A geothermal caprock multi-factor coupling evaluation system

Abstract

The application discloses a geothermal caprock multi-factor coupling evaluation system, which aims to solve the problems of low standardization degree of existing evaluation manual operation process, lack of unified engineering architecture of multi-factor coupling and insufficient result visualization. The application automatically executes caprock comprehensive evaluation on a unified platform through a data acquisition module, a single-factor evaluation module, a coupling model construction module, a coupling score calculation module, a comprehensive evaluation module and a result output module. The system completes single-factor scoring based on basic data, constructs and calculates the scores of four coupling subsystems of lithology-diagenesis-physical property, structure-mechanics-integrity, thickness-continuity and fluid-pressure-temperature, quantifies the coupling relationship between the subsystems by using a cross influence matrix to obtain the final score, and outputs the comprehensive score and the visualized result after weighting. The application realizes the integration and automation of the evaluation process, supports the engineering landing of complex coupling models, and improves the result visualization and decision support capability.

Description

Technical Field

[0001] This invention belongs to the field of geothermal resource exploration and engineering information technology, and in particular relates to a multi-factor coupled evaluation system for geothermal caprock. Background Technology

[0002] With the advancement of medium-deep geothermal resource development and the coordinated development of oil and gas and geothermal resources, the need for rapid and accurate quantitative evaluation of caprock sealing performance is becoming increasingly urgent. Currently, the traditional evaluation methods widely relied upon in this field have several significant drawbacks, severely restricting the efficiency, accuracy, and engineering applicability of the evaluation work.

[0003] Traditional caprock evaluation schemes typically rely on manual methods to collect heterogeneous data from multiple sources, such as seismic interpretation, well logging analysis, and core experiments, for single-factor scoring and subsequent weighted calculations. Throughout the manual evaluation process, data acquisition, preprocessing, single-factor calculation, coupled analysis, and result visualization require switching between different software programs, leading to difficulties in data transfer and potential errors during multiple manual operations, thus affecting the repeatability and reliability of the evaluation results. Furthermore, caprock sealing performance is the result of complex coupling of multiple factors, including lithology and diagenesis and physical properties, tectonic activity and mechanical integrity, formation thickness and spatial continuity, and fluid pressure and temperature fields. There is a lack of software tools to dynamically transfer and iteratively solve these parameters within a unified and scalable computational framework. The absence of a complete system platform with a configurable and scalable architecture to support flexible loading, version management, and reuse across multiple projects for evaluation models and parameters under different basin or geological conditions hinders the accumulation of technical experience and long-term maintenance and upgrades. Finally, traditional methods are relatively simple in terms of result presentation, lacking visualization tools such as plan views and multi-dimensional cross-sectional views that can intuitively reflect the spatial distribution characteristics of caprock sealing and thermal insulation performance. As a result, it is difficult for engineering technicians to quickly and clearly identify the caprock's advantageous areas and risk-vulnerable zones in the target area, thus affecting the efficiency and effectiveness of development scheme optimization and risk management decisions. Summary of the Invention

[0004] To address the aforementioned technical problems, this invention proposes a multi-factor coupled evaluation system for geothermal cap layers, thereby resolving the issues present in the prior art.

[0005] Firstly, to achieve the above objectives, the present invention provides a multi-factor coupled evaluation system for geothermal cap layers, comprising: The data acquisition module is used to acquire basic data of the geothermal cap layer. The basic data includes data characterizing the lithological characteristics, physical properties, geometric morphology, tectonic development, geostress and mechanical characteristics, sedimentary evolution characteristics, temperature field characteristics, fluid characteristics, and drainage conditions of the geothermal cap layer. The single-factor evaluation module is used to receive the basic data obtained by the data acquisition module, and perform single-factor evaluation based on the basic data to obtain multiple single-factor evaluation results. The coupled model construction module is used to receive the multiple single-factor evaluation results output by the single-factor evaluation module, and call the four pre-built coupled subsystem calculation units to calculate the initial scores of the lithology-diagenesis-physical property subsystem, the structure-mechanics-integrity subsystem, the thickness-continuity subsystem, and the fluid-pressure-temperature subsystem based on the single-factor evaluation results, respectively. The coupling score calculation module is used to receive the initial score, including a storage unit storing a 4×4 cross-influence matrix, and to perform coupling calculation on the scores of each subsystem based on the matrix to obtain the final score; The comprehensive evaluation module is used to receive the final scores of each coupled subsystem output by the coupling score calculation module, and perform weighted calculations according to preset weights to obtain the comprehensive score and sealing level of the geothermal cap layer. The result output module is used to receive the comprehensive score and sealing level of the geothermal cap layer output by the comprehensive evaluation module, and output the comprehensive score, sealing level and evaluation results of each coupled subsystem of the geothermal cap layer.

