End-to-end workflow for subsurface carbon dioxide storage site identification and evaluation

Abstract

Certain aspects of the disclosure relate to subsurface carbon dioxide storage. A method includes generating a geological basin model for a candidate region; simulating fluid flow of carbon dioxide for the candidate region using the geological basin model to identify structural trap(s) and / or carbon dioxide leakage pathway(s); generating suitability maps for the candidate region based on the structural trap(s) and / or carbon dioxide leakage pathway(s), wherein each suitability map corresponds to a candidate carbon dioxide storage site in the candidate region; selecting a candidate carbon dioxide storage site based on its generated suitability map; generating reservoir model realizations from at least the geological basin model for the candidate carbon dioxide storage site; for each reservoir model realization, performing storage and containment simulations to generate simulation results; and generating an evaluation score for the candidate carbon dioxide storage site based on the simulation results generated for each of the reservoir model realizations.

Description

END-TO-END WORKFLOW FOR SUBSURFACE CARBON DIOXIDE STORAGE SITE IDENTIFICATION AND EVALUATIONBACKGROUNDField

[0001] Aspects of the present disclosure relate to subsurface carbon dioxide storage.Description of Related Art

[0002] The stabilization and / or the reduction of atmospheric concentrations of greenhouse gases, particularly carbon dioxide (CO2), represents a key challenge in the attempt to mitigate climate change. In particular, carbon dioxide and other heat-trapping gases have molecular structures that enable them to absorb infrared radiation and re-radiate the infrared waves out in all directions - some into space and some back to Earth. The infrared radiation that is radiated back to Earth causes further warming at the surface and lower atmosphere.

[0003] Concern over environmental effects, including global warming, of carbon dioxide has resulted in significant efforts to reduce overall atmospheric carbon dioxide including, for example, through reforesting, increasing use of renewable energy sources, and the use of carbon capture, utilization, and storage (CCUS) processes. CCUS involves the capture of carbon dioxide prior to release into the atmosphere, generally from large point sources, such as power generation or industrial facilities that use either fossil fuels and / or biomass as fuel. The captured carbon dioxide is then compressed into a liquid state and transported by pipeline, ship, rail, or road tanker to be injected into deep geological formations, and thus permanently stored in depleted oil and gas reservoirs, coalbeds, or deep saline aquifers, where the geology is suitable for containment. An alternative to permanent storage is to re-use the captured carbon dioxide in industrial processes by converting it into, for example, plastics, concrete, or biofuel, to name a few. This prevents the carbon dioxide from entering the atmosphere, mitigating against carbon emissions from industry and heating and thereby reducing the contribution to global warming, ocean acidification, and other environmental effects. As such, CCUS has emerged as a critical mechanism in the global effort to combat climate change.Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO

[0004] Modeling and simulation of carbon dioxide storage is vital to understanding and optimizing CCUS implementations. For example, modeling and simulation may involve the use of advanced computational models and simulations to replicate the complex interactions that occur when carbon dioxide is injected deep underground for long-term storage. Modeling may include the collation of subsurface data into a three-dimensional representation of the subsurface geology and hydrogeology of a carbon dioxide storage site and surrounding area. Simulation may refer to the process of using specialized software to create quantitative predictions of the dynamic effects of carbon dioxide injection, including the migration of carbon dioxide and other formation fluids, pressure and temperature behavior, and the long-term behavior of injected carbon dioxide within the modeled volume.

[0005] Modeling and simulation of carbon dioxide storage not only enhance understanding of the subsurface behavior of existing CCUS implementations, but may also play an important role in designing efficient, effective, and safe CCUS systems. For example, in some cases, modeling and simulation of carbon dioxide storage may be used to identify and rank prospective carbon dioxide storage site(s) that meet various criteria to ensure the safe, sustainable, and economic storage of carbon dioxide over geological timescales.SUMMARY

[0006] One aspect provides a method of subsurface carbon dioxide storage site identification and evaluation. The method includes generating a geological basin model having a plurality of rock formations based on data associated with a candidate region for subsurface carbon dioxide storage; simulating fluid flow of carbon dioxide for the candidate region using the geological basin model to identify at least one of a structural trap or a carbon dioxide leakage pathway for the candidate region; generating a plurality of suitability maps for the candidate region based on at least one of the structural trap or the carbon dioxide leakage pathway, wherein each suitability map corresponds to a candidate carbon dioxide storage site among a plurality of candidate carbon dioxide storage sites in the candidate region; selecting a candidate carbon dioxide storage site from the plurality of candidate carbon dioxide storage sites in the candidate region based on the suitability map generated for the candidate carbon dioxide storage site; generating a plurality of reservoir model realizations from at least the geological basin model, wherein each reservoir model realization represents a subterranean environment for the candidate carbon dioxide storage site andClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO comprises at least a different facies distribution than a facies distribution associated with other reservoir model realizations of the plurality of reservoir model realizations; for each of the plurality of reservoir model realizations, performing a plurality of storage and containment simulations to generate simulation results; and generating an evaluation score for the candidate carbon dioxide storage site based on the simulation results generated for each of the plurality of reservoir model realizations, the evaluation score indicating a performance of the candidate carbon dioxide storage site with respect to the subsurface carbon dioxide storage.

[0007] Other aspects provide processing systems configured to perform the aforementioned methods as well as those described herein; non-transitory, computer-readable media comprising instructions that, when executed by a processors of a processing system, cause the processing system to perform the aforementioned methods as well as those described herein; a computer program product embodied on a computer readable storage medium comprising code for performing the aforementioned methods as well as those further described herein; and a processing system comprising means for performing the aforementioned methods as well as those further described herein.

[0008] The following description and the appended figures set forth certain features for purposes of illustration.DESCRIPTION OF THE DRAWINGS

[0009] The appended figures depict certain aspects and are therefore not to be considered limiting of the scope of this disclosure.

[0010] FIG. 1A depicts an example end-to-end workflow for subsurface carbon dioxide storage site identification and evaluation.

[0011] FIG. IB depicts example suitability maps generated for a candidate region for subsurface carbon dioxide storage.

[0012] FIG. 1C depicts example model resolution difference between a geological basin model associated with a candidate region and a geological model generated for a candidate carbon dioxide storage site in the candidate region.Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO

[0013] FIG. ID depicts example geological models associated with a candidate carbon dioxide storage site.

[0014] FIGS. 2A and 2B depict example simulation results generated as a result of performing a fluid flow simulation.

[0015] FIGS. 3 and 4 depict example simulation results generated as a result of performing a geomechanical simulation.

[0016] FIG. 5 depicts an example method of subsurface carbon dioxide storage site identification and evaluation.

[0017] FIG. 6 depicts an example processing system on which aspects of the present disclosure can be performed.

[0018] To facilitate understanding, identical reference numerals have been used, where possible, to designate identical elements that are common to the drawings. It is contemplated that elements and features of one embodiment may be beneficially incorporated in other embodiments without further recitation.DETAILED DESCRIPTION

[0019] Designing a CCUS system that provides effective storage of carbon dioxide over geological timescales, while also meeting commercial and safety targets, is a complex and multifaceted process. For example, a CCUS planning project may include a multitude of tasks from regional screening (e.g., a preliminary assessment of the suitability of a candidate region for subsurface carbon dioxide storage) to comprehensive containment and integrity assessment of specific candidate carbon dioxide storage sites (e.g., prospective sites for long-term subsurface carbon dioxide storage). Additionally, there are many factors that may need to be considered for each task. For example, technical performance factors such as, subsurface carbon dioxide storage capacity (e.g., the amount of carbon dioxide that may be stored), injectivity (e.g., the rate of carbon dioxide injection), and / or containment (e.g., the assurance that that injected carbon dioxide remains confined in pore spaces over time) may be considered for one or more tasks. Further, nontechnical requirements such as, for example, proximity of emitter(s) of carbon dioxide to a candidate carbon dioxide storage site, the presence and / or absence of existing transport network(s)Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO to a carbon dioxide storage site, the presence and / or absence of legacy well(s), monitorability (e.g., the ability to monitor carbon dioxide migration in the subsurface via one or more instruments), legal requirements and / or regulations, public opinion, proximity to sensitive area(s), site costs, and / or project economics may also be considered for one or more tasks of the CCUS planning project.

