A stochastic method for describing fractures in a thermal reservoir

Abstract

The application provides a random description method of hot reservoir fissures, relates to the field of deep artificial reservoirs and numerical simulation, and the method comprises the following steps: based on a discrete fissure network model and a Monte Carlo random method, taking an elliptical sheet as a basic characterization unit of the fissures, determining a random distribution model of central coordinates, semi-axis length, inclination angle and self rotation angle by statistically analyzing the geometric characteristics of the hot reservoir fissures, constructing a spatial coordinate constraint relationship of the inclined elliptical sheet, and realizing arbitrary posture description of the elliptical sheet in a three-dimensional space through coordinate transformation; based on the above distribution model and the constraint relationship, generating an elliptical sheet fissure set through the Monte Carlo random method and constructing a three-dimensional random fissure network model through iterative screening. The application can realize real simulation and accurate characterization of the hot reservoir fissure distribution.

Description

Technical Field

[0001] This application relates to the field of deep artificial reservoirs and numerical simulation, and in particular to a stochastic description method for fractures in thermal reservoirs. Background Technology

[0002] Thermal reservoir rock masses are complex geological bodies composed of intact rock blocks and various natural and man-made fractures. Fractures, as weak points within the rock mass, directly influence the mechanical properties, permeability, and overall stability of the rock mass through their spatial distribution and geometric morphology. They serve as the primary channels for heat and mass transfer of underground fluids. Accurately describing the random distribution characteristics of rock mass fractures is a core prerequisite for permeability prediction, rock mass engineering numerical simulation, and disaster prediction. In actual engineering, thermal reservoir rock mass fractures exhibit significant randomness and dispersion. The center location, extension scale, and dip angle of fractures vary significantly in different regions, posing a significant challenge to the accurate description of fractures.

[0003] Existing methods for describing rock mass fractures often employ a single geometric model or fixed parameters, failing to fully consider the random distribution characteristics of fracture geometric parameters. They may simply assign random values ​​to some parameters, lacking a systematic set of rules for random parameter distribution and a geometric constraint system. This results in significant deviations between the fracture descriptions and the actual development patterns of rock mass fractures, failing to accurately reproduce the spatial distribution characteristics of fractures. Consequently, this affects the accuracy of subsequent rock mechanics analysis and seepage simulation, making it difficult to meet the design and control requirements of complex rock mass engineering projects. Therefore, constructing a random description method for rock mass fractures that balances parameter randomness and geometric rationality is crucial for solving the problem of accurate characterization of rock mass fractures. Summary of the Invention

[0004] The purpose of this invention is to provide a stochastic description method for fractures in thermal reservoirs, in order to solve the technical problems of low accuracy, poor distribution reproduction, and difficulty in conforming to the actual fracture development law of traditional fracture models.

[0005] The above-mentioned objective of this application is achieved through the following technical solution: Step S1: Perform geometric feature statistical analysis on the fractures in the thermal reservoir to determine the core geometric parameters of the elliptical plate characterization unit; select a suitable probability statistical distribution function to establish a random distribution model for each core geometric parameter, and at the same time construct the spatial coordinate constraint relationship of the tilted elliptical plate. Step S2: Based on the random distribution model and spatial coordinate constraints, an elliptical crack set is generated using the Monte Carlo random method to construct a three-dimensional random crack model, as detailed below: Step S21: Within the preset three-dimensional thermal reservoir simulation domain, randomly generate the center coordinates of each elliptical fracture according to the Poisson distribution, so that each fracture is randomly and uniformly distributed in the reservoir space. Step S22: Based on the distribution parameters determined by on-site statistics, generate the semi-major axis length and semi-minor axis length of each elliptical piece; Step S23: Based on the lumped parameters determined by on-site statistics The dip angle and inclination of each elliptical crack are generated, as well as the rotation angle of the elliptical crack in its own plane, thus fully characterizing the spatial attitude of the crack. Step S24: Based on the generated center coordinates, major semi-axis length, minor semi-axis length, dip, dip angle and self-rotation angle, and combined with the spatial coordinate constraint relationship, determine the specific attitude of each elliptic slice in the reservoir space; Step S25: Repeat steps S21 to S24 to generate elliptical fractures until the preset number or density of fractures is reached. Eliminate elliptical fragments that exceed the boundary of the three-dimensional thermal reservoir simulation domain and those that excessively overlap with other fractures to form a three-dimensional random fracture model.

