A method, system, electronic device, and storage medium for analyzing the symbiotic mechanism of geothermal energy and earthquakes.

Abstract

This invention belongs to the field of geophysical exploration technology of geothermal resources and seismic activity. It provides a method, system, electronic device, and storage medium for analyzing the coexistence mechanism of geothermal and seismic activity. The method includes: three-dimensional joint inversion, computational domain gridding, attribute addition, boundary condition addition, reference temperature addition, simulation calculation, and correlation analysis. By performing three-dimensional joint inversion on electromagnetic and gravity data, this invention makes the model more consistent with the actual underground geological structure characteristics, freeing it from the idealized constraints of theoretical models and improving the accuracy of simulation results. Through attribute addition, boundary condition addition, reference temperature addition, simulation calculation, and correlation analysis, a complete theoretical system for the deep control and coexistence of seismic activity and geothermal resources is constructed, realizing the extraction of the intrinsic correlation between geothermal activity and earthquake occurrence.

Description

Technical Field

[0001] This invention relates to the field of geophysical exploration technology of geothermal resources and seismic activity, and in particular to a method, system, electronic device and storage medium for analyzing the coexistence mechanism of geothermal and seismic activity. Background Technology

[0002] Tectonic activity on a global scale is the result of relative movement between tectonic plates. The compression and collision between plates make the interface zones of modern lithospheric plates the most active regions, manifested as anomalous displays of high-heat flow zones, volcanic activity, magmatic intrusion, orogeny, seismic activity, and metamorphism. This provides ample heat sources and upward channels for the formation and distribution of high-temperature geothermal fluids. During the upward migration and escape of deep fluids, explosions occur, generating earthquakes of varying magnitudes and focal depths within the Earth. Fluids in the Earth's crust play a crucial role in earthquakes and the release of heat energy. Faults, as channels for the transport of fluids and groundwater or important storage spaces for thermal materials, are the main controlling factors for geothermal resources and deep seismic activity. Faults remain open under active seismic activity, allowing groundwater to circulate to deep, high-temperature regions and flow back to the surface as thermal fluids, forming geothermal energy. Volatile substances generated during fluid transport enter the thermal reservoir or surrounding rock strata, increasing pore pressure and causing rock rupture, thus triggering earthquakes. Therefore, geothermal resources and earthquake disasters are closely related in terms of their formation mechanisms. The main methods for characterizing the symbiotic mechanism between geothermal energy and earthquakes are geochemical analysis and geophysical exploration. Geochemical methods can discuss the relationship between geothermal energy and earthquakes by analyzing the source and origin of geothermal fluids, reservoir temperature, gas origin, and the intensity of mantle-derived fluid release. Geophysical exploration provides spatial information for discussing the relationship between geothermal resources and seismic activity by inverting subsurface geological structures. However, the external factors of seismic activity and geothermal resources are the result of tectonic regimes, while the internal factors depend on material and structural properties. Current research methods only focus on the observational characteristics and conversion relationships between the two, lacking a complete system for the deep control and symbiotic relationship between seismic activity and geothermal resources, as well as related theories. Establishing a unified framework is a shortcut to jointly solving resource and disaster problems, and is also a key scientific issue for achieving the two strategic goals of a habitable planet and a secure supply of new energy sources.

[0003] Traditional thermal-fluid-solid coupling models suffer from dual limitations in terms of application scenarios and research scale. On the one hand, their applications are mostly focused on enhanced geothermal production, such as exploring the impact of different fracture types on heat transfer through simulating actual production injection processes, or focusing on microscopic simulations of rock skeletons and pores at the laboratory scale to explain multiphysics coupling mechanisms. However, they have not yet broken through the scale bottleneck to extend to macroscopic simulations at the crustal level, making it difficult to analyze the interaction between actual geothermal resources and seismic hazards. On the other hand, constrained by technological development, current research on the relationship between geothermal and earthquakes still has significant shortcomings: most studies fail to fully consider the effects of fluid thermal convection and rely excessively on idealized theoretical models, leading to significant deviations between research results and actual geological processes, and failing to accurately characterize the intrinsic connection between geothermal and earthquake phenomena. Summary of the Invention

[0004] To overcome the shortcomings of existing technologies, the purpose of this invention is to provide a method, system, electronic device, and storage medium for analyzing the symbiotic mechanism of geothermal energy and earthquakes, thereby solving the problems of traditional models being unable to analyze the interaction between actual geothermal resources and earthquake disasters, and over-reliance on idealized theoretical models.

[0005] To achieve the above objectives, the present invention provides the following solution:

[0006] A method for analyzing the symbiotic mechanism of geothermal energy and earthquakes includes:

[0007] Three-dimensional joint inversion was performed on the pre-collected electromagnetic and gravity data to obtain a three-dimensional resistivity and density model;

[0008] The three-dimensional resistivity and density model is divided into several computational domain grids;

[0009] Fluid field, heat transfer field, deformation field, heat source attributes, thermal property parameters, and mechanical parameters are added to each of the partitioned computational domain meshes to obtain attribute meshes;

[0010] Boundary conditions are added to the fluid field, heat transfer field, and deformation field of each attribute mesh to obtain the simulation mesh;

[0011] A reference temperature is added to the simulation mesh based on its distribution location to obtain a thermal-fluid-structure interaction model;

[0012] The thermal-fluid-solid coupling model was simulated and calculated under different heat source conditions to obtain the temperature field and strain field within the Earth's crust.

