Method and equipment for predicting and optimizing CO2 mineralization storage efficiency and storage medium

Abstract

The invention relates to a method and equipment for predicting and optimizing CO2 mineralization storage efficiency and a storage medium. The method comprises the following steps: constructing a mineral supercell structure model and obtaining a stable configuration of a target mineral; constructing a vacuum layer based on the stable configuration, and filling H2O molecules and CO2 molecules to construct a CO2-water-mineral system model; carrying out reaction molecular dynamics simulation to obtain atomic motion trail and bond level change information; calculating the CO2 sequestration rate; drawing a three-dimensional carbon sequestration mechanism distribution diagram; and the sealing conditions of actual geological sealing engineering are optimized. According to the method, adsorption and chemical reaction behaviors of CO2 in underground rock pores are reduced, the storage condition of CO2 is quantified, then the influence of parameters such as temperature, pressure and water content on the CO2 storage rate is evaluated, the storage effects under different conditions are compared, a basis can be provided for optimizing the optimal storage condition, and the storage efficiency of CO2 is improved. The method has important guiding significance on design and optimization of a sealing scheme in practical engineering.

Description

Technical Field

[0001] This invention relates to the field of carbon dioxide geological storage technology, and in particular to a method, equipment and storage medium for predicting and optimizing CO2 mineralization storage efficiency. Background Technology

[0002] Elevated atmospheric carbon dioxide concentrations are considered a major contributor to global warming, and carbon capture, utilization, and storage (CCUS) is a key technological approach for achieving large-scale, deep reduction of greenhouse gas emissions. Geological storage is a core element for achieving long-term, safe, and stable CO2 storage. Currently, CO2 is believed to be stored underground primarily in four physical or geochemical forms: tectonic storage, residual phase storage (also known as capillary storage), dissolution storage, and mineralization storage. Mineralization storage involves the chemical reaction of CO2 with aluminosilicate minerals in the formation to generate stable carbonate minerals, achieving permanent CO2 storage with significant advantages in long-term safety and stability. During mineralization storage, its long-term safety and storage efficiency are heavily influenced by CO2-water-mineral interactions. However, traditional experiments and field trials are costly, time-consuming, and difficult to implement, limiting the efficiency of optimizing storage conditions. Furthermore, physical and numerical simulations struggle to accurately describe the complex multiphase, multi-scale micro-dynamic processes of mineralization storage and the impact of parameters such as temperature, pressure, and water content on CO2 storage efficiency. Molecular simulation technology provides a powerful tool for revealing microscopic mechanisms at the atomic / molecular scale.

[0003] The existing methods for predicting and evaluating the effectiveness of CO2 mineralization storage still have shortcomings: (1) The existing research on the mechanism of CO2 mineralization storage is not yet perfect, and the influence of key parameters such as temperature, pressure and water content on storage efficiency is unclear; (2) Traditional experiments and field tests are costly and time-consuming, making it difficult to achieve rapid evaluation under multiple conditions; (3) Existing molecular simulation methods have insufficient accuracy in predicting reaction pathways under multi-field coupling conditions and lack quantitative evaluation methods.

[0004] Therefore, it is necessary to establish a quantitative method for predicting and evaluating the effectiveness of CO2 mineralization and storage, which can be used to assess the impact of parameters such as temperature, pressure, and water content on the CO2 storage rate, and provide theoretical basis and data support for the design and optimization of storage schemes in practical engineering. Summary of the Invention

[0005] To address the shortcomings of existing technologies, this invention provides a method, equipment, and storage medium for predicting and optimizing CO2 mineralization and storage efficiency. It solves the problems of incomplete research on the mechanism of traditional CO2 mineralization and storage, unclear influence of key parameters such as temperature, pressure, and water content on storage efficiency, high cost and long cycle of traditional experiments and field tests making it difficult to achieve rapid evaluation under multiple conditions, and insufficient accuracy of traditional molecular simulation methods in predicting reaction paths under multi-field coupling conditions, lacking quantitative evaluation methods.