[0006] Optionally, step S1 includes: The core geometric parameters include: center coordinates , used to characterize the location of the crack in three-dimensional space; Long half-axis length and short half axis length , used to characterize the extent of crack propagation; tendency and tilt angle , used to characterize the spatial orientation of fractures; Self-rotation angle , used to characterize the rotational attitude of the tilted elliptical slice in its own plane; The specific random distribution model is as follows: center coordinates It follows a three-dimensional Poisson distribution; Long half-axis length It follows a gamma distribution; Short half-axis length The ratio of the minor axis to the major axis is determined by multiplying the minor axis ratio by the major axis length, and the minor axis ratio follows a normal distribution. inclination It follows a Fisher distribution; Self-rotation angle It follows a von Mises distribution.

[0007] Optionally, the length of the long semi-axis The probability density function of the gamma distribution is:

[0008] In the formula, The shape parameter of the gamma distribution. This is the inverse scaling parameter. For gamma function, The length of the semi-major axis of the ellipse; Elliptical plate minor semi-axis length Can be with the length of the long half-axis The probability density function can be set at a fixed ratio, or represented solely by a normal distribution. If a normal distribution is used, its probability density function is...

[0009] In the formula, This is the mean of the shorter semi-axis length. The standard deviation is determined by fitting field statistical data and can reflect the discrete characteristics of the elliptical morphology of fractures in actual thermal reservoirs. The tilt angle The probability density function of the Fisher distribution is:

[0010] In the formula, The lumped parameter of the Fisher distribution reflects the degree of clustering of fracture dip angles. The lumped parameters The calculation formula is obtained by analyzing the crack dip angle data collected on-site. ,in The number of cracks, The resultant vector of the unit normal vector of the fracture; The self-rotation angle The probability density function of the von Mises distribution is:

[0011] In the formula, The rotation angle of the elliptical disc itself. For the advantageous rotation angle, For angle lumped parameters, It is a zeroth-order modified Bessel function of the first kind.

[0012] Optionally, the spatial coordinate constraint relationship is a transformation from the local coordinate system of the elliptical slice to the global coordinate system, specifically expressed as:

[0013] In the formula, These are the coordinates of the center point of the ellipse in the global coordinate system. , These are the lengths of the major and minor semi-axis of the ellipse, respectively. As a tendency, The angle of inclination, The rotation angle of the elliptical disc itself. These are the coordinates of the elliptic in its local coordinate system; the expression for the elliptic in its local coordinate system is: .

[0014] Optionally, the criterion for judging excessive overlap of other cracks is: the overlapping area exceeds a preset threshold of the area of ​​the elliptical piece itself.

[0015] Optionally, the preset number or density of fractures is determined based on the on-site statistical fracture density of the thermal reservoir. The three-dimensional thermal reservoir simulation domain It is a cuboid region.

[0016] An electronic device includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform a stochastic description method of thermal reservoir fractures.

[0017] A computer-readable storage medium storing instructions that, when executed, perform a method for stochastic description of fractures in a thermal reservoir.

[0018] The beneficial effects of the technical solution provided in this application are: 1. Improved accuracy of fracture characterization. This invention abandons the traditional simplified disk model and uses elliptical slices as fracture characterization units. It introduces six core parameters: semi-major axis length, semi-minor axis length, center coordinates, dip direction, tilt angle, and self-rotation angle, and adapts them to gamma distribution, normal distribution, Poisson distribution, Fisher distribution, and von Mises distribution respectively, forming a systematic multi-dimensional parameter random distribution system. At the same time, it constructs a complete three-dimensional coordinate transformation relationship to avoid geometric distortion and significantly improve the characterization accuracy of the fracture network model.

[0019] 2. Accurately reproduces the spatial distribution pattern. The center point of the elliptical fragment follows a three-dimensional Poisson distribution, ensuring that the fractures are randomly and uniformly distributed within the reservoir space. Combined with an iterative screening mechanism, fractures outside the boundary and excessively overlapping are eliminated, thus truly reflecting the natural law of random development of natural fractures.

