases ranging from about 150°C to about 400°C under adiabatic conditions.

[0328] A thirty sixth aspect can include the method of the any one of the twenty seventh toAtty. Docket No.: GE0001PCT_8022-00200 thirty fifth aspects, wherein the controlled conditions comprise an operating temperature in a range between 150°C to about 500°C, an operating pressure in a range of 50 bar to about 3000 bar; and a pH in a range from 6 to about 13.

[0329] A thi rt seventh aspect can include the method of the any one of the twenty sixth to thirty sixth aspects, wherein the hydrogen gas is produced in an amount of from about 0. 1 kT Ha / year per well to about 10 kT Ha / yr per well.

[0330] A thirty eighth aspect can include the method of the any one of the twenty sixth to thirty seventh aspects, wherein injecting the fluid comprises injecting the fluid using a pressure modulation to induce fracturing, wherein the fracturing forms a dense fracturing network

[0331] A thirty ninth aspect can include the method of the thirty eighth aspect, wherein the fluid is injected at a pressure of 95% of the breakdown pressure of the subsurface rock or less.

[0332] A fortieth aspect can include the method of the any one of the tw enty sixth to thirty ninth aspects, wherein injecting the fluid comprises injecting the fluid using a temperature modulation to induce fracturing, wherein the fracturing forms a dense fracturing network.

[0333] In a forty first aspect, a method for production of hydrogen from geological formations comprises: operating one or more wells in alternating injection and extraction cycles, wherein at least a first well of the one or more wells receives a fluid during the injection cycle, and wherein the first well extracts fluid in the extraction cycle; modulating pressure as a function of time P(t), temperature T(t) as a function of time, or both during the alternating injection and extraction cycles; controlling pH as a function of time pH(t) during the alternating injection and extraction cycles; and recovering one of more products during the extraction cycle.

[0334] A forty second aspect can include the method of the forty7first aspect, wherein the one or more wells are in fluid communication with a Fe2+-rich geological formation.

[0335] A forty third aspect can include the method of the forty second aspect, wherein recovering the one or more products comprises recovering hydrogen.

[0336] A forty' fourth aspect can include the method of any7one of the forty first to forty7third aspects, wherein recovering the one or more products comprises recovering amorphous silica, one or more rare earth minerals, or any combination thereof.

[0337] A forty fifth aspect can include the method of any one of the forty first to forty7fourth aspects, further comprising: controlling cycle durations in arange from about 0.5 hours to about 48 hours.

[0338] A forty sixth aspect can include the method of any one of the forty7first to forty fifth aspects, wherein modulating the pressure as the function of time P(t) ranges from about 50 bar to about 3000 bar.Atty. Docket No.: GE0001PCT_8022-00200

[0339] A forty seventh aspect can include the method of any one of the forty' first to forty sixth aspects, wherein controlling the pH as the function of time pH(t) ranges from about 2 to about 13, and wherein the pH is controlled by injecting acids comprising hydrochloric acid, sulfuric acid, organic acids, or any combination thereof, or bases comprising hydroxides.

[0340] A forty eighth aspect can include the method of any one of the forty' first to forty' seventh aspects, further comprising: controlling water-to-rock ratio WRR(t) ranging from about 0. 1 to about 5.0 during the alternating injection and extraction cycles.

[0341] A forty ninth aspect can include the method of any one of the forty first to forty eighth aspects, further comprising: injecting chemical additives selected from the group consisting of a carbonate, carbon dioxide, and a brine with controlled ionic composition.

[0342] A fiftieth aspect can include the method of the forty ninth aspect, wherein the carbonate comprises sodium bicarbonate (NaHCCfi) in concentrations ranging from about 0.01 M to about 1.0 M.

[0343] A fifty' first aspect can include the method of the forty ninth aspect, wherein the carbon dioxide is supercritical carbon dioxide (sCC ) at injection rates ranging from about 10 kg / hr to about 1000 kg / hr.