[0013] Using GIS spatial analysis technology, the spatial distribution data of the temperature field, strain field, surface geothermal resources, and underground seismic hazards within the Earth's crust are overlaid, compared, and analyzed for spatial coupling relationships to obtain the results of the analysis on the coupling relationship between geothermal energy and earthquakes.

[0014] Preferably, a three-dimensional joint inversion is performed on the pre-acquired electromagnetic data and gravity data to obtain a three-dimensional resistivity and density model, including:

[0015] The electromagnetic data is subjected to three-dimensional MT inversion to obtain the MT inversion results; the objective function of the three-dimensional MT inversion is: ;in, ; The objective function value for the three-dimensional MT inversion; Fit a functional to the data; Represents data type, A value of 1 indicates MT. The value 2 represents gravity; This is the model parameter vector; As a regularization factor; For the model's stable functional; For constraint terms;

[0016] The MT inversion results are transformed into a structural reference model using a method for converting prior physical property information; the expression of the structural reference model includes: , ;in, The fitting functional is for the electromagnetic data; This is a regularization factor for the electromagnetic data; This is a model parameter vector for the electromagnetic data; The objective function value transformed from the structural reference model; This is the parameter vector for converting the electromagnetic model into a gravity model; For the prior rock physical property correlation function of density and resistivity;

[0017] The structural reference model is added to a preset wide-range constraint, and a three-dimensional gravity joint inversion is performed on the gravity data under the wide-range constraint to obtain the gravity inversion result; the calculation formula for the three-dimensional gravity inversion is: ;in, The gravity inversion result is as described; The fitting functional is given for the gravity data; This is a model parameter vector for the gravity data; This is a regularization factor for the gravity data;

[0018] The MT inversion results and the gravity inversion results are iterated to obtain the three-dimensional resistivity and density model.

[0019] Preferably, the three-dimensional resistivity and density model is divided into several computational domain grids, including:

[0020] Based on the collected geological information, the three-dimensional resistivity and density model is divided into different computational domain blocks using interpolation functions;

[0021] Define the geological structure of each computational domain block; the geological structure includes: thickness, geometry, and lithology;

[0022] Each computational domain block is divided into tetrahedral meshes using the finite element method to obtain several computational domain meshes.

[0023] Preferably, the thermophysical parameters include: density, thermal conductivity, heat generation rate, constant pressure heat capacity, coefficient of thermal expansion, and specific heat rate; the mechanical parameters include: Young's modulus, Poisson's ratio, porosity, and permeability.

[0024] Preferably, boundary conditions are added to the fluid field, heat transfer field, and deformation field of each attribute mesh to obtain a simulation mesh, including:

[0025] The inlet of the fluid field is set to a head of 15 km, the outlet of the fluid field is set to a head of 6 km, the upper boundary temperature of the aquifer of the fluid field is set to 623.15 K, and the lower boundary temperature of the aquifer of the fluid field is set to 787.15 K.

[0026] The annual average surface temperature at the upper boundary of the heat transfer field is set to 293.15 K, and the lower boundary condition of the heat transfer field is set to a mantle heat flux of 40 mW / m. 2 The side boundary conditions of the heat transfer field are set to adiabatic.

[0027] The simulation mesh is obtained by setting the lower boundary of the deformation field as a fixed boundary, the upper boundary of the deformation field as a free surface, and the side boundaries of the deformation field as symmetric boundaries.

[0028] Preferably, a reference temperature is added to the simulation mesh according to its distribution location to obtain a thermal-fluid-structure interaction model, including:

[0029] The surface temperature of the upper crust of the simulation grid was set to 293.15 K;

[0030] The temperature of the lower crustal rock mass portion of the simulation grid was set to 773.15K;

[0031] The temperature of the magma portion of the simulation mesh was set to 873.15K to obtain the thermo-fluid-solid coupling model.

[0032] Preferably, the thermo-fluid-solid coupling model is simulated under different heat source conditions to obtain the temperature field and strain field within the Earth's crust, including:

[0033] Construct the heat conduction equation; the heat conduction equation is: ;in, For effective thermal conductivity; For temperature field variables; For fluid density; The specific heat capacity at constant pressure of the fluid; The seepage velocity; As a volumetric heat source; For viscous heat dissipation;

[0034] Construct the governing equations for fluid seepage; the governing equations for fluid seepage include: , ;in, For quality source items; For permeability tensor; For fluid viscosity; Pore ​​fluid pressure; It is the acceleration due to gravity;

[0035] Construct the thermal stress control equations; the thermal stress control equations include: , , , ;in, This is the total stress tensor; It is a solid potential vector; Thermal strain; It is the linear thermal expansion coefficient; For reference temperature; Unit tensor; For stress tensor; Here is the stiffness matrix; It is a volume force;

[0036] The thermal-fluid-solid coupling model is simulated and calculated using the heat conduction equation, the fluid seepage equation, and the thermal stress equation to obtain the temperature field and strain field within the Earth's crust.