[0006] Optionally, the data acquisition module includes: The multi-source data import unit is used to import basic data from seismic interpretation data, well logging data, geological databases, and structured data files; The historical observation data interface unit is used to acquire caprock sealing observation data of the target area, including formation breakthrough pressure, fluid leakage records, and known sealing level labels, as data input for system self-optimization; The data standardization and gridding processing unit is used to perform coordinate transformation, physical unit conversion, outlier detection and processing on the imported data, and to perform spatial gridding processing on the discrete well point data based on the interpolation algorithm.

[0007] Optionally, the single-factor evaluation module includes: The scoring function library calling unit is used to call a preset scoring function library, which contains standardized scoring functions for lithology type, caprock thickness, permeability and thermal conductivity. The thickness score adopts the Sigmoid function form, the permeability score adopts the logarithmic scaling function form, and the thermal conductivity score adopts the Gaussian function form. The single-factor calculation execution unit is used to call the scoring function to independently calculate the lithological data, thickness data, permeability data and thermal conductivity data in the gridded data, and normalize the calculation results to the [0,1] interval to generate the corresponding single-factor score.

[0008] Optionally, the coupling model construction module includes: The lithology-diagenesis-physical property subsystem unit is used to calculate the lithology-diagenesis-physical property subsystem score after diagenesis correction based on the initial permeability correction of the diagenesis degree index; wherein the initial score calculated by the subsystem unit has not yet considered the cross-system dynamic interaction between subsystems, and the cross-system dynamic interaction is realized by the coupling score calculation module through the cross-influence matrix; The structure-mechanics-integrity subsystem unit is used to calculate crack risk and plastic self-healing factor based on the effective stress and brittleness index characterizing mechanical properties, evaluate the mechanical integrity of the caprock, and obtain the structure-mechanics-integrity subsystem score; wherein, the plastic self-healing factor It characterizes the ability of caprock to recover partial integrity through plastic deformation mechanisms such as creep and pressure solution after tectonic stress relaxation. It is a dimensionless parameter with a value range of [0,1], and is determined by the rock clay content, temperature and stress history. The thickness-continuity subsystem unit is used to calculate the thickness-continuity subsystem score after coupling thickness with effective continuity, based on the caprock thickness and fault density, which characterizes the degree of geometric continuity cutting. The fluid-pressure-temperature subsystem unit is used to calculate the pore overpressure value based on permeability and deposition rate, and to calculate the fluid-pressure-temperature subsystem score in combination with geothermal gradient.

[0009] Optionally, the coupling score calculation module includes: The cross-influence matrix construction unit is used to construct a cross-influence matrix based on a preset geological interaction rule base or statistical analysis of historical data, wherein the matrix elements represent the unidirectional influence coefficients between each subsystem. It is a 4×4 square matrix, and its elements are... Indicates the first The subsystem for the first Cross-system influence coefficient of each subsystem, diagonal elements This indicates that the internal coupling of the subsystem has been reflected through the initial score calculation.

[0010] The matrix normalization processing unit is used to perform row sum constraint processing on the cross-influence matrix to ensure that the spectral radius of the matrix is ​​less than 1 to guarantee iterative convergence; The coupling correction calculation unit is used to take the initial scores of each coupled subsystem as an initial vector and perform iterative correction calculations on the initial vector using the normalized cross-influence matrix. The coupling correction calculation unit is configured to perform a linear correction operation, or to perform an operation that starts from the initial vector and iterates based on the cross-influence matrix until convergence.

[0011] Optionally, the comprehensive evaluation module includes: The weight configuration unit is used to receive weight coefficients for each coupled subsystem, either configured by the user or optimized by the system itself. The weighted calculation unit is used to multiply the final scores of each coupled subsystem by the corresponding weight coefficients and then sum them to obtain the comprehensive score of the geothermal cap layer. The grading unit is used to match the comprehensive score of the geothermal cover layer with a pre-stored grading threshold range to determine the sealing level.