[0344] In a fifty second aspect, a system for integrated hydrogen production from geological formations comprises: at least one well configured for alternating injection and extraction cycles; a pressure controller capable of maintaining pressures ranging from about 50 bar to about 4000 bar; a chemical injection unit for delivering pH control agents and reaction enhancers; a temperature control system for maintaining operating temperatures ranging from about 150°C to about 500°C; a gas separation and recovery equipment for capturing hydrogen gas; and a control system configured to execute the alternating injection and extraction cycles.

[0345] A fifty third aspect can include the system of the fifty second aspect, further comprising: a fracture generation unit configured to control a brine composition and properties to create reaction-induced fracturing through controlled serpentinization reactions.

[0346] A fifty' fourth aspect can include the sy stem of the fifty' second or fifty third aspect, wherein the control system is configured to modulate pressure as a function of time P(t), pH as a function of time pH(t). or a water-to-rock ratio as a function of time WRR(t).

[0347] A fifty fifth aspect can include the system of any one of the fifty second to fifty' fourth aspects, wherein the control system is configured to: determine a porosity', permeability7, or both of a subsurface formation into which the at least one well extends, and control production of a fluid from the at least one well based on the porosity, permeability, or both.

[0348] A fifty sixth aspect can include the system of the fifty fifth aspect, further comprising:Atty. Docket No.: GE0001PCT_8022-00200 producing hydrogen in the fluid from the at least one well.

[0349] A fifty seventh aspect can include the system of any one of the fifty second to fifty sixth aspects, wherein the reactor is configured to receive a fluid from the at least one well and contact the fluid with a mineral in the reactor, wherein the reactor is configured to produce hydrogen, silica, metals, metal oxides, one or more rare earth elements, or any combination thereof.

[0350] While the invention has been particularly shown and described with reference to specific preferred embodiments, it should be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.

Claims

1. Atty. Docket No.: GE0001PCT_8022-00200CLAIMSWhat is claimed is:

1. A method for fracturing of a subsurface rock formation for hydrogen production, comprising: injecting a fluid comprising water into a subsurface rock formation under controlled conditions, wherein the fluid is injected at a pressure below the breakdown pressure of the subsurface rock; generating fractures in the subsurface rock; and recovering hydrogen gas produced by subsurface rock after the generation of the fractures.

2. The method of claim 1, wherein injecting the fluid comprises injecting the fluid to induce serpentinization reactions, wherein the subsurface rock formation comprises a Fe2+-containing mineral, wherein generating the fractures comprises generating reaction-induced fracturing through volume changes accompanying the serpentinization reactions, and wherein recovering the hydrogen gas comprises recovering the hydrogen gas produced by the serpentinization reactions.

3. The method of claim 2, wherein the Fe2+-containing mineral is selected from the group consisting of olivine, fayalite, grunerite, siderite, ferrosilite, and combinations thereof.

4. The method of claim 2, wherein the volume changes range from about 1 % to about 60%.

5. The method of claim 2, wherein the volume changes range from about 10% to about 50%.

6. The method of claim 2, wherein the serpentinization reactions generate crystallization pressures ranging from about 100 MPa to about 2000 MPa.

7. The method of claim 2, wherein the serpentinization reactions cause density changes from an initial densi ty ranging from about 2.8 g / cm3to about 4.0 g / cm3to a final density ranging from about 2.0 g / cm3to about 3.0 g / cm3., with corresponding large volume changes.

8. The method of claim 7. wherein the initial density ranges from about 3.2 g / cm3to about 3.6 g / cm3and the final density ranges from about 2.3 g / cm3to about 2.7 g / cm3.

9. The method of claim 2, wherein the serpentinization reactions generate thermal energy ranging from about 4 MJ to about 10 MJ per cubic meter of serpentinite formation.

10. The method of claim 2, wherein the thermal energy generation produces temperature increases ranging from about 150°C to about 400°C under adiabatic conditions.Atty. Docket No.: GE0001PCT_8022-0020011. The method of claim 2, wherein the controlled conditions comprise an operating temperature in a range between 150°C to about 500°C, an operating pressure in a range of 50 bar to about 3000 bar; and a pH in a range from 6 to about 13.