[0037] Preferably, a geothermal and earthquake symbiotic mechanism analysis system includes:

[0038] The joint inversion model is used to perform a three-dimensional joint inversion of pre-acquired electromagnetic and gravity data to obtain a three-dimensional resistivity and density model.

[0039] The mesh generation module is used to divide the three-dimensional resistivity and density model into several computational domain meshes;

[0040] The attribute addition module is used to add fluid field, heat transfer field, deformation field, heat source attributes, thermal property parameters and mechanical parameters to each of the partitioned computational domain meshes to obtain attribute meshes;

[0041] The boundary condition adding module is used to add boundary conditions to the fluid field, heat transfer field, and deformation field of each attribute mesh to obtain the simulation mesh;

[0042] The reference temperature addition module is used to add reference temperatures to the simulation mesh according to the distribution location of the simulation mesh to obtain a thermal-fluid-structure interaction model.

[0043] The simulation calculation module is used to simulate and calculate the thermo-fluid-solid coupling model under different heat source conditions to obtain the temperature field and strain field inside the Earth's crust.

[0044] The correlation analysis module is used to perform overlay comparison and spatial coupling relationship analysis on the spatial distribution data of the temperature field, strain field, surface geothermal resources and underground seismic hazards in the crust using GIS spatial analysis technology, so as to obtain the analysis results of the coupling relationship between geothermal and seismic forces.

[0045] Preferably, an electronic device includes: at least one processor and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, the instructions being executed by the processor to enable the processor to perform the aforementioned method for analyzing geothermal and seismic symbiotic mechanisms.

[0046] Preferably, a non-transitory computer-readable storage medium stores computer instructions for causing a computer to execute the aforementioned method for analyzing geothermal and seismic symbiotic mechanisms.

[0047] The present invention discloses the following technical effects:

[0048] This invention provides a method, system, electronic device, and storage medium for analyzing the symbiotic mechanism of geothermal energy and earthquakes. By performing three-dimensional joint inversion of electromagnetic and gravity data, it solves the problem of traditional models relying too heavily on idealized theoretical models, thereby improving the accuracy of simulation results. Through attribute addition, boundary condition addition, reference temperature addition, simulation calculation, and correlation analysis, it solves the problem that traditional models are unable to analyze the interaction between actual geothermal resources and earthquake disasters, and realizes the extraction of the intrinsic correlation between geothermal activity and earthquake occurrence. Attached Figure Description

[0049] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0050] Figure 1 This is a schematic diagram of the analysis process for the symbiotic mechanism of geothermal energy and earthquakes provided in an embodiment of the present invention;

[0051] Figure 2 The geological model diagram provided in the embodiment of the present invention is shown in (a) as a schematic diagram of the three-dimensional geological model and (b) as a cross-sectional view of the three-dimensional model in the N–S direction.

[0052] Figure 3 The following are schematic diagrams of numerical simulation results provided in the embodiments of the present invention: (a) is a temperature simulation result diagram, (b) is an equivalent stress simulation result diagram, (c) is a shear stress simulation result diagram, and (d) is a distance distribution schematic diagram.

[0053] Figure 4 The temperature field and stress field results provided in the embodiments of the present invention are shown in the following cross-sectional diagrams: (a) is a cross-sectional diagram of the temperature field in the N-S direction, (b) is a cross-sectional diagram of the equivalent stress in the N-S direction, and (c) is a cross-sectional diagram of the shear stress in the N-S direction.

[0054] Figure 5 The following is a comparison diagram of the temperature curves provided in the embodiments of the present invention and the measured temperature curves in the wells. (a) is the geothermal curve of well C-2 compared with the measured temperature curve and the simulation temperature curve, and (b) is the geothermal curve of well C-3 compared with the measured temperature curve and the simulation temperature curve. Detailed Implementation

[0055] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] The purpose of this invention is to provide a method, system, electronic device, and storage medium for analyzing the symbiotic mechanism of geothermal energy and earthquakes, and to solve the problems of traditional models being unable to analyze the interaction between actual geothermal resources and earthquake disasters, as well as the over-reliance on idealized theoretical models.

[0057] 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.

[0058] Figure 1 This is a schematic diagram of the analysis process for the symbiotic mechanism of geothermal energy and earthquakes provided in an embodiment of the present invention, as shown below. Figure 1 As shown, this invention provides a method for analyzing the symbiotic mechanism of geothermal and earthquake, including:

[0059] Step 100: Perform a three-dimensional joint inversion on the pre-collected electromagnetic and gravity data to obtain a three-dimensional resistivity and density model;

[0060] Step 200: Divide the three-dimensional resistivity and density model into several computational domain grids;

[0061] Step 300: Add fluid field, heat transfer field, deformation field, heat source attributes, thermal property parameters, and mechanical parameters to each of the partitioned computational domain meshes to obtain attribute meshes;

[0062] Step 400: Add boundary conditions to the fluid field, heat transfer field, and deformation field of each attribute mesh to obtain the simulation mesh;

[0063] Step 500: Add a reference temperature to the simulation mesh according to its distribution location to obtain a thermal-fluid-structure interaction model;

[0064] Step 600: Simulate the thermo-fluid-solid coupling model under different heat source conditions to obtain the temperature field and strain field within the Earth's crust;

[0065] Step 700: Using GIS spatial analysis technology, the spatial distribution data of the temperature field within the Earth's crust, the strain field within the Earth's crust, and the surface geothermal resources and underground seismic hazards are overlaid, compared, and analyzed for spatial coupling relationships to obtain the results of the geothermal-seismic coupling relationship analysis.