[0020] 3. Supporting seepage analysis and engineering assessment. The constructed three-dimensional random fracture network model can provide accurate geometric input for seepage simulation, heat transfer calculation, and rock mechanics analysis, improving the accuracy of reservoir permeability prediction and providing reliable technical support for hydraulic fracturing and geothermal energy development.

[0021] 4. Strong engineering adaptability. All distribution parameters can be flexibly determined based on field statistical data, enabling it to adapt to the engineering needs of geothermal reservoirs at different geological conditions and scales. Attached Figure Description

[0022] The present application will be further described below with reference to the accompanying drawings and embodiments. In the accompanying drawings: Figure 1 This is a flowchart illustrating a method for stochastically describing fractures in a thermal reservoir, as provided in an embodiment of this application. Figure 2 This is a schematic diagram of a typical probability distribution provided in an embodiment of this application; Figure 3 This is a schematic diagram of the local coordinate system of the elliptical slice provided in an embodiment of this application; Figure 4 This is a schematic diagram of rock mass fractures generated based on Monte Carlo simulation, provided in an embodiment of this application. Figure 5 This is a schematic diagram of the electronic device structure in the embodiments of this application. Detailed Implementation

[0023] To provide a clearer understanding of the technical features, objectives, and effects of this application, the specific embodiments of this application will now be described in detail with reference to the accompanying drawings.

[0024] Embodiments of this application provide a method for stochastically describing fractures in a thermal reservoir.

[0025] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating the steps of a method for stochastically describing fractures in a thermal reservoir according to an embodiment of this application, including: Step S1: Perform geometric feature statistical analysis on the fractures in the thermal reservoir to determine the core geometric parameters of the elliptical plate characterization unit; select a suitable probability statistical distribution function to establish a random distribution model for each core geometric parameter, and at the same time construct the spatial coordinate constraint relationship of the tilted elliptical plate. Step S2: Based on the random distribution model and spatial coordinate constraints, an elliptical crack set is generated using the Monte Carlo random method to construct a three-dimensional random crack model, as detailed below: Step S21: Within the preset three-dimensional thermal reservoir simulation domain, randomly generate the center coordinates of each elliptical fracture according to the Poisson distribution, so that each fracture is randomly and uniformly distributed in the reservoir space. Step S22: Based on the distribution parameters determined by on-site statistics, generate the semi-major axis length and semi-minor axis length of each elliptical piece; Step S23: Based on the lumped parameters determined by on-site statistics The dip angle and inclination of each elliptical crack are generated, as well as the rotation angle of the elliptical crack in its own plane, thus fully characterizing the spatial attitude of the crack. Step S24: Based on the generated center coordinates, major semi-axis length, minor semi-axis length, dip, dip angle and self-rotation angle, and combined with the spatial coordinate constraint relationship, determine the specific attitude of each elliptic slice in the reservoir space; Step S25: Repeat steps S21 to S24 to generate elliptical fractures until the preset number or density of fractures is reached. Eliminate elliptical fragments that exceed the boundary of the three-dimensional thermal reservoir simulation domain and those that excessively overlap with other fractures to form a three-dimensional random fracture model.

[0026] This application employs the aforementioned technical solution, using elliptical slices with randomly distributed center coordinates, semi-axis lengths, and inclination angles to describe reservoir fractures. By constraining the coordinate relationships of these inclined elliptical slices, a precise fracture model is constructed, achieving realistic simulation and quantitative characterization of fracture distribution within the geothermal reservoir. This addresses the technical problems of low accuracy, poor distribution reproduction, and difficulty in accurately reflecting the actual fracture development patterns of traditional fracture models, providing reliable fracture network model support for geothermal reservoir seepage characteristic analysis and development scheme design. Based on the Discrete Fracture Network (DFN) model and the Monte Carlo random method, this invention uses elliptical slices as the basic characterization unit for geothermal reservoir fractures. The random distribution of elliptical slice geometric parameters is determined through field statistics. Combined with the coordinate constraints of the inclined elliptical slices and the random generation process, a three-dimensional random fracture model consistent with the statistical characteristics of actual geothermal reservoir fracture distribution is constructed, achieving precise random description and network construction of geothermal reservoir fractures.