[0020] Conventionally, a siloed approach has been used for carrying out tasks of a CCUS planning project to identify, select, and evaluate candidate carbon dioxide storage sites for subsurface carbon dioxide storage. For example, (1) a first set of experts, decision makers, and / or stakeholders may be involved with a first task for regional screening and ranking, (2) a second set of experts, decision makers, and / or stakeholders may be involved with a second task for carbon dioxide storage site selection, and (3) a third set of experts, decision makers, and / or stakeholders may be involved with a third task for carbon dioxide storage site evaluation with respect to different carbon dioxide injection schedules. The myriad different parties involved, in combination with the detailed analyses needing to be performed and / or the number of factors needing to be considered at each task of the CCUS planning project, may lead to an inefficient decision making process. For example, the CCUS planning project, in some cases, may occur over many years before a decision is reached as to when, where, and / or how to store carbon dioxide in the subsurface. The conventional approach of considering independent aspects of a CCUS project at a time tends to make the process cumbersome and time-consuming.

[0021] Further, conventional decision making at each task in a CCUS project has been empirical in nature, as opposed to being data driven and / or based on the use of repeatable algorithms. For example, one conventional approach is to rely on a human’s knowledge for ad- hoc decision making at each task of a CCUS planning project. However, a human’s personal opinions, feelings, and / or experience with particular storage sites, locations, injectivity schedules, well placements, etc. may influence their decision making in sub-optimal ways. Conventional subjective methods are not repeatable or scalable, and in some cases, may lead to inconsistency across different CCUS projects.

[0022] Additionally, CCUS planning projects tend to deal with many unknowns and / or parameters, which may make the use of deterministic approaches unsuitable. For example, reservoirs (e.g., subsurface bodies of rock having sufficient porosity and permeability to store andClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO transmit fluids) considered for carbon dioxide storage may have complex geology and / or heterogeneity. In particular, heterogeneity in such reservoirs may be attributed to variable lithology, chemistry / mineralogy, pore types, pore connectivity, and / or variable lithofacies (simply referred to herein as “facies”). These inherent complexities may be related to processes controlling original deposition and subsequent diagenesis (e.g., refers to the physical and chemical processes that affect sedimentary materials after deposition and before metamorphism and between deposition and weathering). Such variability in these reservoirs may, in some cases, occur within small sections of the reservoir thereby making it difficult to (1) understand the heterogeneous nature of rock that may be used to store carbon dioxide and / or (2) understand the flow properties of carbon dioxide within the porous and / or fractured formations of the reservoirs. Accordingly, the sheer number of variables and facies to consider, along with their corresponding variability, especially over short length scales in a reservoir, may make the identification and evaluation of carbon dioxide storage sites for potential carbon dioxide storage a technically challenging task.

[0023] Thus, for at least the reasons described above, conventional methods for identifying, selecting, and evaluating candidate carbon dioxide storage sites for subsurface carbon dioxide storage are not effective and technically deficient.

[0024] Embodiments described herein overcome the aforementioned technical problems and improve upon the state of the art by providing an end-to-end integrated workflow (simply referred to herein as the “workflow”) for subsurface carbon dioxide storage site identification and evaluation. The workflow may encompass various aspects of CCUS planning by integrating specific methodologies, models, and / or technologies to provide a comprehensive and consistent framework for CCUS planning, decision making, and execution for decarbonization efforts. For example, the workflow may combine (1) geological basin model construction, (2) regional screening, (3) carbon dioxide migration and leakage pathway identification techniques, (4) carbon dioxide storage site selection methodology, (5) dynamic geological modeling, (6) dynamic fluid flow modeling, and (7) and geomechanical modeling for assessing the viability, effectiveness, and / or risk of subsurface carbon dioxide storage and containment at candidate carbon dioxide storage sites. This workflow may also enable a vast amount of data to be harnessed for carbon dioxide storage site identification and evaluation, such as from public sources (e.g., world maps, public repositories, multi-client seismic data, well data, etc.) and / or including proprietary dataClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO(e.g., two-dimensional (2D) seismic lines data, three-dimensional (3D) seismic data, well log data, core data (e.g., core data may be proprietary to a company that “owns” the rock sample and has paid for a laboratory experiment), etc.).

[0025] The integration of end-to-end modeling and techniques in the workflow beneficially offers a robust approach to address multi-disciplinary challenges associated with conventional CCUS planning projects, as described above. Specifically, the workflow extracts insights from data sourced from various outlets to construct models and perform simulations that may be used to make informed decisions about subsurface carbon dioxide storage. As such, the workflow overcomes technical problems associated with conventional CCUS planning approaches that rely on the subjective expertise and knowledge of experts, stakeholders, and / or specialized teams to perform ad-hoc decision making during CCUS planning projects. By instead relying on integrated models and simulations, the workflow provides a streamlined and analytical approach to CCUS planning, decision making, and execution that may be repeated and applied to various scenarios and / or data. Accordingly, the workflow beneficially is an efficient, consistent, and repeatable workflow that improves upon the state of the art.

[0026] Further, the workflow described herein is beneficially capable of dealing with the complex geology and / or heterogeneity of reservoirs, unlike conventional approaches. For example, the workflow may automatically generate a plurality of reservoir model realizations, wherein each reservoir model realization represents a subterranean environment for a candidate carbon dioxide storage site and comprises at least a different facies distribution than a facies distribution associated with another reservoir model realization generated for the same candidate carbon dioxide storage site. Storage and containment simulations may be run for each reservoir model realization to holistically evaluate a performance of the candidate carbon dioxide storage site with respect to carbon dioxide storage and containment. Using this approach for site evaluation has the beneficial technical effect of improving capacity to handle the uncertainty associated with the subsurface geology of various reservoirs considered for carbon dioxide storage. For example, using the workflow described herein to generate multiple reservoir model realizations for a same candidate carbon dioxide storage site helps to illustrate the likely range of behavior of the site with respect to carbon dioxide storage and containment. Instead of evaluating the performance of the carbon dioxide storage site using a single estimate of the subsurface geology and / or itsClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO petrophysical properties (e.g., a single reservoir model realization), many different estimates of feasible subsurface geology and / or its petrophysical properties may be analyzed. As such, candidate carbon dioxide storage site evaluation may be more accurate and provide a more complete view of possible behavior of carbon dioxide, should it later be injected and stored at the candidate carbon dioxide storage site for long-term storage.Example End-to-End Workflow for Carbon Dioxide Storage Site Identification and Evaluation

[0027] FIG. 1A depicts an example end-to-end workflow 100 (simply referred to herein as “workflow 100”) for subsurface carbon dioxide storage site identification and evaluation. As shown in FIG. 1A, workflow 100 includes, in this example, (1) geological basin model generation and carbon dioxide storage site selection at 140, (2) detailed geological modeling at 142, (3) dynamic reservoir model realizations generation at 144, (4) flow and geomechanical coupling simulation at 146, and (5) evaluation score generation at 148. Workflow 100 may be integrated such that a prior step in the workflow informs a next step in the workflow to provide a comprehensive design for subsurface carbon dioxide storage site identification and evaluation. As used herein, a basin may refer to a depression in the crust of the Earth, caused by plate tectonic activity and / or subsidence, in which sediments accumulate. Further, as described herein, a reservoir may refer to a subsurface body of rock having sufficient porosity and / or permeability to store and transmit fluids, such as carbon dioxide.