[0066] Specifically, a three-dimensional joint inversion is performed on the pre-acquired electromagnetic and gravity data to obtain a three-dimensional resistivity and density model, including:

[0067] The electromagnetic data is subjected to three-dimensional MT inversion to obtain the MT inversion results; the objective function of the three-dimensional MT inversion is: ;in, ; The objective function value for the three-dimensional MT inversion; Fit a functional to the data; Represents data type, A value of 1 indicates MT. The value 2 represents gravity; This is the model parameter vector; As a regularization factor; For the model's stable functional; For constraint terms;

[0068] The MT inversion results are transformed into a structural reference model using a method for converting prior physical property information; the expression of the structural reference model includes: , ;in, The fitting functional is for the electromagnetic data; This is a regularization factor for the electromagnetic data; This is a model parameter vector for the electromagnetic data; The objective function value transformed from the structural reference model; This is the parameter vector for converting the electromagnetic model into a gravity model; For the prior rock physical property correlation function of density and resistivity;

[0069] The structural reference model is added to a preset wide-range constraint, and a three-dimensional gravity joint inversion is performed on the gravity data under the wide-range constraint to obtain the gravity inversion result; the calculation formula for the three-dimensional gravity inversion is: ;in, The gravity inversion result is as described; The fitting functional is given for the gravity data; This is a model parameter vector for the gravity data; This is a regularization factor for the gravity data;

[0070] The MT inversion results and the gravity inversion results are iterated to obtain the three-dimensional resistivity and density model.

[0071] Furthermore, the three-dimensional resistivity and density model is divided into several computational domain grids, including:

[0072] Based on the collected geological information, the three-dimensional resistivity and density model is divided into different computational domain blocks using interpolation functions;

[0073] Define the geological structure of each computational domain block; the geological structure includes: thickness, geometry, and lithology;

[0074] Each computational domain block is divided into tetrahedral meshes using the finite element method to obtain several computational domain meshes.

[0075] Specifically, the thermophysical parameters include: density, thermal conductivity, heat generation rate, constant pressure heat capacity, coefficient of thermal expansion, and specific heat rate; the mechanical parameters include: Young's modulus, Poisson's ratio, porosity, and permeability.

[0076] Further, boundary conditions are added to the fluid field, heat transfer field, and deformation field of each attribute mesh to obtain a simulation mesh, including:

[0077] The inlet of the fluid field is set to a head of 15 km, the outlet of the fluid field is set to a head of 6 km, the upper boundary temperature of the aquifer of the fluid field is set to 623.15 K, and the lower boundary temperature of the aquifer of the fluid field is set to 787.15 K.

[0078] The annual average surface temperature at the upper boundary of the heat transfer field is set to 293.15 K, and the lower boundary condition of the heat transfer field is set to a mantle heat flux of 40 mW / m. 2 The side boundary conditions of the heat transfer field are set to adiabatic.

[0079] The simulation mesh is obtained by setting the lower boundary of the deformation field as a fixed boundary, the upper boundary of the deformation field as a free surface, and the side boundaries of the deformation field as symmetric boundaries.

[0080] Specifically, a reference temperature is added to the simulation mesh according to its distribution location to obtain a thermal-fluid-structure interaction model, including:

[0081] The surface temperature of the upper crust of the simulation grid was set to 293.15 K;

[0082] The temperature of the lower crustal rock mass portion of the simulation grid was set to 773.15K;

[0083] The temperature of the magma portion of the simulation mesh was set to 873.15K to obtain the thermo-fluid-solid coupling model.

[0084] Furthermore, the thermo-fluid-solid coupling model was simulated under different heat source conditions to obtain the temperature field and strain field within the Earth's crust, including:

[0085] Construct the heat conduction equation; the heat conduction equation is: ;in, For effective thermal conductivity; For temperature field variables; For fluid density; The specific heat capacity at constant pressure of the fluid; The seepage velocity; As a volumetric heat source; For viscous heat dissipation;

[0086] Construct the governing equations for fluid seepage; the governing equations for fluid seepage include: , ;in, For quality source items; For permeability tensor; For fluid viscosity; Pore ​​fluid pressure; It is the acceleration due to gravity;

[0087] Construct the thermal stress control equations; the thermal stress control equations include: , , , ;in, This is the total stress tensor; It is a solid potential vector; Thermal strain; It is the linear thermal expansion coefficient; For reference temperature; Unit tensor; For stress tensor; Here is the stiffness matrix; It is a volume force;

[0088] The thermal-fluid-solid coupling model is simulated and calculated using the heat conduction equation, the fluid seepage equation, and the thermal stress equation to obtain the temperature field and strain field within the Earth's crust.