[0027] Step S1 includes: The core geometric parameters include: center coordinates , used to characterize the location of the crack in three-dimensional space; Long half-axis length and short half axis length , used to characterize the extent of crack propagation; tendency and tilt angle , used to characterize the spatial orientation of fractures; Self-rotation angle , used to characterize the rotational attitude of the tilted elliptical slice in its own plane; The specific random distribution model is as follows: center coordinates It follows a three-dimensional Poisson distribution; Long half-axis length It follows a gamma distribution; Short half-axis length The ratio of the minor axis to the major axis is determined by multiplying the minor axis ratio by the major axis length, and the minor axis ratio follows a normal distribution. inclination It follows a Fisher distribution; Self-rotation angle It follows a von Mises distribution.

[0028] As one embodiment, geometric feature statistical analysis is performed on the fractures in the thermal reservoir to determine the core geometric parameters (center coordinates, semi-axis length, dip angle) of the elliptical plate characterization unit. A suitable probability statistical distribution function is selected to establish a random distribution model for each parameter. Simultaneously, coordinate constraint relationships for the tilted elliptical plates are constructed, laying the foundation for the random generation of fractures. Taking the simulated area of ​​the thermal reservoir as the research object, and using planar elliptical plates as the geometric characterization carrier for a single fracture, on-site investigation and sampling statistics (which can be combined with photography, SFM algorithm reconstruction, etc., to obtain the fracture vertex coordinates and then extract geometric features) are conducted to clarify the statistical characteristics of the core random parameters. A suitable probability statistical distribution function (commonly gamma distribution, normal distribution, Fisher distribution, etc.) is then selected. Figure 2 As shown, a random distribution model of parameters is established based on the goodness of fit of field statistical data; at the same time, the coordinate constraint relationship of the inclined elliptical plate is constructed to avoid geometric distortion of the elliptical plate and ensure accurate characterization of individual cracks.

[0029] As one example, in the three-dimensional thermal reservoir simulation domain Inside, the center point of the elliptical plate It follows a Poisson distribution, thus ensuring that fractures are randomly and uniformly distributed in the reservoir space, which is consistent with the natural development characteristics of fractures in actual thermal reservoirs; the advantage of the gamma distribution is that it can accurately characterize the statistical distribution characteristics of the semi-major axis of the elliptical plate, which fits the multi-scale distribution law of fracture size in actual thermal reservoirs, and is more applicable than the single size parameter of the traditional disk model.

[0030] The length of the long semi-axis The probability density function of the gamma distribution is:

[0031] In the formula, The shape parameter of the gamma distribution. This is the inverse scaling parameter. For gamma function, The length of the semi-major axis of the ellipse; Elliptical plate minor semi-axis length Can be with the length of the long half-axis The probability density function can be set at a fixed ratio, or represented solely by a normal distribution. If a normal distribution is used, its probability density function is...

[0032] In the formula, This is the mean of the shorter semi-axis length. The standard deviation is determined by fitting field statistical data and can reflect the discrete characteristics of the elliptical morphology of fractures in actual thermal reservoirs. The tilt angle The probability density function of the Fisher distribution is:

[0033] In the formula, The lumped parameter of the Fisher distribution reflects the degree of clustering of fracture dip angles. The lumped parameters The calculation formula is obtained by analyzing the crack dip angle data collected on-site. ,in The number of cracks, The resultant vector of the unit normal vector of the fracture; The self-rotation angle The probability density function of the von Mises distribution is:

[0034] In the formula, The rotation angle of the elliptical disc itself. For the advantageous rotation angle, For angle lumped parameters, It is a zeroth-order modified Bessel function of the first kind.

[0035] As one embodiment, in order to fully describe the rotational attitude of the elliptical slice in its own plane, the rotation angle of the elliptical slice follows a von Mises distribution, which is a probabilistic model suitable for cyclic angle data and can accurately characterize the random distribution characteristics of the major axis direction of the ellipse.