[0012] Optionally, the result output module includes: The plan view generation unit is used to generate a planar grid map showing the spatial distribution of the comprehensive score and sealing level of the geothermal cap layer; The profile generation unit is used to generate profiles showing the changes in the scores of each coupled subsystem along a selected geological profile; The report generation unit is used to generate a formatted report file that includes the planar grid diagram, cross-sectional view, and data analysis conclusions.

[0013] Secondly, the present invention also provides a computer terminal device, comprising: One or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the module functions of the geothermal cap multi-factor coupled evaluation system in the first aspect described above.

[0014] Thirdly, the present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, it implements the module functions of the geothermal cap multi-factor coupled evaluation system in the first aspect described above.

[0015] Fourthly, the present invention also provides a computer program product, including a computer program that, when executed by a processor, implements the module functions of the geothermal cap multi-factor coupled evaluation system described in the first aspect.

[0016] Compared with the prior art, the present invention has the following advantages and technical effects: This invention provides a multi-factor coupled evaluation system for geothermal caprocks, achieving integration and automation of the geothermal caprock evaluation process. This reduces the need for switching between multiple software programs and manual operations, improving evaluation efficiency and process standardization. This invention supports the engineering implementation of complex coupled models. Through built-in four coupled subsystem models and parameterized management, the theoretical model can run stably and iteratively update in actual projects. This invention enhances the visualization and decision support capabilities of the results, visually revealing the spatial distribution and weak areas of caprock sealing and insulation performance through various forms such as plan views and cross-sectional views. This invention also incorporates thermal conductivity into the single-factor evaluation system (using standardized Gaussian function scoring), achieving quantitative processing of caprock thermal properties and comprehensively reflecting the influence of the thermal field on caprock sealing performance within the fluid-pressure-temperature subsystem, thus overcoming the shortcomings of traditional methods in the non-standardized processing of thermal conductivity parameters. This invention possesses good scalability and reusability; its modular design facilitates the loading of corresponding models and parameters according to different projects, forming a unified evaluation platform. Attached Figure Description

[0017] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an undue limitation of the invention. In the drawings: Figure 1 This is a schematic diagram of a multi-factor coupled evaluation system for geothermal cap layer according to an embodiment of the present invention. Detailed Implementation

[0018] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other. The present invention will now be described in detail with reference to the accompanying drawings and embodiments.

[0019] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0020] like Figure 1 As shown, this embodiment provides a multi-factor coupled evaluation system for geothermal cap, including: The data acquisition module is used to acquire basic data of the geothermal cap layer. The basic data includes data characterizing the lithological characteristics, physical properties, geometric morphology, tectonic development, geostress and mechanical characteristics, sedimentary evolution characteristics, temperature field characteristics, fluid characteristics, and drainage conditions of the geothermal cap layer. The single-factor evaluation module is used to receive the basic data obtained by the data acquisition module, and perform single-factor evaluation based on the basic data to obtain multiple single-factor evaluation results. The coupled model construction module is used to receive the multiple single-factor evaluation results output by the single-factor evaluation module, call the four pre-built coupled subsystem calculation units, and calculate the initial scores of the lithology-diagenesis-physical property subsystem, the structure-mechanics-integrity subsystem, the thickness-continuity subsystem, and the fluid-pressure-temperature subsystem based on the single-factor evaluation results, respectively. The coupling score calculation module is used to receive the initial score, including a storage unit storing a 4×4 cross-influence matrix, and to perform coupling calculation on the scores of each subsystem based on the matrix to obtain the final score; The comprehensive evaluation module is used to receive the final scores of each coupled subsystem output by the coupling score calculation module, and perform weighted calculations according to preset weights to obtain the comprehensive score and sealing level of the geothermal cap layer. The result output module is used to receive the comprehensive score and sealing level of the geothermal cap layer output by the comprehensive evaluation module, and output the comprehensive score, sealing level and evaluation results of each coupled subsystem of the geothermal cap layer.