[0089] Specifically, a method for analyzing the coexistence mechanism of geothermal and seismic activity based on multiphysics-fluid-solid coupled numerical simulation is proposed. This method obtains detailed crustal resistivity and density structure through three-dimensional joint inversion of electromagnetic (MT) and gravity data, and constructs a numerical simulation geometric model. The computational domain is divided and meshed based on geological information, and material properties, thermal properties, and mechanical parameters are added. Boundary conditions for heat transfer, fluid, and deformation fields are set to form a coupled thermal-fluid-solid model. Simulations of temperature and stress fields under different heat sources reveal the patterns and causes of geothermal and seismic activity, and explore the deep-seated driving mechanism of the coexistence of geothermal resources and seismic activity. Specific implementation methods include:

[0090] S1: Based on the resistivity model, the actual underground stratigraphic structure (undulations, etc.) is obtained. Then, by combining the density model and surface geological information, different lithologies are added to the above structure to finally obtain an underground geological model that fits the actual situation. Electromagnetic and gravity data are used for three-dimensional joint inversion to obtain a three-dimensional resistivity and density model at the crustal scale. This model, which highly matches the actual geological conditions, is used as the geometric model for numerical simulation.

[0091] S2: Based on the collected geological information, the geometric model is divided into different computational domains using interpolation functions, and the computational domains are meshed using the finite element method;

[0092] S3: Add corresponding material properties to each computational domain, namely, divide it into porous medium heat transfer field, fluid field and solid deformation field, as well as different heat source properties (such as magma heat source and radioactive heat source), and then add the corresponding thermal and mechanical parameters of the rock layer;

[0093] S4: Add appropriate boundary conditions to the fluid field, heat transfer field and deformation field according to the actual situation;

[0094] S5: Establish coupling relationships to form a thermal-fluid-solid coupling model;

[0095] S6: Simulation calculations yielded the temperature and strain fields within the Earth's crust under different heat source conditions;

[0096] S7: By combining the spatial distribution of surface geothermal resources and underground seismic hazards, we can obtain the patterns and causes of geothermal and seismic activity, and finally obtain the correlation between the two in terms of deep control mechanisms.

[0097] Furthermore, in S1, a three-dimensional wide-range physical property constraint joint inversion is performed using electromagnetic and gravity data to obtain a crustal-scale resistivity and density model, which serves as the initial geometric model for numerical simulation. The core of this inversion method is to utilize the correlation between physical property parameters such as rock resistivity and density to constrain joint inversion, achieving complementarity between different geophysical methods. Specifically, the inversion strategy involves performing a three-dimensional MT inversion on the electromagnetic data to obtain the MT inversion results; the objective function of the three-dimensional MT inversion is: ;in, The objective function value for the MT inversion; Fit a functional to the data; i represents the data type (MT or gravity). This is the model parameter vector; As a regularization factor; For the model's stable functional; For the constraint term, Gramian constraint is used, which is expressed as: ;in, For Gramian constraint coupling terms; For the penalty function constraint term; The weight coefficients of the Gramian constraint terms are adaptively adjusted using a decay strategy. These are the weighting coefficients of the penalty function term;

[0098] The MT inversion results are transformed into a structural reference model using prior physical property information to guide subsequent joint inversion of gravity data. The calculation formula is as follows: ;in, This is the model parameter vector for electromagnetic data; For the prior rock physical property correlation function of density and resistivity;

[0099] The above structural reference model is added to a wide-range constraint, and then a three-dimensional gravity joint inversion is performed to obtain the gravity inversion result; the calculation formula for the three-dimensional gravity inversion is: ;in, The gravity inversion result is as described; The fitting functional for gravity data; This is the model parameter vector for gravity data; This is a regularization factor for gravity data; These are the physical property constraints for Gramian constraints;

[0100] The MT inversion results are transformed and the gravity joint inversion is iterated to obtain the three-dimensional resistivity and density model.

[0101] Specifically, in S2, the COMSOL platform is used to establish the subsequent numerical simulation model. Geological information of the study area is collected, and interpolation functions are used to subdivide the coarse structure in the geometric model into undulating layers or irregular blocks to simulate the actual underground geological structure. Thickness, geometry, and lithology are defined, resulting in... Figure 2 (a) shows the three-dimensional geological model. Figure 2 (b) The geological structure of the N–S profile is shown, and the model is then divided into different computational domains using the finite element method.

[0102] Furthermore, in S3, the thermal properties of the rock include: density, thermal conductivity, heat generation rate, constant pressure heat capacity, coefficient of thermal expansion, and specific heat rate; the mechanical properties include: Young's modulus, Poisson's ratio, porosity, and permeability.

[0103] Specifically, in S4, to simulate actual underground geological conditions, appropriate boundary conditions were set for different computational domains. The inlet of the fluid field was set to a hydraulic head of 15 km, and the outlet was set to a hydraulic head of 6 km. The upper boundary temperature of the aquifer was 623.15 K, and the lower boundary temperature was 787.15 K. The upper boundary of the porous media heat transfer field was set to the annual average surface temperature of the study area, 293.15 K, and the lower boundary condition was a mantle heat flux of 40 mW / m. 2 (Fixed base heat flow), the model side boundary conditions are adiabatic; the lower boundary of the deformation field is fixed, the upper boundary is a free surface, and the side boundaries are symmetrical boundaries.