[0028] Geological basin model generation, at 140 (which also includes carbon dioxide storage site selection), includes generating a geological basin model 102 (a larger depiction of the example geological basin model 102 provided in FIG. 1A is provided in FIG. IB). For example, geological basin model generation, at 140, leverages a combination of (1) published data, such as data sourced from national repositories, and / or (2) proprietary data to construct a geological basin model 102. Geological basin model 102 may be generated as a pressure-temperature-driven basin model in some examples. As an illustrative example, a geological basin model 102 may be generated to have a plurality of rock formations based on historical data associated with the Sleipner gas field, which is a candidate region for subsurface carbon dioxide storage in the North Sea having approximately twenty years of active carbon dioxide injection.Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO

[0029] The published data and / or proprietary data used to generate geological basin model 102 may include well log data 120, 2D seismic lines data 122, 3D seismic data 124, core data 126, drilling data 128, and geological maps 130 (e.g., as raster images) (as shown in FIG. 1A), among others, associated with a candidate region for subsurface carbon dioxide storage. Well log data 120 may include recorded physical, acoustic, and / or electrical properties of rocks penetrated by a well (e.g., including, for example, exploration, plugged, and / or abandoned wells). Example well log data 120 may include exploration well data and / or well logs made available by the Norwegian Petroleum Directorate (NPD). 2D seismic lines data 122 may include a plurality of 2D seismic lines acquired individually, while 3D seismic data 124 may include multiple sets of numerous closely-spaced seismic lines that provide a high spatially sampled measure of subsurface reflectivity. Example 2D seismic lines data 122 may include seismic data also made available by the NPD. 3D seismic data 124 may provide detailed information about fault distribution (e.g., where a fault is a break or planar surface in brittle rock across which there is observable displacement) and / or subsurface structure(s) for the candidate region. Core data 126 may include direct measurements of rock properties, such as porosity, permeability, saturation, and / or mineralogy, for the candidate region. In certain aspects, core data 126 may be used to calibrate and / or validate other sources of information, such as well log data 120, 2D seismic lines data 122, and / or 3D seismic data 124. Drilling data 128 may include information that is collected during drilling processes(s). For example, drilling data 128 may include data collected by sensor(s) on a drilling rig, which captures real-time details such as depth, mud characteristics, the depth at which drilling equipment is located, etc. Example maps and images used to generate geological basin model may include maps and images from “The Millennium Atlas” book published by the Geological Society of London.

[0030] In certain aspects, geological basin model generation at 140 includes contour digitization of horizon(s) (e.g., a surface in or of rock, or a distinctive layer of rock that might be represented by a reflection in 2D seismic lines data 12 and / or 3D seismic lines data 124) and / or faults from maps, well tie, and the creation of geological basin model 102 (e.g., a large 3D regional model). In certain aspects, the use of gamma ray data may also aid in producing discrete facies models, which may then be subsequently transferred to the geological basin model 102. For example, gamma ray well log data may be propagated in a 3D geocellular basin model to createClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO the discrete facies models, which are subsequently transferred to the geological basin model 102. Gamma ray is a gross indicator for sand or shale lithology. Thus, generating a 3D property that shows its distribution may provide a “gross” indication of the location of sand or shale.

[0031] Geological basin model 102 may include multiple candidate carbon dioxide storage sites. A candidate carbon dioxide storage site may be a prospective site for injecting and storing carbon dioxide for decarbonization, for example. Thus, carbon dioxide storage site selection (also referred to as “regional site identification”), also at 140 in FIG. 1A, may include selecting, for evaluation, a candidate carbon dioxide storage site from multiple carbon dioxide storage sites in geological basin model 102.

[0032] In certain aspects, carbon dioxide storage site selection, at 140, includes (1) simulating fluid flow of carbon dioxide for the candidate region using geological basin model 102 to identify structural trap(s) and / or carbon dioxide leakage pathway(s) for the candidate region. Further, in certain aspects, carbon dioxide storage site selection, at 140, includes (2) generating suitability maps for two or more candidate carbon dioxide storage sites in the candidate region based on the identified structural trap(s) and / or carbon dioxide leakage pathway(s) and (3) selecting a candidate carbon dioxide storage site from the candidate carbon dioxide storage sites in the candidate region based on the suitability map generated for the selected candidate carbon dioxide storage site.

[0033] For example, structural maps and / or lithology drivers may be obtained by previous geological studies. The basin simulator may use (1) rock properties from the structural maps and / or lithology drivers and (2) invasion percolation techniques to simulate realistic fluid flow of carbon dioxide through porous media in geological basin model 102. This simulation may allow for the identification and quantification of structural trap(s) and / or carbon dioxide leakage pathway(s) for the candidate region represented by geological basin model 102.

[0034] As an illustrative example, distribution maps of petrophysical properties, such as gamma ray, porosity, and / or permeability, may be created. These petrophysical properties may be derived from well data 120 (e.g., well log data) and used to propagate values into a 3D basin model. Average maps for each of these petrophysical properties may then be created within the reservoir interval. This data may be shared with a basin simulator to form the basis of the basin analysis.Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO

[0035] As used herein, a leakage pathway may include a leaky fault and / or fracture that provides a pathway for carbon dioxide to migrate and reduces the effectiveness of storage. Alternatively, a structural trap may be a trapping mechanism consisting of geologic structures in deformed strata, such as faults and / or folds (e.g., a wave-like geologic structure that forms when rocks deform by bending instead of breaking under compressional stress), whose geometries permit retention of fluid, such as carbon dioxide. In certain aspects, the structural trap(s) in geological basin model 102 may be identified using 2D seismic lines data 122 and / or 3D seismic data 124.

[0036] Carbon dioxide storage suitability maps (simply referred to herein as “suitability maps”) may be generated for the candidate region based on the identified structural trap(s) and / or carbon dioxide leakage pathway(s) identified for the candidate region. Further, in certain aspects, the suitability maps may be generated based on properties, such as pressure, temperature, top seal capacity, and / or capillary pressure, determined at a basin scale for the candidate region. For example, geological basin model 102 may be integrated with facies maps (e.g., high-resolution facies maps) and / or lithology distribution models to determine one or more of these parameters. The facies map may show the distribution of different types of rock attributes and / or facies occurring within the candidate region (e.g., for which geological basin model 102 is created). Volume conversion into grids and maps may also be used to generate the suitability maps. This may include volumes such as basin and rock properties (e.g., temperature, pressure, porosity, permeability, capillary pressure, etc.), as well as volumes representing the presence of different carbon dioxide trapping mechanisms.

[0037] FIG. IB depicts example suitability maps 152( 1 )-(4) (collectively referred to herein as “suitability maps 152” and individually referred to herein as “suitability map 152”) generated for the candidate region modeled by geological basin model 102. As shown in geological basin model 102, the candidate region may include a plurality of candidate carbon dioxide storage sites 154(1)- (4) (collectively referred to herein as “candidate carbon dioxide storage sites 154” and individually referred to herein as “candidate carbon dioxide storage site 154”). Each candidate carbon dioxide storage site 154 may correspond to a reservoir where carbon dioxide may be injected and stored. To identify a candidate carbon dioxide storage site 154 most suitable for injection and storage (e.g., and also based on one or more limitations and / or constraints, as described in detail below), aClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO suitability map 152 may be generated for each candidate carbon dioxide storage site 154. For example, suitability map 152(1) may be generated for candidate carbon dioxide storage site 154(1), suitability map 152(2) may be generated for candidate carbon dioxide storage site 154(2), suitability map 152(3) may be generated for candidate carbon dioxide storage site 154(3), and suitability map 152(4) may be generated for candidate carbon dioxide storage site 154(4). Although only four suitability maps 152 are generated for candidate carbon dioxide storage sites 154 in the example illustrated in FIG. IB, in some other examples, more or less suitability maps may be generated for more or less candidate carbon dioxide storage sites in a candidate region.

[0038] As shown in FIG. IB, each suitability map 152 may estimate a suitability of the corresponding candidate carbon dioxide storage site 154, in the candidate region, to store carbon dioxide, thereby offering valuable insights for sustainable carbon sequestration strategies. For example, areas with a first pattern, in each suitability map 152, are associated with areas in the candidate carbon dioxide storage site 154 corresponding to the respective suitability map 152 where there exists a high success potential for carbon dioxide storage. For example, areas identified as high success potential areas for carbon dioxide storage may be areas that provide permeability, porosity, facies, structural traps, etc. useful for containing injected carbon dioxide for long-term storage. Alternatively, areas with a second pattern, in each suitability map 152, are associated with areas, in the candidate carbon dioxide storage site 154 corresponding to the respective suitability map 152, where there exists a low success potential for carbon dioxide storage.

[0039] Suitability maps 152 may be used to identify modeling target(s) for detailed geological modeling, simulation, and evaluation. In particular, one or more candidate carbon dioxide storage sites 154 may be selected, among the plurality of candidate carbon dioxide storage sites 154 in the candidate region, based on the suitability maps 152 generated for sites 154. In certain aspects, a user may perform the selection using a visualization of the suitability maps 152 (e.g., the system may cause the suitability maps 152 to be displayed to the user for selection). In the example illustrated in FIG. 1A and IB, a single storage site, e.g., candidate carbon dioxide storage 154(1), is selected for further detailed geological modeling (e.g., at 142 in FIG. 1A), simulation (e.g., at 142 in FIG. 1A), and evaluation (e.g., at 148 in FIG. 1A) (e.g., evaluation of the storage site with respect to carbon dioxide storage and containment). Although this example illustrates the selectionClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO of one only candidate carbon dioxide storage site 154, in some other examples, multiple candidate carbon dioxide storage sites may be selected.