[0006] To solve the above-mentioned technical problems, the present invention provides the following technical solution: a method for predicting and optimizing CO2 mineralization and storage efficiency, comprising the following steps: S1. Based on the single-cell structure of the target mineral, construct a supercell structure model of the mineral and relax the mineral structure to obtain a stable configuration of the target mineral. S2. Construct a vacuum layer based on the stable configuration of the target mineral, fill the vacuum layer with H2O molecules and CO2 molecules, and construct a CO2-water-mineral system model. S3. Conduct reaction molecular dynamics simulations: Minimize the energy of the CO2-water-mineral system model, perform reaction molecular dynamics simulations, and obtain information on atomic trajectories and bond order changes; S4. Calculate the CO2 sequestration rate based on the atomic motion trajectories and bond order changes obtained from the simulation; S5. Draw a three-dimensional carbon sequestration mechanism distribution map based on CO2 sequestration rate to intuitively show the impact of each parameter on CO2 sequestration efficiency; S6. Based on the three-dimensional carbon sequestration mechanism distribution map, optimize the storage conditions for actual geological storage projects.

[0007] Furthermore, in step S1, the specific process includes the following steps: S11. Obtain the single-cell structure of the target mineral from the inorganic crystal structure database; S12. Based on the obtained single-cell structure, construct a mineral supercell structure model using molecular modeling software; S13. Relaxation is performed in the NPT ensemble using an open-source software package to obtain the stable configuration with the lowest system energy.

[0008] Furthermore, in step S2, the specific process includes the following steps: S21. Extend the stable configuration of the target mineral along the Y-axis in both the upper and lower directions to construct two vacuum layers with the same thickness as itself, and set periodic boundary conditions in the X, Y, and Z spatial dimensions. S22. Randomly and uniformly fill the vacuum layer with H2O molecules and CO2 molecules of a set density to simulate different target water content and pressure conditions, thus forming a CO2-water-mineral system model.

[0009] Furthermore, in step S3, the reaction molecular dynamics simulation specifically includes the following steps: S31. Before performing reaction molecular dynamics simulations, optimize each CO2-water-mineral system model by minimizing energy. S32. The optimized geometric configuration is simulated using the NVT ensemble: Newton's equations of motion are solved using the reaction force field to calculate the atomic trajectories, and the bond order is calculated in real time based on the interatomic spacing. The breaking and formation of chemical bonds are dynamically described, and information on bond order changes is obtained. The entire process of CO2 molecules adsorption, diffusion and reaction with the target mineral surface in the pore water environment under different temperatures and pressures is simulated.

[0010] Furthermore, in step S4, the specific process includes the following steps: S41. Based on information about atomic motion trajectories and bond order changes, count the number of CO2 molecules consumed during the reaction process; S42. Define CO2 sequestration rate The number of CO2 molecules consumed during the reaction. Compared with the initial total number of injected CO2 molecules The ratio is calculated using the following formula: .

[0011] Further, step S5 specifically includes: drawing a three-dimensional carbon sequestration mechanism distribution map based on the CO2 sequestration rate under different temperature, pressure, and water content conditions.

[0012] Furthermore, step S6 specifically includes: by analyzing the three-dimensional carbon sequestration mechanism distribution map, determining the key parameter combination for achieving the optimal CO2 sequestration rate, and providing optimization suggestions for sequestration conditions for actual geological sequestration projects.

[0013] Furthermore, the present invention also provides an electronic device comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement steps of a method for predicting and optimizing CO2 mineralization storage efficiency.

[0014] Furthermore, the present invention also provides a storage medium, which is a computer-readable storage medium, on which a computer program is stored, wherein when the computer program is executed by a processor, the steps of a method for predicting and optimizing CO2 mineralization sequestration efficiency are implemented.