[0104] Furthermore, in S5, during the generation of geothermal energy, the unevenly distributed temperature of the lithosphere and the thermal stress generated by the thermal structure will accumulate in the brittle layer of the middle and upper crust until an earthquake occurs. Therefore, this relationship is used to realize the multi-physics coupling of heat, fluid and solid. Considering thermal expansion, different reference temperatures are set: 293.15K for the upper crust, 773.15K for the lower crust rock mass, and 873.15K for the magma.

[0105] Specifically, in S6, the actual underground conditions are simulated to obtain the temperature distribution and thermal strain generated by different heat sources under steady-state conditions. The specific steps are as follows: the temperature distribution is calculated considering conduction and convection, and the thermal strain is calculated using the coefficient of thermal expansion. By introducing thermal strain as the "initial strain" into the equations of elasticity, the stress tensor and equivalent stress can be obtained. Specific formulas include:

[0106] 1) Heat conduction equation (porous medium, steady state):

[0107]

[0108] This equation describes the thermal transport process of a saturated fluid in a porous medium, where... It is the effective thermal conductivity (considering both solids and fluids). It is the fluid density. It is the specific heat capacity of a fluid at constant pressure. It is the seepage velocity. It is a temperature field variable. It is a volumetric heat source (considering magma heat sources and radioactive heat sources). This is viscous heat dissipation, which can be ignored in most practical groundwater and geothermal modeling. Furthermore, under steady-state conditions:

[0109]

[0110] 2) Fluid seepage equation governing equation:

[0111] Mass conservation equation for porous media flow:

[0112]

[0113] This equation describes the conservation of local fluid mass, that is, the fluid entering per unit volume is in equilibrium with the fluid source term, where... It is the fluid density. It is the seepage velocity. These are mass source items (such as the generation and consumption of fluids);

[0114] Darcy's Law:

[0115]

[0116] This equation describes how a fluid flows in a porous medium due to pressure gradients and gravity, where, It is the permeability tensor. It is fluid viscosity. It is pore fluid pressure. It is the fluid density. It is the acceleration due to gravity. In addition, the model assumes that the fluid is incompressible, isothermal, and laminar.

[0117] 3) Thermodynamic Stress Control Equation (Solid Mechanics):

[0118] The governing equations are those for small-deformation linear elasticity, considering thermal expansion and strain, and the stress-strain relationship is as follows:

[0119]

[0120]

[0121]

[0122] Force balance equations:

[0123]

[0124] in, It is a solid potential vector. It is a volume force, mainly gravity.

[0125] Furthermore, Figure 3 (a) to Figure 3 (c) The temperature field, equivalent stress field, and shear stress obtained using the above model are shown respectively. It can be seen that the temperature field changes significantly mainly in the brittle-ductile transition zone around 10 km and near the Moho surface, resulting in large equivalent stress. Earthquakes also tend to occur in these corresponding locations. Figure 4 (a) to Figure 4 As shown in (b). Meanwhile, the equivalent stress generated in the northern part of the 10km depth study area is higher than that in the southern part, while the southern part generates a larger equivalent stress at the Moho surface depth. Reference Figure 3 (c) and Figure 3 (d) Shear stress results show that at a depth of 10 km, earthquakes are mostly located in compressive zones, while hot springs and geothermal wells (star-shaped and red rectangles) are situated at the boundary between compressive and extensional zones. Furthermore, the shape of the extensional zones aligns with the strike of the Yalu River fault. The cross-sectional view also shows that earthquakes in the northern part of the study area are all located in compressive zones (see reference). Figure 4 It can be clearly seen from the temperature curve (reference). Figure 5 ), within the study area C-2 (reference) Figure 5 (a) and C-3 well (reference) Figure 5(b) The simulated temperature curve, the measured temperature curve, and the temperature curve calculated by previous researchers show a high degree of overlap, proving that the simulation results have strong reliability and credibility. The simulation results demonstrate that when a heat source generates heat, it causes uneven temperature distribution in the lithosphere, affecting the stress state in the crust. Compared to radioactive heat sources in rock strata, magmatic heat sources generate higher thermal stress and have a greater impact on the thermal state. The presence of aquifers enhances the compressive stress above the brittle-ductile transition zone, which helps stress accumulate until an earthquake occurs. The enhancement of tensile stress around hot springs and geothermal wells helps heat rise to the shallow surface and generate thermal anomalies. The above analysis reveals the dynamic coupling mechanism between "heat source-stress-earthquake", characterizes the symbiotic relationship between geothermal energy and earthquakes, and provides a theoretical basis for geothermal resource development and earthquake risk assessment.

[0126] As an optional implementation, this embodiment also provides a geothermal and earthquake symbiotic mechanism analysis system, including:

[0127] The joint inversion model is used to perform a three-dimensional joint inversion of pre-acquired electromagnetic and gravity data to obtain a three-dimensional resistivity and density model.