[0021] Optionally, the data acquisition module includes: The multi-source data import unit is used to import basic data from seismic interpretation data, well logging data, geological databases, and structured data files; The historical observation data interface unit is used to acquire caprock sealing observation data of the target area, including formation breakthrough pressure, fluid leakage records, and known sealing level labels, as data input for system self-optimization; The data standardization and gridding processing unit is used to perform coordinate transformation, physical unit conversion, outlier detection and processing on the imported data, and to perform spatial gridding processing on the discrete well point data based on the interpolation algorithm.

[0022] Optionally, the single-factor evaluation module includes: The scoring function library calling unit is used to call a preset scoring function library, which contains standardized scoring functions for lithology type, caprock thickness, permeability and thermal conductivity. The thickness score adopts the Sigmoid function form, the permeability score adopts the logarithmic scaling function form, and the thermal conductivity score adopts the Gaussian function form. The single-factor calculation execution unit is used to call the scoring function to independently calculate the lithological data, thickness data, permeability data and thermal conductivity data in the gridded data, and normalize the calculation results to the [0,1] interval to generate the corresponding single-factor score.

[0023] Optionally, the coupling model construction module includes: The lithology-diagenesis-physical property subsystem unit is used to calculate the lithology-diagenesis-physical property subsystem score after diagenesis correction based on the initial permeability correction of the diagenesis degree index; wherein the initial score calculated by the subsystem unit has not yet considered the cross-system dynamic interaction between subsystems, and the cross-system dynamic interaction is realized by the coupling score calculation module through the cross-influence matrix; The structure-mechanics-integrity subsystem unit is used to calculate crack risk and plastic self-healing factor based on the effective stress and brittleness index characterizing mechanical properties, evaluate the mechanical integrity of the caprock, and obtain the structure-mechanics-integrity subsystem score; wherein, the plastic self-healing factor It characterizes the ability of caprock to recover partial integrity through plastic deformation mechanisms such as creep and pressure solution after tectonic stress relaxation. It is a dimensionless parameter with a value range of [0,1], and is determined by the rock clay content, temperature and stress history. The thickness-continuity subsystem unit is used to calculate the thickness-continuity subsystem score after coupling thickness with effective continuity, based on the caprock thickness and fault density, which characterizes the degree of geometric continuity cutting. The fluid-pressure-temperature subsystem unit is used to calculate the pore overpressure value based on permeability and deposition rate, and to calculate the fluid-pressure-temperature subsystem score in combination with geothermal gradient.

[0024] Optionally, the coupling score calculation module includes: The cross-influence matrix construction unit is used to construct a cross-influence matrix based on a preset geological interaction rule base or statistical analysis of historical data, wherein the matrix elements represent the unidirectional influence coefficients between each subsystem. It is a 4×4 square matrix, and its elements are... Indicates the first The subsystem for the first Cross-system influence coefficient of each subsystem, diagonal elements This indicates that the internal coupling of the subsystem has been reflected through the initial score calculation.

[0025] The matrix normalization processing unit is used to perform row sum constraint processing on the cross-influence matrix to ensure that the spectral radius of the matrix is ​​less than 1 to guarantee iterative convergence; The coupling correction calculation unit is used to take the initial scores of each coupled subsystem as an initial vector and perform iterative correction calculations on the initial vector using the normalized cross-influence matrix. The coupling correction calculation unit is configured to perform a linear correction operation, or to perform an operation that starts from the initial vector and iterates based on the cross-influence matrix until convergence.

[0026] Optionally, the comprehensive evaluation module includes: The weight configuration unit is used to receive weight coefficients for each coupled subsystem, either configured by the user or optimized by the system itself. The weighted calculation unit is used to multiply the final scores of each coupled subsystem by the corresponding weight coefficients and then sum them to obtain the comprehensive score of the geothermal cap layer. The grading unit is used to match the comprehensive score of the geothermal cover layer with a pre-stored grading threshold range to determine the sealing level.

[0027] Optionally, the result output module includes: The plan view generation unit is used to generate a planar grid map showing the spatial distribution of the comprehensive score and sealing level of the geothermal cap layer; The profile generation unit is used to generate profiles showing the changes in the scores of each coupled subsystem along a selected geological profile; The report generation unit is used to generate a formatted report file that includes the planar grid diagram, cross-sectional view, and data analysis conclusions.