[0036] The spatial coordinate constraint relationship is a transformation from the local coordinate system of the elliptical slice to the global coordinate system, and the specific expression is as follows:

[0037] In the formula, These are the coordinates of the center point of the ellipse in the global coordinate system. , These are the lengths of the major and minor semi-axis of the ellipse, respectively. As a tendency, The angle of inclination, The rotation angle of the elliptical disc itself. These are the coordinates of the elliptic in its local coordinate system; the expression for the elliptic in its local coordinate system is: .

[0038] As one embodiment, the coordinate transformation relationship described above can completely describe the arbitrary position and orientation of the elliptical plate crack in three-dimensional space, avoiding geometric distortion and ensuring the accuracy of single crack characterization.

[0039] The criterion for judging excessive overlap of other cracks is: the overlapping area exceeds a preset threshold of the area of ​​the ellipse itself.

[0040] The preset number or density of fractures is determined based on the on-site statistical fracture density of the thermal reservoir. The three-dimensional thermal reservoir simulation domain It is a cuboid region.

[0041] As one embodiment, the set of elliptical plate cracks is generated using the Monte Carlo random method. The specific generation and network construction process includes the following steps: (1) Randomly generate the center of the elliptical plate crack. In the preset thermal reservoir simulation domain Inside, a series of circle center coordinates are randomly generated according to a Poisson distribution. This ensures that each fracture is randomly and evenly distributed within the reservoir space, without obvious clustering or sparse areas, which conforms to the spatial distribution pattern of fractures in actual thermal reservoirs. (2) Length of the major and minor semi-axis of the generated elliptical slice , Based on the distribution parameters determined by on-site statistics, combined with the formula , The length of the semi-major axis of each elliptical piece is randomly generated. , length of short half axis Elliptical pieces that exceed the actual statistical range are removed to ensure that the fracture size is consistent with the actual fracture size of the thermal reservoir. (3) The inclination angle of the generated elliptical plate crack : Lumped parameters determined based on on-site statistics Combined with formula Randomly generate the tilt angle of each elliptical piece. Meanwhile, the rotation angle of the elliptical slice is randomly generated according to formula (6) to fully characterize the attitude of the fracture space and ensure that the tilt attitude of the elliptical slice conforms to the characteristics of the actual thermal reservoir. (4) Apply coordinate constraints and determine the spatial orientation of the elliptic: based on the generated center coordinates ,inclination and the length of the short and long semi-axis , By combining spatial coordinate constraints, the specific orientation of each elliptic slice in the reservoir space is determined, avoiding geometric distortion and spatial overlap, and ensuring the accuracy of single fracture characterization. (5) Iterative screening and fracture network construction: Repeat steps (1) to (4) to randomly generate elliptical fractures until the preset number of fractures is reached. At the same time, elliptical pieces that exceed the boundary of the thermal reservoir simulation domain and overlap excessively with other fractures are removed. Finally, a three-dimensional random fracture model is constructed to complete the random description and network construction of thermal reservoir fractures.

[0042] In one embodiment, after a geothermal reservoir undergoes hydraulic fracturing, it is necessary to characterize the reservoir fractures to assess its permeability. This embodiment employs the method of the present invention to perform random fracture characterization of the geothermal reservoir.

[0043] (I) On-site measurement and data acquisition Geometric feature data of reservoir fractures were obtained through methods such as core drilling, UAV photography, and SFM algorithm reconstruction.

[0044] (II) Statistical Analysis of Fractured Geometric Characteristics Statistical analysis was performed on the collected fracture samples to analyze the distribution patterns of the center point, semi-major axis length, minor axis ratio, attitude (dip and dip), and self-rotation angle.

[0045] (III) Goodness-of-fit test to determine the distribution model Based on the goodness-of-fit test results of the statistical data, the best-fit probability distribution model was selected, as shown in Table 1.

[0046] Table 1 Geometric parameters characterizing the fracture

[0047] Self-rotation angle distribution: Based on the fitting of field statistical data, in this embodiment, the crack has two sets of dominant rotation directions: Group 1: Mean rotation angle =79°, lumped parameter =9.95 Group 2: Mean rotation angle = 17°, lumped parameters =10.08 The two groups of cracks each account for approximately 50%.