[0015] By employing the above technical solutions, the present invention provides a method, apparatus, and storage medium for predicting and optimizing CO2 mineralization and storage efficiency, which has at least the following beneficial effects: (1) This invention outputs quantitative data through reaction molecular dynamics simulation and draws a three-dimensional carbon fixation mechanism distribution map, realizing quantitative prediction and visualization analysis of CO2 sequestration efficiency, overcoming the limitations of traditional methods that rely on experience; (2) By using computational simulation to replace high-cost physical experiments and field tests, this invention significantly reduces research costs and time, and provides the possibility for rapid evaluation and optimization under multiple scenarios and conditions; (3) This invention reveals the influence mechanism of parameters such as temperature, pressure and water content on CO2 storage effect by dynamically simulating the entire process of CO2 mineralization and storage at the atomic scale. It simulates different target water content and pressure conditions by constructing CO2-water-mineral system models of H2O molecules and CO2 molecules with different densities. Different temperatures are set in the simulation process to reflect the influence of temperature on storage efficiency. (4) This invention has strong versatility. It is verified by taking calcium feldspar as an example, but its principle and process can be extended to the evaluation and optimization of CO2 sequestration efficiency of other aluminosilicate minerals (such as potassium feldspar, sodium feldspar, etc.), and has broad application prospects. Attached Figure Description

[0016] The accompanying drawings, which are included to provide a further understanding of this application and form part of this application, illustrate exemplary embodiments and are used to explain this application, but do not constitute an undue limitation of this application. In the drawings: Figure 1 This is a flowchart of a method for predicting and optimizing CO2 mineralization and storage efficiency according to the present invention; Figure 2 This is a three-dimensional carbon fixation mechanism distribution diagram drawn in an embodiment of the present invention. Detailed Implementation

[0017] To make the above-mentioned objects, features, and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments. This will allow for a full understanding of how the present application uses technical means to solve technical problems and achieve technical effects, and to facilitate its implementation.

[0018] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0019] Please refer to Figures 1-2This illustration shows a specific implementation of the present embodiment. In this embodiment, a stable configuration of the target mineral is obtained, a vacuum layer is constructed and filled with H2O and CO2 molecules to build a CO2-water-mineral system model. Reaction molecular dynamics simulation is performed to obtain atomic motion trajectories and bond order changes, CO2 sequestration rate is calculated, a three-dimensional carbon fixation mechanism distribution map is drawn, sequestration conditions are optimized, the adsorption and chemical reaction behavior of CO2 in underground rock pores is reconstructed, its sequestration status is quantified, and the influence of parameters such as temperature, pressure, and water content on CO2 sequestration rate is evaluated. By comparing the sequestration effects under different conditions, a basis can be provided for selecting the optimal sequestration conditions, which has important guiding significance for the design and optimization of sequestration schemes in actual engineering.

[0020] Please refer to Figure 1 This embodiment proposes a method for predicting and optimizing CO2 mineralization and storage efficiency, which includes the following steps: S1. The single-cell structure of anorthite can be obtained from the Inorganic Crystal Structure Database (ICSD). The cell is expanded (7×2×4, a total of 5824 atoms) using molecular modeling software to construct a mineral supercell structure model. The system is then relaxed in the NPT ensemble (i.e., isothermal and isobaric ensemble) under the conditions of 300K and 1 atm (i.e., 1 standard atmosphere) using LAMMPS software (an open-source software package) to obtain the stable configuration with the lowest energy of the system.

[0021] In this embodiment, "7×2×4" refers to the cell expansion factor in the three lattice vector directions of the mineral single cell structure during the cell expansion process. That is, the initial single cell structure lattice vector direction a is expanded by 7 times, direction b by 2 times, and direction c by 4 times.

[0022] This invention uses NPT ensemble to relax supercell structures and obtain stable configurations of supercell models. This process is to obtain mineral crystal structures under real conditions and automatically adjust to equilibrium lattice constants and volumes at target temperatures and pressures, eliminating internal stresses or non-equilibrium lattice distortions that may exist during initial modeling.