[0040] In certain aspects, selecting the candidate carbon dioxide storage site 154 from the plurality of candidate carbon dioxide storage sites 154 in the candidate region is further based on one or more constraints. Example constraint(s) may include a location constraint, a depth constraint, a porosity constraint, a pressure constraint, a rock failure constraint, a fault stability bound, and / or a fracture stability bound, to name a few. For example, a location constraint may indicate a maximum distance allowed between a candidate carbon dioxide storage site 154 and an existing well (e.g., a legacy well) to avoid the additional expense of needing to implement a well for carbon dioxide injection at the carbon dioxide storage site. Based on this location constraint, only carbon dioxide storage sites 154 with a distance to a well below or equal to the maximum distance may be considered for selection.

[0041] Detailed geological modeling, at 142 in FIG. 1A, includes generating a plurality of geological models 104(l)-(x) (collectively referred to herein as “geological models 104” and individually referred to herein as “geological model 104”) for the selected candidate carbon dioxide storage site 154(1). For example, the geological models 104, created at 142, may represent a subterranean environment for the candidate carbon dioxide storage site 154(1). Further, each geological model 104 may include at least a different facies distribution than a facies distribution associated with other geological models 104 created for the candidate carbon dioxide storage site 154(1) (e.g., each geological model 104’s facies distribution may be different). As such, geological models 104 may provide various realizations that are feasible for the static, geological environment of the candidate carbon dioxide storage site 154(1). Geological models 104 may provide the framework for simulating material flow of fluid, such as carbon dioxide.

[0042] To create geological models 104, detailed geological modeling, at 142, may include transitioning from a basin scale characterization to a reservoir scale characterization for candidate carbon dioxide storage site 154(1). In some cases, this transition may include refining the data associated with geological basin model 102 and further increasing the resolution of data for the candidate carbon dioxide storage site 154(1).

[0043] For example, data (e.g., well log data 120, 2D seismic lines data 122, 3D seismic data 124, core data 126, drilling data 128, and geological maps 130) used to generate geological basinClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO model 102 may include data for specific areas of interest in the candidate region (e.g., such as at the location of a well within the candidate region), with approximately 10 meter (m) and 15 centimeter (cm) resolution. Geological structures, however, may exist at sub-centimeter scales. For example, fine-scale cross and planar bedding in sedimentary strata (layers) may provide important routes for fluid flow and storage. To capture millimeter-scale variations of the subsurface for better evaluation of the subsurface for carbon dioxide storage and containment, high resolution geological models 104 may be generated at 142.

[0044] FIG. 1C depicts example model resolution difference between a geological basin model (e.g., such as geological basin model 102 in FIG. 1A) and a geological model (e.g., such as geological model 104(1), generated for candidate carbon dioxide storage site 154(1), in FIG. 1A). In particular, higher resolution data may be used to generate the geological model as compared to data used to generate the geological basin model. Thus, a number of grid cells 166 in the geological model may be greater than a number of grid cells 164 in the geological basin model. For example, as shown, data represented as four grid cells 164 in the geological basin model (e.g., shown at 160 in FIG. 1C) may be represented as sixty -four grid cells 166 in the geological basin model (e.g., shown at 162 in FIG. 1C). Data gathered for each well in each grid cell 164 may be averaged for each grid cell 164 (e.g., to account for sparse data collected for the candidate region). This data may then be augmented and enhanced when generating the geological model such that the model resolution is increased and data variability is better captured for the represented candidate carbon dioxide storage site (e.g., due to increased resolution of data). For example, data averaged for a single grid cell 164 in the geological basin model may be separated into sixteen grid cells 166, each with its own data average, in the geological model. In certain aspects, to enhance the available data, existing information is augmented and / or machine learning techniques are employed to map lithological distributions.

[0045] FIG. ID depicts example geological models 104(l)-(6), associated with candidate carbon dioxide storage site 154(1), and generated during detailed geological modeling in FIG. 1A at 142. Although FIG. ID depicts only six geological models 104 being generated for candidate carbon dioxide storage site 154(1), in some other examples, more or less geological models 104 may be generated. Each geological model 104 may represent a different realization of candidate carbon dioxide storage site 154(1). For example, each geological model 104 may have a differentClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO facies distribution possible for candidate carbon dioxide storage site 154(1). Further, in certain aspects, each geological model have different petrophysical properties possible for candidate carbon dioxide storage site 154(1). For example, in certain aspects, permeability is a useful discriminator among geological models 104.

[0046] In certain aspects, lithology discriminators and / or cutoffs are applied to determine a net-to-gross lithological distribution for candidate carbon dioxide storage site 154(1). The lithological distribution may include information about shale and sand distributions for candidate carbon dioxide storage site 154(1). In certain aspects, known porosity and / or permeability values are further used to discriminate between different geological zones of candidate carbon dioxide storage site 154(1). In certain aspects, analogues and additional data are amalgamated to create geological models 104. For example, an analogue, or trend model, may be imposed from other “known” data, such as other published study(ies) and / or measured field information. Trend data from this trend model may be used to overprint and / or supersede a distribution created by the 3D property modelling.

[0047] In FIG. 1 A, after detailed geological modeling is performed at 142 to create geological models 104(l)-(x), dynamic reservoir model realization generation is performed, at 144, to create reservoir model realizations 108(l)-(z) (collectively referred to herein as “reservoir model realizations 108” and individually referred to herein as ‘reservoir model realization 108”). A reservoir model realization 108 may be created by incorporating fluid physics data and / or rock physics data with a geological model 104. The fluid physics data may include carbon dioxide solubility and phase behavior information. Incorporation of such physics data may result in the formation of a dynamic model, e.g., a reservoir model realization 108. In certain aspects, one reservoir model realization 108 is created for each geological model 104 (as shown in FIG. 1A). In certain aspects, multiple reservoir model realizations 108 are created for each geological model 104. For example, there may exist a set of static uncertainty, which may lead to the generation of the geological models 104. Further, dynamic uncertainty elements may be added to each of the geological models 104, which may then create multiple (different) reservoir model realizations 108.

[0048] Flow and geomechanical coupling simulation (simply referred to herein as “dynamic simulation”), at 146, may include performing a plurality of storage and containment simulationsClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO(e.g., shown as simulations 110 in FIG. 1A) to generate simulation results for each reservoir model realization 108. For example, dynamic simulation, at 146, may be used for injection planning and dynamic modeling with a specific focus on capacity assessment, plume migration, and storage mechanisms for candidate carbon dioxide storage site 154(1).

[0049] For example, for dynamic simulation at 146, a number, / / , simulations 110 (e g., where n is an integer greater than or equal to two) may be performed on each reservoir model realization 108 to generate simulation results for each reservoir model realization 108. A first simulation 110(1) may include a fluid flow simulation simulating, for example, the flow of carbon dioxide over multiple time periods. For example, fluid flow simulation may be performed to simulate carbon dioxide flow at carbon dioxide storage site 154(1) for a first time period, a second time period, a third time period, etc. (e.g., simulate carbon dioxide flow over a first year after injection, over a second year after injection, over a third year after injection, etc.). Simulation results generated as a result of performing such simulations may include information about predicted pressure and saturation behavior of candidate carbon dioxide storage site 154(1) over time. Through multiple flow simulations (e.g., numerical simulations, which may span several centuries), plume migration patterns for the candidate carbon dioxide storage site 154(1), and specifically for each reservoir model realization 108 generated for candidate carbon dioxide storage site 154(1), may be realized. Further, storage capacity, based on different trapping mechanisms, may be evaluated for each reservoir model realization 108 to better understand (and remove uncertainty surrounding) storage capacity of candidate carbon dioxide storage site 154(1). The storage capacity realized for candidate carbon dioxide storage site 154(1) may provide insight into the containment capability and long-term safety risk of storing carbon dioxide at carbon dioxide storage site 154(1).