11. The method of claim 1, wherein the hydrogen gas is produced in an amount of from about 0. 1 kT H2 / year per well to about 10 kT Ha / yr per well.

12. The method of claim 1, wherein injecting the fluid comprises injecting the fluid using a pressure modulation to induce fracturing, wherein the fracturing forms a dense fracturing network13. The method of claim 12, wherein the fluid is injected at a pressure of 95% of the breakdown pressure of the subsurface rock or less.

14. The method of claim 1, wherein injecting the fluid comprises injecting the fluid using a temperature modulation to induce fracturing, wherein the fracturing forms a dense fracturing network.

15. A method for production of hydrogen from geological formations, the method comprising: operating one or more wells in alternating injection and extraction cycles, wherein at least a first well of the one or more wells receives a fluid during the injection cycle, and wherein the first well extracts fluid in the extraction cycle; modulating pressure as a function of time P(t), temperature T(t) as a function of time, or both during the alternating injection and extraction cycles; controlling pH as a function of time pH(t) during the alternating injection and extraction cycles; and recovering one of more products during the extraction cycle.

16. The method of claim 15, wherein the one or more wells are in fluid communication with a Fe2+-rich geological formation.

17. The method of claim 16, wherein recovering the one or more products comprises recovering hydrogen.

18. The method of claim 15. wherein recovering the one or more products comprises recovering amorphous silica, one or more rare earth minerals, or any combination thereof.

19. The method of claim 15, further comprising: controlling cycle durations in a range from about 0.5 hours to about 48 hours.

20. The method of claim 15, wherein modulating the pressure as the function of time P(t) ranges from about 50 bar to about 3000 bar.Atty. Docket No.: GE0001PCT_8022-0020021. The method of claim 15, wherein controlling the pH as the function of time pH(t) ranges from about 2 to about 13, and wherein the pH is controlled by injecting acids comprising hydrochloric acid, sulfuric acid, organic acids, or any combination thereof, or bases comprising hydroxides.

22. The method of claim 15, further comprising: controlling water-to-rock ratio WRR(t) ranging from about 0.1 to about 5.0 during the alternating injection and extraction cycles.

23. The method of claim 15, further comprising: injecting chemical additives selected from the group consisting of a carbonate, carbon dioxide, and a brine with controlled ionic composition.

24. The method of claim 23, wherein the carbonate comprises sodium bicarbonate (NaHCCh) in concentrations ranging from about 0.01 M to about 1.0 M.

25. The method of claim 23, wherein the carbon dioxide is supercritical carbon dioxide (sCOa) at injection rates ranging from about 10 kg / hr to about 1000 kg / hr.

26. A system for integrated hydrogen production from geological formations comprising: at least one well configured for alternating injection and extraction cycles; a pressure controller capable of maintaining pressures ranging from about 50 bar to about 4000 bar; a chemical injection unit for delivering pH control agents and reaction enhancers; a temperature control system for maintaining operating temperatures ranging from about 150°C to about 500°C; a gas separation and recovery equipment for capturing hydrogen gas; and a control system configured to execute the alternating injection and extraction cycles.

27. The system of claim 26, further comprising: a fracture generation unit configured to control a brine composition and properties to create reaction-induced fracturing through controlled serpentinization reactions.

28. The system of claim 26, wherein the control system is configured to modulate pressure as a function of time P(t), pH as a function of time pH(t). or a water-to-rock ratio as a function of time WRR(t).

29. The system of claim 26, wherein the control system is configured to: determine a porosity, permeability, or both of a subsurface formation into which the at least one well extends, and control production of a fluid from the at least one well based on the porosity, permeability, or both.

30. The system of claim 29, further comprising:Atty. Docket No.: GE0001PCT_8022-00200 producing hydrogen in the fluid from the at least one well.

31. The system of claim 26, further comprising a reactor, wherein the reactor is configured to receive a fluid from the at least one well and contact the fluid with a mineral in the reactor, wherein the reactor is configured to produce hydrogen, silica, metals, metal oxides, one or more rare earth elements, or any combination thereof.

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