[0023] S2. Extend the stable configuration of anorthite along both the upper and lower Y-axis to construct a vacuum layer with the same thickness as itself. The thickness of both vacuum layers along the Y-axis is 25.794 Å, and periodic boundary conditions are set in the X, Y, and Z spatial dimensions. Then, within the vacuum layer, apply a 0.25 g / cm³ boundary condition. 3 and 0.5g / cm 3 H2O molecules were randomly and uniformly packed at varying densities, and CO2 molecules were packed at different target densities (CO2 density: 0.1 g / cm³) under different water densities. 3 0.2g / cm 3 0.3g / cm 3To simulate different target water content and pressure conditions, a CO2-water-calcium feldspar system model was constructed.

[0024] The periodic boundary condition is a computational technique that infinitely replicates a finite simulation box in space along specified directions. It is primarily used to eliminate boundary effects, simulate macroscopic systems (X and Z axes), construct isolated surfaces, and effectively isolate interlayer interactions (Y axis). Employing periodic boundary conditions eliminates finite-size effects, improving the physical realism and reliability of simulation results. It allows for the accurate characterization of an infinitely large mineral-fluid interface system using a relatively small CO2-water-mineral system model. While ensuring the accuracy of the calculation results, it significantly reduces computational costs, achieving a high degree of balance between computational efficiency and model accuracy.

[0025] This invention simulates different target water content and pressure conditions by constructing CO2-water-mineral system models with different densities of H2O and CO2 molecules. During the simulation, different temperatures are set to reflect the effect of temperature on storage efficiency. This solves the problem that the traditional CO2 mineralization storage mechanism is still incomplete and the influence of key parameters such as temperature, pressure, and water content on storage efficiency is unclear.

[0026] S3. The above system models were simulated using LAMMPS software. Before simulation, each CO2-water-calcium feldspar system model was optimized for energy minimization. The NVT ensemble (i.e., a canonical ensemble) was used for the molecular dynamics simulation. Newton's equations of motion were solved using the reaction force field to calculate atomic trajectories. Bond order was calculated in real-time based on interatomic spacing to dynamically describe the breaking and formation of chemical bonds and obtain information on bond order changes. In this embodiment, the temperature range was 400-800K (temperature gradient of 100K), the time step was set to 0.2 fs (femtoseconds), and the calculation results were output every 1000 steps, with a total runtime of 1 ns (nanoseconds). Each example was run independently three times by changing the initial random number seed to ensure the statistical reliability of the results. The simulation results can be visualized in OVITO software (a software for visualizing and analyzing atomic simulation data) to obtain real-time dynamic images of the adsorption, diffusion, and reaction of CO2 molecules with the surface of calcium feldspar in a porous water environment under different temperatures and pressures.

[0027] In this embodiment, the ReaxFF force field is selected as the reaction force field, and the force field parameters are derived from the C / H / O / Ca / Al / Si parameter set developed by the Van Duin team.

[0028] In this embodiment, by employing computational simulation to replace high-cost physical experiments and field tests, the research cost and cycle are significantly reduced, enabling rapid evaluation and optimization under multiple scenarios and conditions. Simultaneously, by dynamically simulating the entire CO2 mineralization and sequestration process at the atomic scale, the influence mechanism of parameters such as temperature, pressure, and water content on the CO2 sequestration effect is revealed in depth. Furthermore, the NVT ensemble indicates that the number of atoms (N), volume (V), and temperature (T) of the simulated system remain constant. The fixed temperature (T) simulates the reaction occurring under isothermal conditions in a real environment; the fixed volume (V) ensures that the structure and surface area of ​​the mineral substrate remain unchanged, providing a stable and controllable interface environment for the adsorption and reaction of CO2 and water on the mineral surface. Therefore, reaction molecular dynamics simulation based on the NVT ensemble enables this invention to accurately study the reaction mechanism and kinetic behavior of CO2 on a fixed mineral surface, eliminating the interference of system volume and density changes on the reaction process, thereby revealing the microscopic nature of the reaction more clearly.