[0050] FIGS. 2A and 2B depict example simulation results generated as a result of performing a fluid flow simulation. For example, FIG. 2A depicts an example visualization generated for display after performing the fluid flow simulation to represent a full-field view of dissolved carbon dioxide at the end of a monitoring period. FIG. 2B depicts example visualizations generated for display after performing the fluid flow simulation to represent the impact of grid resolution around a well. In particular, in a numerical simulation, results accuracy may be dependent on the grid resolution, that is, the discretization of the numerical mesh that is provided to the simulator. ForClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO example, an area to be simulated may be divided into blocks of 25 meters x 25 meters x 1 meters. The results obtained from this simulation may provide a more accurate representation than if the area is divided into blocks of lower resolution, such as 250 meters x 250 meters x 10 meter bocks. There is, however, a higher computational cost to using blocks of higher resolution, specifically, the use of higher resolution blocks may result in a larger number of grid cells and thus more computations. By using a performant numerical simulator that can handle such complexity, however, higher resolutions may be obtainable to thereby make more informed decisions.

[0051] A second simulation 110(2), for dynamic simulation at 146 in FIG. 1A, may include a geomechanical simulation. The geomechanical simulation may be performed to assess the impact of fluid flow on time-dependent rock structure degradation and containment risk at the candidate carbon dioxide storage site 154(1), and more specifically for each reservoir model realization 108 generated for candidate carbon dioxide storage site 154(1). For example, simulation results for different time periods generated based on performing first simulation 110(1), e.g., the fluid flow simulation, may be used as input into performing second simulation 110(2), e.g., the geomechanical simulation. In certain aspects, the geomechanical simulation is used to evaluate pressure build-up implications on fault stability and cap rock integrity, including quantifying rock failure and mechanical thresholds, for each reservoir model realization 108 of candidate carbon dioxide storage site 154(1). In certain aspects, the geomechanical simulation is used to understand fault criticality and risk indexes for each reservoir model realization 108 of candidate carbon dioxide storage site 154(1).

[0052] FIGS. 3 and 4 depict example simulation results generated as a result of performing a geomechanical simulation. For example, FIG. 3 depicts an example visualization generated for display after performing the geomechanical simulation to represent minimum horizontal stress variability through depth at candidate carbon dioxide storage site 154(1). FIG. 4 depicts an example visualization generated for display after performing the geomechanical simulation to represent the fault uncertainty at candidate carbon dioxide storage site 154(1).

[0053] In certain aspects, simulation results generated as a result of performing second simulation 110(2) (e.g., the geomechanical simulation) may be used to refine the first simulation 110(1) (e.g., the fluid flow simulation). In certain aspects, simulation results generated as a resultClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO of performing second simulation 110(2) (e.g., the geomechanical simulation) may be used as input into another simulation 110.

[0054] In certain aspects, simulations 1 10( 1 )-( / / ) are performed to evaluate different candidate well placements 132 for carbon dioxide injection at candidate carbon dioxide storage site 154(1). In certain aspects, simulations 110(l)-(n) are performed to evaluate different candidate injection schedules 134 for carbon dioxide injection at candidate carbon dioxide storage site 154(1). In certain aspects, simulations 110( 1 )-( / ?) are performed to evaluate the storage and containment of carbon dioxide at candidate carbon dioxide storage site 154(1) based on one or more operating constraints 136. Example operating constraints 136 may include a maximum carbon dioxide injection rate, a minimum carbon dioxide injection rate, a fluid containment risk threshold, a compaction threshold, a subsidence threshold, and / or a maximum risk of affecting one more adjacent reservoirs allowed during operation, to name a few.

[0055] After performing simulations 110(l)-(z?), workflow 100 proceeds to evaluation score generation at 148 in FIG. 1A. Evaluation score generation, at 148, may include generating an evaluation score 149 for candidate carbon dioxide storage site 154(1) based on the simulation results generated for each of reservoir model realization 108 (and based on each candidate well placement 132, each candidate injection schedule, and / or different operating constraints 136). Evaluation score 149 may indicate a performance of candidate carbon dioxide storage site 154(1) with respect to subsurface carbon dioxide storage and containment.

[0056] In certain aspects, evaluation score 149, generated for candidate carbon dioxide storage site 154(1), may be generated for display on a computing device. Display of the evaluation score may allow a user to determine whether to proceed with using this candidate carbon dioxide storage site 154(1) for CCUS or not. In certain other aspects, evaluation score 149 is compared against a threshold to determine if the candidate carbon dioxide storage site 154(1) is suitable for long-term carbon dioxide storage and containment. A message may be generated for display on a computing device to indicate whether the evaluation score is above or below the threshold.

[0057] In certain aspects, workflow 100 is performed to generate evaluation scores for multiple candidate carbon dioxide storage sites 154. One or more of these candidate carbon dioxide storage sites 154 may be selected for CCUS based on evaluation score(s) for these candidate carbonClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO dioxide storage site(s) 154 being greater than evaluation scores for other candidate carbon dioxide storage sites 154, also evaluated according to workflow 100.

[0058] Workflow 100 beneficially provides a robust and thorough framework useful for the identification and evaluation of subsurface carbon dioxide storage sites for CCUS planning projects. Specifically, workflow 100 integrates multidisciplinary models and methodologies to enable a better understanding of a carbon dioxide storage site for long-term carbon dioxide storage and containment. This provides a technical benefit over conventional methods for subsurface carbon dioxide storage site identification and evaluation, which are often tackled by focusing on independent aspects one at a time (e.g., focusing only on basin modeling at a single time, focusing only on geological modeling at a single time, etc.), thereby making the integration of knowledge available from independent aspects for improved decision making cumbersome.

[0059] It is noted that FIGS. IB, ID, 2A, 2B, 3, and 4 represent data specific to Utsira in Norway. For example, the Utsira data used to create these figures includes data under the Norwegian License for Open Government Data (NLOD) distributed by the NPD. Although Utsira data is used herein to create FIGS. IB, ID, 2A, 2B, 3, and 4, it is noted that Utsira data represents only one example type of data, and in some other examples, other data types may be considered.Example Operations for Subsurface Carbon Dioxide Storage Site Identification and Evaluation

[0060] FIG. 5 shows a method 500 of subsurface carbon dioxide storage site identification and evaluation.

[0061] Method 500 begins at block 505 with generating a geological basin model having a plurality of rock formations based on data associated with a candidate region for subsurface carbon dioxide storage.

[0062] Method 500 then proceeds to block 510 with simulating fluid flow of carbon dioxide for the candidate region using the geological basin model to identify at least one of a structural trap or a carbon dioxide leakage pathway for the candidate region.

[0063] Method 500 then proceeds to block 515 with generating a plurality of suitability maps for the candidate region based on at least one of the structural trap or the carbon dioxide leakage pathway, wherein each suitability map corresponds to a candidate carbon dioxide storage site among a plurality of candidate carbon dioxide storage sites in the candidate region.Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO

[0064] Method 500 then proceeds to block 520 with selecting a candidate carbon dioxide storage site from the plurality of candidate carbon dioxide storage sites in the candidate region based on the suitability map generated for the candidate carbon dioxide storage site.

[0065] Method 500 then proceeds to block 525 with generating a plurality of reservoir model realizations from at least the geological basin model, wherein each reservoir model realization represents a subterranean environment for the candidate carbon dioxide storage site and comprises at least a different facies distribution than a facies distribution associated with other reservoir model realizations of the plurality of reservoir model realizations.

[0066] Generating multiple realizations subterranean environment for the candidate carbon dioxide storage site, at block 525, beneficially helps to (1) accelerate characterization of the candidate carbon dioxide storage site during storage and containment simulations, at block 530 below, for CCUS planning and (2) enable a better understanding of uncertainties for the storage site.

[0067] Method 500 then proceeds to block 530 with, for each of the plurality of reservoir model realizations, performing a plurality of storage and containment simulations to generate simulation results.

[0068] Method 500 then proceeds to block 535 with generating an evaluation score for the candidate carbon dioxide storage site based on the simulation results generated for each of the plurality of reservoir model realizations, the evaluation score indicating a performance of the candidate carbon dioxide storage site with respect to the subsurface carbon dioxide storage.

[0069] Use of method 500 provides an end-to-end mechanism for reliable, accurate, repeatable, and efficient subsurface carbon dioxide storage site identification and evaluation at least due to the integration of various data sources as well as multi-disciplinary methodologies and models. Further, this end-to-end mechanism for characterizing the subsurface beneficially ensures that critical aspects are addressed early in the modelling stages for subsurface characterization, thereby allowing for the identification, early in a CCUS planning project, of any potential block and counter-productive practices. As such, efficiency and cross-discipline communication may be increased.Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO

[0070] In certain aspects, a resolution of each of the plurality of reservoir model realizations is greater than a resolution of the geological basin model for the candidate carbon dioxide storage site.