[0028] In this embodiment, a computer terminal device is provided, including: One or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors implement the module functions of the above-mentioned geothermal cap multi-factor coupled evaluation system.

[0029] In this embodiment, a computer-readable storage medium is also provided, on which a computer program is stored. When the computer program is executed by a processor, it implements the module functions of the above-mentioned multi-factor coupled evaluation system for geothermal cap layer.

[0030] In this embodiment, a computer program product is also provided, including a computer program that, when executed by a processor, implements the module functions of the aforementioned multi-factor coupled evaluation system for geothermal cap layer.

[0031] Example 1: System Overall Architecture The multi-factor coupled evaluation system for geothermal cap layers in this invention can be deployed on servers or cloud platforms of geological companies or research institutes, and adopts a layered architecture. Data layer: includes geological database, well logging database and project file storage, used to store lithology, well logging, seismic interpretation results and historical engineering data; Business logic layer: Implements the specific logic of the data acquisition module, single-factor evaluation module, coupled model construction module, coupled score calculation module, and comprehensive evaluation module; Presentation layer: Provides users with a data management, parameter configuration, and result visualization interface through a web client or desktop client.

[0032] Users can log in to the system, select the target area or target well on the interface, configure model parameters and running mode, submit the task, and the system will automatically complete the calculation in the background and push and display the results after the calculation is completed.

[0033] Example 2: Module Function Implementation The data acquisition module interfaces with existing geological information systems to read caprock-related data from databases or files; it performs unified conversion of coordinates from different sources and automatically identifies and converts units. This module also includes a data gridding unit, which uses Kriging interpolation or inverse distance weighting algorithms to uniformly grid discrete wellpoint data (such as well logging interpretation results), ensuring that subsequent coupled calculations are performed on a unified grid cell. Simultaneously, the historical observation data interface unit is responsible for reading historical case data from known geothermal fields as a dataset for model training and calibration.

[0034] Single-factor evaluation module: Converts the input physical quantity into a dimensionless score in the interval [0,1].

[0035] Before calculation, the module first loads the parameter definition table: feature thickness. (Regional statistical average, generally taken as 50-200m), reference permeability (Take the lower limit of typical permeability of mudstone, such as...) mD), diagenetic compaction coefficient (0.1-0.5), Crack Risk Sensitivity Coefficient (0.2-0.5). The module has a built-in standardized scoring function library, specifically including: (1) Thickness scoring uses the Sigmoid function: ,in (2) The permeability score uses a logarithmic scaling function: (2) Characteristic thickness; ,in (3) The thermal conductivity score uses a Gaussian function as a reference permeability. ,in (4) The lithological score is based on a weighted sum of permeability, porosity, and clay content. In addition, the module generates a basic score for structural stability based on fault interpretation data, structural curvature properties, effective stress, and brittleness index. The original continuity score is generated based on the continuity of the cover layer distribution and the degree of fault cutting. The module supports batch calculations by grid cell and outputs single-factor score vectors. And the basic scoring quantity for use by coupled subsystems.

[0036] The parameters of the single-factor evaluation formula are explained below: Thickness score (dimensionless); The actual thickness of the capping layer (m); Characteristic thickness (m); This is the slope control parameter for the Sigmoid curve (m, the smaller the value, the steeper the curve). It is the base of the natural logarithm; Permeability score (dimensionless); For measured or interpreted permeability (mD); Reference penetration threshold (mD); Permeability penalty coefficient (dimensionless); Thermal conductivity score (dimensionless); The measured thermal conductivity is (W / (m·K)). The optimal thermal conductivity is (W / (m·K)). For thermal conductivity tolerance parameter (W / (m·K)); Lithological basis scoring (dimensionless); Porosity score (dimensionless); Scoring for clay content (dimensionless); , , The corresponding weights (dimensionless) are permeability, porosity, and clay content. To construct a stability-based score (dimensionless); This is the original continuous score (dimensionless). The module supports batch calculation by grid cell and outputs single-factor score vectors. .