[0128] The mesh generation module is used to divide the three-dimensional resistivity and density model into several computational domain meshes;

[0129] The attribute addition module is used to add fluid field, heat transfer field, deformation field, heat source attributes, thermal property parameters and mechanical parameters to each of the partitioned computational domain meshes to obtain attribute meshes;

[0130] The boundary condition adding module is used to add boundary conditions to the fluid field, heat transfer field, and deformation field of each attribute mesh to obtain the simulation mesh;

[0131] The reference temperature addition module is used to add reference temperatures to the simulation mesh according to the distribution location of the simulation mesh to obtain a thermal-fluid-structure interaction model.

[0132] The simulation calculation module is used to simulate and calculate the thermo-fluid-solid coupling model under different heat source conditions to obtain the temperature field and strain field inside the Earth's crust.

[0133] The correlation analysis module is used to perform overlay comparison and spatial coupling relationship analysis on the spatial distribution data of the temperature field, strain field, surface geothermal resources and underground seismic hazards in the Earth's crust using GIS spatial analysis technology, so as to obtain the analysis results of the coupling relationship between geothermal and seismic forces.

[0134] As an optional implementation, this embodiment also provides an electronic device, including: at least one processor, and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, the instructions being executed by the processor to enable the processor to perform the aforementioned method for analyzing geothermal and seismic symbiotic mechanisms.

[0135] As an optional implementation, this embodiment also provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the aforementioned method for analyzing geothermal and seismic symbiotic mechanisms.

[0136] The beneficial effects of this invention are as follows:

[0137] This invention performs three-dimensional joint inversion of electromagnetic and gravity data, making the model more consistent with the actual underground geological structure characteristics, freeing it from the idealized constraints of theoretical models, and improving the accuracy of simulation results. Through attribute addition, boundary condition addition, reference temperature addition, simulation calculation, and correlation analysis, a complete theoretical system of deep control and symbiosis of seismic activity and geothermal resources is constructed, realizing the extraction of the intrinsic correlation between geothermal activity and earthquake occurrence.

[0138] The various embodiments in this specification are described in a progressive manner, with each embodiment focusing on the differences from other embodiments. The same or similar parts between the various embodiments can be referred to each other.

[0139] This document uses specific examples 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. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for analyzing the symbiotic mechanism of geothermal energy and earthquakes, characterized in that, include: Three-dimensional joint inversion was performed on the pre-collected electromagnetic and gravity data to obtain a three-dimensional resistivity and density model; The three-dimensional resistivity and density model is divided into several computational domain grids; Fluid field, heat transfer field, deformation field, heat source attributes, thermal property parameters, and mechanical parameters are added to each of the partitioned computational domain meshes to obtain attribute meshes; Boundary conditions are added to the fluid field, heat transfer field, and deformation field of each attribute mesh to obtain the simulation mesh; A reference temperature is added to the simulation mesh based on its distribution location to obtain a thermal-fluid-structure interaction model; The thermal-fluid-solid coupling model was simulated and calculated under different heat source conditions to obtain the temperature field and strain field within the Earth's crust. Using GIS spatial analysis technology, the spatial distribution data of the temperature field, strain field, surface geothermal resources, and underground seismic hazards within the Earth's crust are overlaid, compared, and analyzed for spatial coupling relationships to obtain the results of the analysis on the coupling relationship between geothermal energy and earthquakes.

2. The method for analyzing the symbiotic mechanism of geothermal energy and earthquakes according to claim 1, characterized in that, A three-dimensional joint inversion was performed on the pre-acquired electromagnetic and gravity data to obtain a three-dimensional resistivity and density model, including: The electromagnetic data is subjected to three-dimensional MT inversion to obtain the MT inversion results; the objective function of the three-dimensional MT inversion is: ;in, ; The objective function value for the three-dimensional MT inversion; Fit a functional to the data; Represents data type, A value of 1 indicates MT. The value 2 represents gravity; This is the model parameter vector; As a regularization factor; For the model's stable functional; For constraint terms; The MT inversion results are transformed into a structural reference model using a method for converting prior physical property information; the expression of the structural reference model includes: , ;in, The fitting functional is for the electromagnetic data; This is a regularization factor for the electromagnetic data; This is a model parameter vector for the electromagnetic data; The objective function value transformed from the structural reference model; This is the parameter vector for converting the electromagnetic model into a gravity model; For the prior rock physical property correlation function of density and resistivity; The structural reference model is added to a preset wide-range constraint, and a three-dimensional gravity joint inversion is performed on the gravity data under the wide-range constraint to obtain the gravity inversion result; the calculation formula for the three-dimensional gravity inversion is: ;in, The gravity inversion result is as described; The fitting functional is given for the gravity data; This is a model parameter vector for the gravity data; This is a regularization factor for the gravity data; The MT inversion results and the gravity inversion results are iterated to obtain the three-dimensional resistivity and density model.