[0071] In certain aspects, block 530 includes performing a flow simulation and a geomechanical simulation for a plurality of time periods.

[0072] In certain aspects, performing the plurality of storage and containment simulations is based on at least one of fluid physics data or rock physics data.

[0073] In certain aspects, the evaluation score for the candidate carbon dioxide storage site indicates the performance of the candidate carbon dioxide storage site with respect to the subsurface carbon dioxide storage for at least one of: one or more candidate well placements for carbon dioxide injection at the candidate carbon dioxide storage site; one or more carbon dioxide injection schedules for the carbon dioxide injection at the candidate carbon dioxide storage site; or one or more operating constraints.

[0074] In certain aspects, the operating constraints comprise at least one of: a maximum carbon dioxide injection rate; a minimum carbon dioxide injection rate; a fluid containment risk threshold; a compaction threshold; a subsidence threshold; or a maximum risk of affecting one more adjacent reservoirs during operation.

[0075] In certain aspects, simulating the fluid flow of the carbon dioxide for the candidate region using the geological basin model is based on buoyancy data for carbon dioxide under pressure and temperature conditions associated with the candidate region.

[0076] In certain aspects, selecting the candidate carbon dioxide storage site from the plurality of candidate carbon dioxide storage sites in the candidate region is based on one or more constraints comprising at least one of a location constraint, a depth constraint, a porosity constraint, a pressure constraint, a rock failure constraint, a fault stability bound, or a fracture stability bound.

[0077] In certain aspects, data associated with the candidate region comprises at least one of: well log data; seismic data; 2D seismic lines; core data; or drilling data.

[0078] In certain aspects, method 500, or any aspect related to it, may be performed by a processing system, such as processing system 600 of FIG. 6, which includes various componentsClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO operable, configured, or adapted to perform the method 500. Processing system 600 is described below in further detail.

[0079] Note that FIG. 5 is just one example of a method, and other methods including fewer, additional, or alternative operations are possible consistent with this disclosure.Example Processing System for Fault Seal Analysis

[0080] FIG. 6 depicts an example processing system 600 configured to perform various aspects described herein, including, for example, method 500 as described above with respect to FIG. 5

[0081] Processing system 600 is generally an example of an electronic device configured to execute computer-executable instructions, such as those derived from compiled computer code, including without limitation personal computers, tablet computers, servers, smart phones, smart devices, wearable devices, augmented and / or virtual reality devices, and others.

[0082] In the depicted example, processing system 600 includes one or more processors 602, one or more input / output devices 604, one or more display devices 606, one or more network interfaces 608 through which processing system 600 is connected to one or more networks (e.g., a local network, an intranet, the Internet, or any other group of processing systems communicatively connected to each other), and computer-readable medium 670. In the depicted example, the aforementioned components are coupled by a bus 610, which may generally be configured for data exchange amongst the components. Bus 610 may be representative of multiple buses, while only one is depicted for simplicity.

[0083] Processor(s) 602 are generally configured to retrieve and execute instructions stored in one or more memories, including local memories like computer-readable medium 670, as well as remote memories and data stores. Similarly, processor(s) 602 are configured to store application data residing in local memories like the computer-readable medium 670, as well as remote memories and data stores. More generally, bus 610 is configured to transmit programming instructions and application data among the processor(s) 602, display device(s) 606, network interface(s) 608, and / or computer-readable medium 670. In certain embodiments, processor(s) 602 are representative of one or more central processing units (CPUs), graphics processing unit (GPUs), tensor processing unit (TPUs), accelerators, and other processing devices.Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO

[0084] Input / output device(s) 604 may include any device, mechanism, system, interactive display, and / or various other hardware and software components for communicating information between processing system 600 and a user of processing system 600. For example, input / output device(s) 604 may include input hardware, such as a keyboard, touch screen, button, microphone, speaker, and / or other device for receiving inputs from the user and sending outputs to the user.

[0085] Display device(s) 606 may generally include any sort of device configured to display data, information, graphics, user interface elements, and the like to a user. For example, display device(s) 606 may include internal and external displays such as an internal display of a tablet computer or an external display for a server computer or a projector. Display device(s) 606 may further include displays for devices, such as augmented, virtual, and / or extended reality devices. In various embodiments, display device(s) 606 may be configured to display a graphical user interface.

[0086] Network interface(s) 608 provide processing system 600 with access to external networks and thereby to external processing systems. Network interface(s) 608 can generally be any hardware and / or software capable of transmitting and / or receiving data via a wired or wireless network connection. Accordingly, network interface(s) 608 can include a communication transceiver for sending and / or receiving any wired and / or wireless communication.

[0087] Computer-readable medium 670 may be a volatile memory, such as a random access memory (RAM), or a nonvolatile memory, such as nonvolatile random access memory (NVRAM), or the like. In this example, computer-readable medium 670 includes data integration component 620, geological basin model generation component 622, suitability map generation component 624, carbon dioxide storage site selection component 626, detailed geological modeling component 628, dynamic reservoir model realizations generation component 630, flow simulation component 632, geomechanical simulation component 634, evaluation component 636, well log data 638, seismic data 640, 2D seismic lines data 642, core data 644, drilling data 646, buoyancy data 648, geological basin model(s) 650, suitability maps 652, geological models 654, reservoir model realizations 656, simulation results 658, evaluation scores 660, generating logic 662, simulating logic 664, selecting logic 666, and performing logic 668.

[0088] In certain aspects, data integration component 620 is responsible for gathering data for use in subsurface carbon dioxide storage site identification and evaluation.Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO

[0089] In certain aspects, geological basin model generation component 622 is responsible for generating a geological basin model having a plurality of rock formations based on data associated with a candidate region for subsurface carbon dioxide storage.

[0090] In certain aspects, suitability map generation component 624 is responsible for generating a plurality of suitability maps for a candidate region.

[0091] In certain aspects, carbon dioxide storage site selection component 626 is responsible for selecting a candidate carbon dioxide storage site from a plurality of candidate carbon dioxide storage sites in a candidate region.

[0092] In certain aspects, detailed geological modeling component 628 is responsible for generating a plurality of geological model realizations for a selected candidate carbon dioxide storage site.

[0093] In certain aspects, dynamic reservoir model realizations generation component 630 is responsible for generating a plurality of reservoir model realizations from at least a geological basin model.

[0094] In certain aspects, flow simulation component 632 is responsible for performing a flow simulation for a plurality of time periods.

[0095] In certain aspects, geomechanical simulation component 634 is responsible for performing a plurality a geomechanical simulation for a plurality of time periods to generate simulation results.

[0096] In certain aspects, evaluation component 636 is responsible for generating evaluation scores for one or more candidate carbon dioxide storage sites.

[0097] In certain aspects, generating logic 662 includes logic for generating a geological basin model having a plurality of rock formations based on data associated with a candidate region for subsurface carbon dioxide storage. In certain aspects, generating logic 662 includes logic for generating a plurality of suitability maps for the candidate region based on at least one of the structural trap or the carbon dioxide leakage pathway, wherein each suitability map corresponds to a candidate carbon dioxide storage site among a plurality of candidate carbon dioxide storage sites in the candidate region. In certain aspects, generating logic 662 includes logic for generatingClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO a plurality of reservoir model realizations from at least the geological basin model, wherein each reservoir model realization represents a subterranean environment for the candidate carbon dioxide storage site and comprises at least a different facies distribution than a facies distribution associated with other reservoir model realization of the plurality of reservoir model realizations. In certain aspects, generating logic 662 includes logic for generating an evaluation score for the candidate carbon dioxide storage site based on the simulation results generated for each of the plurality of reservoir model realizations, the evaluation score indicating a performance of the candidate carbon dioxide storage site with respect to the subsurface carbon dioxide storage.

[0098] In certain aspects, simulating logic 664 includes logic for simulating fluid flow of carbon dioxide for the candidate region using the geological basin model to identify at least one of a structural trap or a carbon dioxide leakage pathway for the candidate region.

[0099] In certain aspects, selecting logic 666 includes logic for selecting a candidate carbon dioxide storage site from the plurality of candidate carbon dioxide storage sites in the candidate region based on the suitability map generated for the candidate carbon dioxide storage site.