[0037] The coupled model building module calculates the initial score vector based on the four subsystem models. Specifically, this includes: (1) Lithology-Diagenesis-Physical Properties Subsystem (LD): Based on depth-temperature-time coupling functions (e.g., Arrhenius-type diagenetic dynamics equations) ,in Pre-exponential factor, For activation energy, The gas constant is... The absolute temperature of the strata. For geological time, The diagenesis index is calculated using the time index. And adjust the permeability accordingly. Final score ; (2) Structure-Mechanics-Integrity Subsystem (SM): Calculating crack risk based on effective stress and brittleness index and plastic self-healing factors (For example ,in Clay content, For maximum reference clay content, For healing time, (Feature recovery time constant), final score To ensure the score is non-negative; (3) Thickness-Continuity Subsystem (TC): The continuity score is obtained by cutting geometric continuity based on fault density. (For example ), final score Note: The fault density here only quantifies geometric discontinuity (fault density characterizing the degree of geometric cutting, calculated using fault length density). ,in The fault length is... To evaluate the area of ​​the region, unlike the quantified mechanical fracturing risk (fault density characterizing the degree of mechanical fracturing, calculated using activity weighting) in the SM subsystem, this is different. ,in (This refers to the fault activity coefficient). The two have different physical meanings, but they can be derived from the same fault interpretation data and are complementary rather than redundant. (4) Fluid-Pressure-Temperature Subsystem (FPT): Based on the effective deposition rate and total permeability, an overpressure calculation model is used (e.g., the Darcy flow and loading rate balance equation). ,in For the deposition rate, For penetration rate, For fluid viscosity, Overpressure, This is the length of the drainage path. Calculate pore overpressure (for deposition time) Final score ,in This is the overpressure gain coefficient (dimensionless), distinct from the fluid viscosity used in overpressure calculations. When the calculated result is greater than 1, the value is set to 1. The module output contains an initial vector containing the scores of the four subsystems mentioned above. .

[0038] The following is a supplementary explanation of the formula parameters for the coupled subsystem: is a diagenetic degree index (dimensionless). The effective permeability (mD) after diagenetic correction. Initial permeability (mD); Score the LD subsystem (dimensionless); Lithological basis scoring (dimensionless); A sensitivity index for penetration rate correction (dimensionless). Score the SM subsystem (dimensionless). To construct a stability-based score (dimensionless); The crack risk index is dimensionless. , where is the crack risk sensitivity coefficient (dimensionless). The original continuity score (dimensionless); The effective continuity score after fault correction (dimensionless). The fault cutting influence coefficient (dimensionless); Fault length density is used to characterize the degree of geometric cutting. Active weighted fault density to characterize the degree of mechanical fracturing; Continuous contribution index (dimensionless); Score for the TC subsystem (dimensionless). Score for the FPT subsystem (dimensionless); and The weights for the permeability and temperature terms are respectively (dimensionless, and usually satisfy the following conditions). ); The reference value for hydrostatic pressure is (MPa). The pore overpressure is measured in MPa. The module output is an initial vector containing the scores of the four subsystems mentioned above. .

[0039] Coupling score calculation module: First, the cross-influence matrix generation unit is based on a preset geological rule base (example rule: ① negative influence coefficient of SM on LD when tectonic activity is enhanced). ② The positive influence coefficient of FPT on SM during overpressure development ③ The negative influence coefficient of TC on FPT when continuity decreases Alternatively, covariance analysis of historical regional data can automatically generate an initial cross-influence matrix. The cross-influence matrix It is a 4×4 square matrix, and its elements are... Indicates the first The subsystem for the first Cross-system influence coefficient of each subsystem, diagonal elements This indicates that the internal coupling of the subsystem has been reflected through the initial score calculation. The cross-influence matrix... Persistent storage is performed in dedicated storage units (such as in-memory matrix objects or database tables) to support repeated calls to both fast and fine-grained evaluation modes. After matrix generation, row and constraint processing is applied to ensure that the sum of the absolute values ​​of each row's elements is less than 1 (e.g., through scaling factors). To impose constraints, Thus, the matrix spectral radius is strictly guaranteed. To satisfy the sufficient condition for iterative convergence.

[0040] In the coupled correction calculation, for the fast evaluation mode, the following steps are performed: For the refined evaluation mode, iterative calculations are performed. where the initial vector of the iteration Take as the initial score of each subsystem ,Right now .