3. The method for analyzing the symbiotic mechanism of geothermal energy and earthquakes according to claim 2, characterized in that, The three-dimensional resistivity and density model is divided into several computational domain grids, including: Based on the collected geological information, the three-dimensional resistivity and density model is divided into different computational domain blocks using interpolation functions; Define the geological structure of each computational domain block; the geological structure includes: thickness, geometry, and lithology; Each computational domain block is divided into tetrahedral meshes using the finite element method to obtain several computational domain meshes.

4. The method for analyzing the symbiotic mechanism of geothermal energy and earthquakes according to claim 3, characterized in that, The thermophysical parameters include: density, thermal conductivity, heat generation rate, constant pressure heat capacity, coefficient of thermal expansion, and specific heat rate; the mechanical parameters include: Young's modulus, Poisson's ratio, porosity, and permeability.

5. The method for analyzing the symbiotic mechanism of geothermal energy and earthquakes according to claim 4, characterized in that, Boundary conditions are added to the fluid field, heat transfer field, and deformation field of each attribute mesh to obtain a simulation mesh, including: The inlet of the fluid field is set to a head of 15 km, the outlet of the fluid field is set to a head of 6 km, the upper boundary temperature of the aquifer of the fluid field is set to 623.15 K, and the lower boundary temperature of the aquifer of the fluid field is set to 787.15 K. The annual average surface temperature at the upper boundary of the heat transfer field is set to 293.15 K, and the lower boundary condition of the heat transfer field is set to a mantle heat flux of 40 mW / m. 2 The side boundary conditions of the heat transfer field are set to adiabatic. The simulation mesh is obtained by setting the lower boundary of the deformation field as a fixed boundary, the upper boundary of the deformation field as a free surface, and the side boundaries of the deformation field as symmetric boundaries.

6. The method for analyzing the symbiotic mechanism of geothermal energy and earthquakes according to claim 5, characterized in that, Based on the distribution location of the simulation mesh, a reference temperature is added to the simulation mesh to obtain a thermal-fluid-structure interaction model, including: The surface temperature of the upper crust of the simulation grid was set to 293.15 K; The temperature of the lower crustal rock mass portion of the simulation grid was set to 773.15K; The temperature of the magma portion of the simulation mesh was set to 873.15K to obtain the thermo-fluid-solid coupling model.

7. The method for analyzing the symbiotic mechanism of geothermal energy and earthquakes according to claim 6, characterized in that, The thermo-fluid-structure interaction model was simulated under different heat source conditions to obtain the temperature field and strain field within the Earth's crust, including: Construct the heat conduction equation; the heat conduction equation is: ;in, For effective thermal conductivity; For temperature field variables; For fluid density; The specific heat capacity at constant pressure of the fluid; The seepage velocity; As a volumetric heat source; For viscous heat dissipation; Construct the governing equations for fluid seepage; the governing equations for fluid seepage include: , ;in, For quality source items; For permeability tensor; For fluid viscosity; Pore ​​fluid pressure; It is the acceleration due to gravity; Construct the thermal stress control equations; the thermal stress control equations include: , , , ;in, This is the total stress tensor; It is a solid potential vector; Thermal strain; It is the linear thermal expansion coefficient; For reference temperature; Unit tensor; For stress tensor; Here is the stiffness matrix; It is a volume force; The thermal-fluid-solid coupling model is simulated and calculated using the heat conduction equation, the fluid seepage equation, and the thermal stress equation to obtain the temperature field and strain field within the Earth's crust.

8. A system for analyzing the symbiotic mechanism of geothermal energy and earthquakes, characterized in that, include: The joint inversion model is used to perform a three-dimensional joint inversion of pre-acquired electromagnetic and gravity data to obtain a three-dimensional resistivity and density model. The mesh generation module is used to divide the three-dimensional resistivity and density model into several computational domain meshes; The attribute addition module is used to add fluid field, heat transfer field, deformation field, heat source attributes, thermal property parameters and mechanical parameters to each of the partitioned computational domain meshes to obtain attribute meshes; The boundary condition adding module is used to add boundary conditions to the fluid field, heat transfer field, and deformation field of each attribute mesh to obtain the simulation mesh; The reference temperature addition module is used to add reference temperatures to the simulation mesh according to the distribution location of the simulation mesh to obtain a thermal-fluid-structure interaction model. The simulation calculation module is used to simulate and calculate the thermo-fluid-solid coupling model under different heat source conditions to obtain the temperature field and strain field inside the Earth's crust. The correlation analysis module is used to perform overlay comparison and spatial coupling relationship analysis on the spatial distribution data of the temperature field, strain field, surface geothermal resources and underground seismic hazards in the Earth's crust using GIS spatial analysis technology, so as to obtain the analysis results of the coupling relationship between geothermal and seismic forces.

9. An electronic device, characterized in that, include: At least one processor, and a memory communicatively connected to the processor; wherein the memory stores instructions executable by the processor, the instructions being executed by the processor to enable the processor to perform a method for analyzing geothermal and seismic symbiotic mechanisms according to any one of claims 1 to 7.

10. A non-transitory computer-readable storage medium storing computer instructions, characterized in that, The computer instructions are used to cause the computer to execute the geothermal and earthquake symbiosis analysis method according to any one of claims 1 to 7.

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