[0029] S4. Based on the atomic motion trajectories and bond order changes output by the simulation, use a Python script to count the number of CO2 molecules consumed during the reaction. Compared with the initial total number of injected CO2 molecules The ratio is used to calculate the CO2 sequestration rate, which is used to quantify CO2 sequestration efficiency.

[0030] The "total number of initially injected CO2 molecules" refers to the total number of CO2 molecules filled during the initial modeling, and its specific value is directly determined by the target pressure conditions set in the simulation. The "number of consumed CO2 molecules" refers to the number of CO2 molecules that no longer exist as free CO2 molecules due to chemical reactions with the mineral surface (such as bonding, carbonate formation, etc.) during the simulation. Based on information about atomic motion trajectories and bond order changes, the number of CO2 molecules still existing in the system as intact molecules at any given reaction time can be accurately identified and counted. Subtracting this number from the "total number of initially injected CO2 molecules" gives the "number of consumed CO2 molecules." To ensure the stability and representativeness of the calculation results, this invention uses a time window after the system reaches reaction equilibrium and calculates the average value of the "number of consumed CO2 molecules" during this time period. The ratio of this average value to the "total number of initially injected CO2 molecules" is the final CO2 sequestration rate.

[0031] S5. Based on the CO2 sequestration rate under different temperature, pressure, and water content conditions, draw a three-dimensional carbon fixation mechanism distribution diagram, such as... Figure 2 As shown, the three-dimensional carbon sequestration mechanism distribution diagram can intuitively demonstrate the influence of various parameters (H2O density, CO2 density, temperature) on CO2 sequestration efficiency (quantified by CO2 sequestration rate).

[0032] S6. By analyzing the three-dimensional storage efficiency distribution map, the key parameter combination for achieving the optimal CO2 storage efficiency is determined, providing suggestions for optimizing storage conditions for actual geological storage projects.

[0033] In this embodiment, quantitative data is output through reaction molecular dynamics simulation, and a three-dimensional carbon fixation mechanism distribution map is drawn, realizing quantitative prediction and visualization analysis of CO2 sequestration efficiency, overcoming the limitations of traditional methods that rely on experience. Furthermore, the method of this invention is highly versatile. This embodiment uses anorthite as an example for verification, but its principles and procedures can be extended to the evaluation and optimization of CO2 sequestration efficiency for other aluminosilicate minerals (such as potassium feldspar, sodium feldspar, etc.), showing broad application prospects.

[0034] This application also provides an electronic device, the device including: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement steps of a method for predicting and optimizing CO2 mineralization storage efficiency.

[0035] This application embodiment also provides a storage medium, which is a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the steps of a method for predicting and optimizing CO2 mineralization storage efficiency.

[0036] In the description of this specification, the references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of this application. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples. Moreover, without contradiction, those skilled in the art can combine and integrate the different embodiments or examples described in this specification, as well as the features of those different embodiments or examples.

[0037] The logic and / or steps represented in the flowchart or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus or device (such as a computer-based system, a processor-included system or other system that can fetch and execute instructions from, an instruction execution system, apparatus or device).