[0041] The system monitors the convergence residuals in real time. If the residual is less than a preset threshold (e.g., 0.001) within a preset number of steps, the convergence condition is met; or, if oscillations occur, a damping factor is automatically introduced. (e.g., 0.5) Perform smooth iteration To ensure a stable final score output The parameters are defined as follows: The initial score column vectors for the four subsystems; This is the final score column vector after coupling correction; This is the cross-influence matrix; It is the identity matrix; For the first The state vector of the next iteration; This is the steady-state solution; For matrix spectral radius; is the damping factor (dimensionless, value range [0,1]).

[0042] Comprehensive evaluation module: based on weight vector Calculate the overall score The weight configuration supports two modes: (1) Expert mode: users directly set the weights; (2) Self-optimization mode: enabled when the number of historical samples meets the statistical significance requirement (e.g., more than 10 times the number of subsystems), the system calls the historical observation data interface to obtain the true closure performance of the developed cap layer (e.g., leakage / non-leakage). The closure level labels are mapped to numerical ranges (e.g., Excellent = 0.9, Good = 0.75, Average = 0.6, Poor = 0.4), and a mean squared error loss function is constructed. The gradient descent algorithm is used for automatic iterative optimization. The closure level of the classification unit is determined based on the optimized score threshold. , is the subsystem weight vector (dimensionless); Transpose it; The overall score (dimensionless); For the first Each sample in weight The predicted composite score below; For the first The true label mapping value corresponding to each sample; This is the sample index.

[0043] Results output module: Maps the overall score and subsystem score into plan view, profile view and bar chart, supports comparative analysis of multiple wells and multiple layers; at the same time, it can generate evaluation reports in PDF or Word format, and automatically insert key charts and text descriptions into the reports.

[0044] Example 3: Deployment and Application In a pilot project in a basin, this system was deployed on an internal server (configuration: Intel Xeon 16-core processor, 64GB RAM, SSD storage) and accessed via a web browser. The data scale and processing capacity are shown in Table 1.

[0045] Table 1

[0046] Users import seismic interpretation structural diagrams, wellbore structures, logging curves, and experimental analysis results. The system automatically completes data preprocessing and model calculations, and the results are shown in Table 2.

[0047] Table 2

[0048] The scores of the caprock TC and SM subsystems near the two main fault zones in the region decreased significantly (0.42–0.48 and 0.45–0.52, respectively), but the scores of the LD and FPT subsystems remained at a medium-to-high level (0.71–0.78 and 0.72–0.76, respectively). Further comparative analysis showed that in complex fault zone areas, the comprehensive score calculated by the "refined evaluation model" (iterative coupling) was on average 0.12 points lower than that of the "rapid evaluation model" (linear correction), successfully identifying three potential leakage risk points that were missed by the rapid model.

[0049] The above are merely preferred embodiments of the present invention, but the scope of protection of the present invention is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in the present invention should be included within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A multi-factor coupled evaluation system for geothermal cap layers, characterized in that, include: The data acquisition module is used to acquire basic data of the geothermal cap layer. The basic data includes data characterizing the lithological characteristics, physical properties, geometric morphology, tectonic development, geostress and mechanical characteristics, sedimentary evolution characteristics, temperature field characteristics, fluid characteristics, and drainage conditions of the geothermal cap layer. The single-factor evaluation module is used to receive the basic data obtained by the data acquisition module, and perform single-factor evaluation based on the basic data to obtain multiple single-factor evaluation results. The coupled model construction module is used to receive the multiple single-factor evaluation results output by the single-factor evaluation module, and call the four pre-built coupled subsystem calculation units to calculate the initial scores of the lithology-diagenesis-physical property subsystem, the structure-mechanics-integrity subsystem, the thickness-continuity subsystem, and the fluid-pressure-temperature subsystem based on the single-factor evaluation results, respectively. The coupling score calculation module is used to receive the initial score, including a storage unit storing a 4×4 cross-influence matrix, and to perform coupling calculation on the scores of each subsystem based on the matrix to obtain the final score; The comprehensive evaluation module is used to receive the final scores of each coupled subsystem output by the coupling score calculation module, and perform weighted calculations according to preset weights to obtain the comprehensive score and sealing level of the geothermal cap layer. The result output module is used to receive the comprehensive score and sealing level of the geothermal cap layer output by the comprehensive evaluation module, and output the comprehensive score, sealing level and evaluation results of each coupled subsystem of the geothermal cap layer.