[0100] In certain aspects, performing logic 668 includes logic for, for each of the plurality of reservoir model realizations, performing a plurality of storage and containment simulations to generate simulation results. In certain aspects, performing logic 668 includes logic for performing a flow simulation and a geomechanical simulation for a plurality of time periods,

[0101] Note that FIG. 6 is just one example of a processing system consistent with aspects described herein, and other processing systems having additional, alternative, or fewer components are possible consistent with this disclosure.Example Clauses

[0102] Implementation examples are described in the following numbered clauses:

[0103] Clause 1 : A method of subsurface carbon dioxide storage site identification and evaluation, comprising: generating a geological basin model having a plurality of rock formations based on data associated with a candidate region for subsurface carbon dioxide storage; simulating fluid flow of carbon dioxide for the candidate region using the geological basin model to identify at least one of a structural trap or a carbon dioxide leakage pathway for the candidate region;Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO generating a plurality of suitability maps for the candidate region based on at least one of the structural trap or the carbon dioxide leakage pathway, wherein each suitability map corresponds to a candidate carbon dioxide storage site among a plurality of candidate carbon dioxide storage sites in the candidate region; selecting a candidate carbon dioxide storage site from the plurality of candidate carbon dioxide storage sites in the candidate region based on the suitability map generated for the candidate carbon dioxide storage site; generating a plurality of reservoir model realizations from at least the geological basin model, wherein each reservoir model realization represents a subterranean environment for the candidate carbon dioxide storage site and comprises at least a different facies distribution than a facies distribution associated with other reservoir model realizations of the plurality of reservoir model realizations; for each of the plurality of reservoir model realizations, performing a plurality of storage and containment simulations to generate simulation results; and generating an evaluation score for the candidate carbon dioxide storage site based on the simulation results generated for each of the plurality of reservoir model realizations, the evaluation score indicating a performance of the candidate carbon dioxide storage site with respect to the subsurface carbon dioxide storage.

[0104] Clause 2: The method of Clause 1, wherein a resolution of each of the plurality of reservoir model realizations is greater than a resolution of the geological basin model for the candidate carbon dioxide storage site.

[0105] Clause 3: The method of any one of Clauses 1-2, wherein performing the plurality of storage and containment simulations comprises performing a flow simulation and a geomechanical simulation for a plurality of time periods.

[0106] Clause 4: The method of any one of Clauses 1-3, wherein performing the plurality of storage and containment simulations is based on at least one of fluid physics data or rock physics data.

[0107] Clause 5: The method of any one of Clauses 1-4, wherein the evaluation score for the candidate carbon dioxide storage site indicates the performance of the candidate carbon dioxide storage site with respect to the subsurface carbon dioxide storage for at least one of: one or more candidate well placements for carbon dioxide injection at the candidate carbon dioxide storageClient Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO site; one or more carbon dioxide injection schedules for the carbon dioxide injection at the candidate carbon dioxide storage site; or one or more operating constraints.

[0108] Clause 6: The method of Clause 5, wherein the operating constraints comprise at least one of: a maximum carbon dioxide injection rate; a minimum carbon dioxide injection rate; a fluid containment risk threshold; a compaction threshold; a subsidence threshold; or a maximum risk of affecting one more adjacent reservoirs during operation.

[0109] Clause 7: The method of any one of Clauses 1-6, wherein simulating the fluid flow of the carbon dioxide for the candidate region using the geological basin model is based on buoyancy data for carbon dioxide under pressure and temperature conditions associated with the candidate region.

[0110] Clause 8: The method of any one of Clauses 1-7, wherein selecting the candidate carbon dioxide storage site from the plurality of candidate carbon dioxide storage sites in the candidate region is based on one or more constraints comprising at least one of a location constraint, a depth constraint, a porosity constraint, a pressure constraint, a rock failure constraint, a fault stability bound, or a fracture stability bound.[OHl] Clause 9: The method of any one of Clauses 1-8, wherein data associated with the candidate region comprises at least one of: well log data; seismic data; 2D seismic lines; core data; or drilling data.

[0112] Clause 10: One or more processing systems, comprising: one or more memories comprising computer-executable instructions; and one or more processors configured to execute the computer-executable instructions and cause the one or more processing systems to perform a method in accordance with any one of Clauses 1-9.

[0113] Clause 11 : One or more processing systems, comprising means for performing a method in accordance with any one of Clauses 1-9.

[0114] Clause 12: One or more non-transitory computer-readable media storing program code for causing one or more processing systems to perform the steps of any one of Clauses 1-9.Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO

[0115] Clause 13: One or more computer program products embodied on one or more computer-readable storage media comprising code for performing a method in accordance with any one of Clauses 1-9.

[0116] Clause 14: An apparatus, comprising: a processing system that includes processor circuitry and memory circuitry that stores code and is coupled with the processor circuitry, the processing system configured to cause the apparatus to perform a method in accordance with any one of Clauses 1-9.Additional Considerations

[0117] The preceding description is provided to enable any person skilled in the art to practice the various embodiments described herein. The examples discussed herein are not limiting of the scope, applicability, or embodiments set forth in the claims. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments. For example, changes may be made in the function and arrangement of elements discussed without departing from the scope of the disclosure. Various examples may omit, substitute, or add various procedures or components as appropriate. For instance, the methods described may be performed in an order different from that described, and various steps may be added, omitted, or combined. Also, features described with respect to some examples may be combined in some other examples. For example, an apparatus may be implemented or a method may be practiced using any number of the aspects set forth herein. In addition, the scope of the disclosure is intended to cover such an apparatus or method that is practiced using other structure, functionality, or structure and functionality in addition to, or other than, the various aspects of the disclosure set forth herein. It should be understood that any aspect of the disclosure disclosed herein may be embodied by one or more elements of a claim.

[0118] As used herein, a phrase referring to “at least one of’ a list of items refers to any combination of those items, including single members. As an example, “at least one of: a, b, or c” is intended to cover a, b, c, a-b, a-c, b-c, and a-b-c, as well as any combination with multiples of the same element (e.g., a-a, a-a-a, a-a-b, a-a-c, a-b-b, a-c-c, b-b, b-b-b, b-b-c, c-c, and c-c-c or any other ordering of a, b, and c).Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO

[0119] As used herein, the term “determining” encompasses a wide variety of actions. For example, “determining” may include calculating, computing, processing, deriving, investigating, looking up (e.g., looking up in a table, a database or another data structure), ascertaining and the like. Also, “determining” may include receiving (e.g., receiving information), accessing (e.g., accessing data in a memory) and the like. Also, “determining” may include resolving, selecting, choosing, establishing and the like.

[0120] The methods disclosed herein comprise one or more steps or actions for achieving the methods. The method steps and / or actions may be interchanged with one another without departing from the scope of the claims. In other words, unless a specific order of steps or actions is specified, the order and / or use of specific steps and / or actions may be modified without departing from the scope of the claims. Further, the various operations of methods described above may be performed by any suitable means capable of performing the corresponding functions. The means may include various hardware and / or software component(s) and / or module(s), including, but not limited to a circuit, an application specific integrated circuit (ASIC), or processor. Generally, where there are operations illustrated in figures, those operations may have corresponding counterpart means-plus- function components with similar numbering.

[0121] The following claims are not intended to be limited to the embodiments shown herein, but are to be accorded the full scope consistent with the language of the claims. Within a claim, reference to an element in the singular is not intended to mean “one and only one” unless specifically so stated, but rather “one or more.” Unless specifically stated otherwise, the term “some” refers to one or more. No claim element is to be construed under the provisions of 35 U.S.C. §112(f) unless the element is expressly recited using the phrase “means for” or, in the case of a method claim, the element is recited using the phrase “step for.” All structural and functional equivalents to the elements of the various aspects described throughout this disclosure that are known or later come to be known to those of ordinary skill in the art are expressly incorporated herein by reference and are intended to be encompassed by the claims. Moreover, nothing disclosed herein is intended to be dedicated to the public regardless of whether such disclosure is explicitly recited in the claims.