[0038] The above embodiments provide a detailed description of the present invention. Specific examples have been used to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. At the same time, for those skilled in the art, there will be changes in the specific implementation methods and application scope based on the ideas of the present invention. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for predicting and optimizing CO2 mineralization and storage efficiency, characterized in that, Includes the following steps: S1. Based on the single-cell structure of the target mineral, construct a supercell structure model of the mineral and relax the mineral structure to obtain a stable configuration of the target mineral. S2. Construct a vacuum layer based on the stable configuration of the target mineral, fill the vacuum layer with H2O molecules and CO2 molecules, and construct a CO2-water-mineral system model. S3. Conduct reaction molecular dynamics simulations: Minimize the energy of the CO2-water-mineral system model, perform reaction molecular dynamics simulations, and obtain information on atomic trajectories and bond order changes; S4. Calculate the CO2 sequestration rate based on the atomic motion trajectories and bond order changes obtained from the simulation; S5. Draw a three-dimensional carbon sequestration mechanism distribution map based on CO2 sequestration rate to intuitively show the impact of each parameter on CO2 sequestration efficiency; S6. Based on the three-dimensional carbon sequestration mechanism distribution map, optimize the storage conditions for actual geological storage projects.

2. The method for predicting and optimizing CO2 mineralization and storage efficiency according to claim 1, characterized in that: Step S1 specifically includes the following steps: S11. Obtain the single-cell structure of the target mineral from the inorganic crystal structure database; S12. Based on the obtained single-cell structure, construct a mineral supercell structure model using molecular modeling software; S13. Relaxation is performed in the NPT ensemble using an open-source software package to obtain the stable configuration with the lowest system energy.

3. The method for predicting and optimizing CO2 mineralization and storage efficiency according to claim 1, characterized in that: Step S2 specifically includes the following steps: S21. Extend the stable configuration of the target mineral along the Y-axis in both the upper and lower directions to construct two vacuum layers with the same thickness as itself, and set periodic boundary conditions in the X, Y, and Z spatial dimensions. S22. Randomly and uniformly fill the vacuum layer with H2O molecules and CO2 molecules of a set density to simulate different target water content and pressure conditions, thus forming a CO2-water-mineral system model.

4. The method for predicting and optimizing CO2 mineralization and storage efficiency according to claim 1, characterized in that: In step S3, the reaction molecular dynamics simulation specifically includes the following steps: S31. Before performing reaction molecular dynamics simulations, optimize each CO2-water-mineral system model by minimizing energy. S32. The optimized geometric configuration is simulated using the NVT ensemble: Newton's equations of motion are solved using the reaction force field to calculate the atomic trajectories, and the bond order is calculated in real time based on the interatomic spacing. The breaking and formation of chemical bonds are dynamically described, and information on bond order changes is obtained. The entire process of CO2 molecules adsorption, diffusion and reaction with the target mineral surface in the pore water environment under different temperatures and pressures is simulated.

5. The method for predicting and optimizing CO2 mineralization and storage efficiency according to claim 1, characterized in that: Step S4 specifically includes the following steps: S41. Based on information about atomic motion trajectories and bond order changes, count the number of CO2 molecules consumed during the reaction process; S42. Define CO2 sequestration rate The number of CO2 molecules consumed during the reaction. Compared with the initial total number of injected CO2 molecules The ratio is calculated using the following formula: 。 6. The method for predicting and optimizing CO2 mineralization and storage efficiency according to claim 1, characterized in that: Step S5 specifically includes: drawing a three-dimensional carbon sequestration mechanism distribution map based on the CO2 sequestration rate under different temperature, pressure, and water content conditions.

7. The method for predicting and optimizing CO2 mineralization and storage efficiency according to claim 1, characterized in that: Step S6 specifically includes: by analyzing the three-dimensional carbon sequestration mechanism distribution map, determining the key parameter combination for achieving the optimal CO2 sequestration rate, and providing optimization suggestions for sequestration conditions for actual geological sequestration projects.

8. An electronic device, characterized in that, The device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the computer program being configured to implement the steps of the method for predicting and optimizing CO2 mineralization storage efficiency as claimed in any one of claims 1 to 7.

9. A storage medium, characterized in that, The storage medium is a computer-readable storage medium, and a computer program is stored on the storage medium. When the computer program is executed by a processor, it implements the steps of the method for predicting and optimizing CO2 mineralization storage efficiency as described in any one of claims 1 to 7.

Images