2. The system according to claim 1, characterized in that, The data acquisition module includes: The multi-source data import unit is used to import basic data from seismic interpretation data, well logging data, geological databases, and structured data files; The historical observation data interface unit is used to acquire caprock sealing observation data of the target area, including formation breakthrough pressure, fluid leakage records, and known sealing level labels, as data input for system self-optimization; The data standardization and gridding processing unit is used to perform coordinate transformation, physical unit conversion, outlier detection and processing on the imported data, and to perform spatial gridding processing on the discrete well point data based on the interpolation algorithm.

3. The system according to claim 1, characterized in that, The single-factor evaluation module includes: The scoring function library calling unit is used to call a preset scoring function library, which contains standardized scoring functions for lithology type, caprock thickness, permeability and thermal conductivity. The thickness score adopts the Sigmoid function form, the permeability score adopts the logarithmic scaling function form, and the thermal conductivity score adopts the Gaussian function form. The single-factor calculation execution unit is used to call the scoring function to independently calculate the lithological data, thickness data, permeability data and thermal conductivity data in the gridded data, and normalize the calculation results to the [0,1] interval to generate the corresponding single-factor score.

4. The system according to claim 1, characterized in that, The coupling model construction module includes: The lithology-diagenesis-physical property subsystem unit is used to calculate the lithology-diagenesis-physical property subsystem score after diagenesis correction based on the initial permeability correction of the diagenesis degree index. The structure-mechanics-integrity subsystem unit is used to calculate crack risk and plastic self-healing factor based on the effective stress and brittleness index that characterize mechanical properties, evaluate the mechanical integrity of the caprock, and obtain the structure-mechanics-integrity subsystem score. The thickness-continuity subsystem unit is used to calculate the thickness-continuity subsystem score after coupling thickness with effective continuity, based on the caprock thickness and fault density, which characterizes the degree of geometric continuity cutting. The fluid-pressure-temperature subsystem unit is used to calculate the pore overpressure value based on permeability and deposition rate, and to calculate the fluid-pressure-temperature subsystem score in combination with geothermal gradient.

5. The system according to claim 1, characterized in that, The coupling score calculation module includes: The cross-influence matrix construction unit is used to construct a cross-influence matrix based on a preset geological interaction rule base or statistical analysis of historical data, where the matrix elements represent the unidirectional influence coefficients between each subsystem. The matrix normalization processing unit is used to perform row sum constraint processing on the cross-influence matrix to ensure that the spectral radius of the matrix is ​​less than 1 to guarantee iterative convergence; The coupling correction calculation unit is used to take the initial scores of each coupled subsystem as an initial vector and perform iterative correction calculations on the initial vector using the normalized cross-influence matrix. The coupling correction calculation unit is configured to perform a linear correction operation, or to perform an operation that starts from the initial vector and iterates based on the cross-influence matrix until convergence.

6. The system according to claim 1, characterized in that, The comprehensive evaluation module includes: The weight configuration unit is used to receive weight coefficients for each coupled subsystem, either configured by the user or optimized by the system itself. The weighted calculation unit is used to multiply the final scores of each coupled subsystem by the corresponding weight coefficients and then sum them to obtain the comprehensive score of the geothermal cap layer. The grading unit is used to match the comprehensive score of the geothermal cover layer with a pre-stored grading threshold range to determine the sealing level.

7. The system according to claim 1, characterized in that, The result output module includes: The plan view generation unit is used to generate a planar grid map showing the spatial distribution of the comprehensive score and sealing level of the geothermal cap layer; The profile generation unit is used to generate profiles showing the changes in the scores of each coupled subsystem along a selected geological profile; The report generation unit is used to generate a formatted report file that includes the planar grid diagram, cross-sectional view, and data analysis conclusions.

8. A computer terminal device, characterized in that, include: One or more processors; A memory, coupled to the processor, for storing one or more programs; When the one or more programs are executed by the one or more processors, the one or more processors enable the module functions of the system as described in any one of claims 1-7.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the module functions of the system as described in any one of claims 1-7.

10. A computer program product, comprising a computer program, characterized in that, When executed by a processor, the computer program implements the module functions of the system as described in any one of claims 1-7.

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