Claims

Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WOCLAIMSWhat is claimed is:

1. A method of subsurface carbon dioxide storage site identification and evaluation, comprising: generating a geological basin model having a plurality of rock formations based on data associated with a candidate region for subsurface carbon dioxide storage; simulating fluid flow of carbon dioxide for the candidate region using the geological basin model to identify at least one of a structural trap or a carbon dioxide leakage pathway for the candidate region; generating a plurality of suitability maps for the candidate region based on at least one of the structural trap or the carbon dioxide leakage pathway, wherein each suitability map corresponds to a candidate carbon dioxide storage site among a plurality of candidate carbon dioxide storage sites in the candidate region; selecting a candidate carbon dioxide storage site from the plurality of candidate carbon dioxide storage sites in the candidate region based on the suitability map generated for the candidate carbon dioxide storage site; generating a plurality of reservoir model realizations from at least the geological basin model, wherein each reservoir model realization represents a subterranean environment for the candidate carbon dioxide storage site and comprises at least a different facies distribution than a facies distribution associated with other reservoir model realization of the plurality of reservoir model realizations; for each of the plurality of reservoir model realizations, performing a plurality of storage and containment simulations to generate simulation results; and generating an evaluation score for the candidate carbon dioxide storage site based on the simulation results generated for each of the plurality of reservoir model realizations, the evaluation score indicating a performance of the candidate carbon dioxide storage site with respect to the subsurface carbon dioxide storage.Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO2. The method of Claim 1, wherein a resolution of each of the plurality of reservoir model realizations is greater than a resolution of the geological basin model for the candidate carbon dioxide storage site.

3. The method of Claim 1, wherein performing the plurality of storage and containment simulations comprises performing a flow simulation and a geomechanical simulation for a plurality of time periods.

4. The method of Claim 1, wherein performing the plurality of storage and containment simulations is based on at least one of fluid physics data or rock physics data.

5. The method of Claim 1, wherein the evaluation score for the candidate carbon dioxide storage site indicates the performance of the candidate carbon dioxide storage site with respect to the subsurface carbon dioxide storage for at least one of: one or more candidate well placements for carbon dioxide injection at the candidate carbon dioxide storage site; one or more carbon dioxide injection schedules for the carbon dioxide injection at the candidate carbon dioxide storage site; or one or more operating constraints.

6. The method of Claim 5, wherein the operating constraints comprise at least one of: a maximum carbon dioxide injection rate; a minimum carbon dioxide injection rate; a fluid containment risk threshold; a compaction threshold; a subsidence threshold; or a maximum risk of affecting one more adjacent reservoirs during operation.

7. The method of Claim 1, wherein simulating the fluid flow of the carbon dioxide for the candidate region using the geological basin model is based on buoyancy data for carbon dioxide under pressure and temperature conditions associated with the candidate region.Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO8. The method of Claim 1, wherein selecting the candidate carbon dioxide storage site from the plurality of candidate carbon dioxide storage sites in the candidate region is based on one or more constraints comprising at least one of a location constraint, a depth constraint, a porosity constraint, a pressure constraint, a rock failure constraint, a fault stability bound, or a fracture stability bound.

9. The method of Claim 1, wherein data associated with the candidate region comprises at least one of: well log data; seismic data; two-dimensional (2D) seismic lines; core data; or drilling data.

10. A processing system, comprising: one or more memories comprising computer-executable instructions; and one or more processors configured to execute the computer-executable instructions and cause the processing system to: generate a geological basin model having a plurality of rock formations based on data associated with a candidate region for subsurface carbon dioxide storage; simulate fluid flow of carbon dioxide for the candidate region using the geological basin model to identify at least one of a structural trap or a carbon dioxide leakage pathway for the candidate region; generate a plurality of suitability maps for the candidate region based on at least one of the structural trap or the carbon dioxide leakage pathway, wherein each suitability map corresponds to a candidate carbon dioxide storage site among a plurality of candidate carbon dioxide storage sites in the candidate region; select a candidate carbon dioxide storage site from the plurality of candidate carbon dioxide storage sites in the candidate region based on the suitability map generated for the candidate carbon dioxide storage site;Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO generate a plurality of reservoir model realizations from at least the geological basin model, wherein each reservoir model realization represents a subterranean environment for the candidate carbon dioxide storage site and comprises at least a different facies distribution than a facies distribution associated with other reservoir model realization of the plurality of reservoir model realizations; for each of the plurality of reservoir model realizations, perform a plurality of storage and containment simulations to generate simulation results; and generate an evaluation score for the candidate carbon dioxide storage site based on the simulation results generated for each of the plurality of reservoir model realizations, the evaluation score indicating a performance of the candidate carbon dioxide storage site with respect to the subsurface carbon dioxide storage.

11. The processing system of Claim 10, wherein a resolution of each of the plurality of reservoir model realizations is greater than a resolution of the geological basin model for the candidate carbon dioxide storage site.

12. The processing system of Claim 10, wherein to perform the plurality of storage and containment simulations, the one or more processors are configured to execute the computerexecutable instructions and cause the processing system to perform a flow simulation and a geomechanical simulation for a plurality of time periods.

13. The processing system of Claim 10, wherein to perform the plurality of storage and containment simulations, the one or more processors are configured to execute the computerexecutable instructions and cause the processing system to perform the plurality of storage and containment simulations based on at least one of fluid physics data or rock physics data.

14. The processing system of Claim 10, wherein the evaluation score for the candidate carbon dioxide storage site indicates the performance of the candidate carbon dioxide storage site with respect to the subsurface carbon dioxide storage for at least one of one or more candidate well placements for carbon dioxide injection at the candidate carbon dioxide storage site;Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO one or more carbon dioxide injection schedules for the carbon dioxide injection at the candidate carbon dioxide storage site; or one or more operating constraints.

15. The processing system of Claim 14, wherein the operating constraints comprise at least one of: a maximum carbon dioxide injection rate; a minimum carbon dioxide injection rate; a fluid containment risk threshold; a compaction threshold; a subsidence threshold; or a maximum risk of affecting one more adjacent reservoirs during operation.

16. The processing system of Claim 10, wherein to simulate the fluid flow of the carbon dioxide for the candidate region using the geological basin model, the one or more processors are configured to execute the computer-executable instructions and cause the processing system to simulate the fluid flow of the carbon dioxide for the candidate region using the geological basin model based on buoyancy data for carbon dioxide under pressure and temperature conditions associated with the candidate region.

17. The processing system of Claim 10, wherein to select the candidate carbon dioxide storage site from the plurality of candidate carbon dioxide storage sites in the candidate region, the one or more processors are configured to execute the computer-executable instructions and cause the processing system to select the candidate carbon dioxide storage site based on one or more constraints comprising at least one of a location constraint, a depth constraint, a porosity constraint, a pressure constraint, a rock failure constraint, a fault stability bound, or a fracture stability bound.

18. The processing system of Claim 10, wherein data associated with the candidate region comprises at least one of: well log data; seismic data;Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO two-dimensional (2D) seismic lines; core data; or drilling data.

19. A non-transitory computer-readable medium comprising instructions that, when executed by one or more processors of a computing system, cause the computing system to perform operations for subsurface carbon dioxide storage site identification and evaluation, the operations comprising: generating a geological basin model having a plurality of rock formations based on data associated with a candidate region for subsurface carbon dioxide storage; simulating fluid flow of carbon dioxide for the candidate region using the geological basin model to identify at least one of a structural trap or a carbon dioxide leakage pathway for the candidate region; generating a plurality of suitability maps for the candidate region based on at least one of the structural trap or the carbon dioxide leakage pathway, wherein each suitability map corresponds to a candidate carbon dioxide storage site among a plurality of candidate carbon dioxide storage sites in the candidate region; selecting a candidate carbon dioxide storage site from the plurality of candidate carbon dioxide storage sites in the candidate region based on the suitability map generated for the candidate carbon dioxide storage site; generating a plurality of reservoir model realizations from at least the geological basin model, wherein each reservoir model realization represents a subterranean environment for the candidate carbon dioxide storage site and comprises at least a different facies distribution than a facies distribution associated with other reservoir model realization of the plurality of reservoir model realizations; for each of the plurality of reservoir model realizations, performing a plurality of storage and containment simulations to generate simulation results; and generating an evaluation score for the candidate carbon dioxide storage site based on the simulation results generated for each of the plurality of reservoir model realizations, the evaluation score indicating a performance of the candidate carbon dioxide storage site with respect to the subsurface carbon dioxide storage.Client Ref. No.: IS24.0015-WO-PCTD&S Ref. No.: SLBG240015WO20. The non-transitory computer-readable medium of Claim 19, wherein a resolution of each of the plurality of reservoir model realizations is greater than a resolution of the geological basin model for the candidate carbon dioxide storage site.

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