[0048] In another embodiment, based on a defined distribution model and coordinate transformation relationship, an elliptical patch fracture set is generated using the Monte Carlo random method. The specific generation and network construction process is as follows: Step 1: Generate the center point of the elliptical plate crack Within the pre-defined simulation domain Ω of the thermal reservoir, the center coordinates are randomly generated according to a predetermined Poisson distribution. This ensures that each fracture is randomly and uniformly distributed within the reservoir space.

[0049] Step 2: Generate the semi-major axis length of the ellipse. Based on the established gamma distribution (shape parameter) =3.62, inverse scaling parameter =15.41), randomly generate the semi-major axis length ai of each ellipse, and remove ellipse pieces that exceed the actual statistical range.

[0050] Step 3: Generate the minor semi-axis length of the ellipse. Based on the established normal distribution (mean) =0.4686, standard deviation =0.1915), randomly generate the minor-to-major axis ratio ke, and calculate the minor semi-axis length bi = ke × ai.

[0051] Step 4: Generate the attitude (dip and dip) of the elliptical plate fracture. Based on the established Fisher distribution (mean dip 90°, mean dip angle 33°, lumped parameters...) (1=14.7), randomly generate the tilt angle of each elliptical piece. and tendencies .

[0052] Step 5: Generate the rotation angle of the ellipse itself. Based on the established von Mises distribution, parameters from either group 1 or group 2 are randomly selected at a 50% ratio to generate the self-rotation angle. .

[0053] Step 6: Apply coordinate transformation to determine the spatial orientation of the elliptical slice. The generated center coordinates , length of semi-axis ai, length of semi-axis bi, inclination ,inclination Self-rotation angle Substitute into formula (4) to calculate the spatial coordinates of each point on the elliptic slice, determine the specific orientation of each elliptic slice in the reservoir space, and avoid geometric distortion and spatial overlap.

[0054] Step 7: Iterative screening and fracture network construction Repeat steps 1-6 to randomly generate elliptical fractures until the preset fracture density is reached. Simultaneously, remove elliptical fragments that extend beyond the simulated thermal reservoir domain boundary or excessively overlap with other fractures (overlapping area exceeding 30% of their own area). Finally, construct a three-dimensional random fracture model as shown below. Figure 4 As shown.

[0055] This application also discloses an electronic device. (See reference...) Figure 5 , Figure 5This is a schematic diagram of the structure of an electronic device disclosed in an embodiment of this application. The electronic device 500 may include: at least one processor 501, at least one network interface 504, a user interface 503, a memory 505, and at least one communication bus 502.

[0056] The communication bus 502 is used to enable communication between these components.

[0057] The user interface 503 may include a display screen, and optionally, the user interface 503 may also include a standard wired interface or a wireless interface.

[0058] The network interface 504 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0059] This application also discloses a computer-readable storage medium storing a plurality of instructions adapted for loading by a processor to execute the above-described method for stochastic description of thermal reservoir fractures.

[0060] The above are merely exemplary embodiments of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure.

[0061] This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described in this disclosure. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for stochastically describing fractures in a thermal reservoir, characterized in that, The method includes the following steps: Step S1: Perform geometric feature statistical analysis on the fractures in the thermal reservoir to determine the core geometric parameters of the elliptical plate characterization unit; select a suitable probability statistical distribution function to establish a random distribution model for each core geometric parameter, and at the same time construct the spatial coordinate constraint relationship of the tilted elliptical plate. Step S2: Based on the random distribution model and spatial coordinate constraints, an elliptical crack set is generated using the Monte Carlo random method to construct a three-dimensional random crack model, as detailed below: Step S21: Within the preset three-dimensional thermal reservoir simulation domain, randomly generate the center coordinates of each elliptical fracture according to the Poisson distribution, so that each fracture is randomly and uniformly distributed in the reservoir space. Step S22: Based on the distribution parameters determined by on-site statistics, generate the semi-major axis length and semi-minor axis length of each elliptical piece; Step S23: Based on the lumped parameters determined by on-site statistics The dip angle and inclination of each elliptical crack are generated, as well as the rotation angle of the elliptical crack in its own plane, thus fully characterizing the spatial attitude of the crack. Step S24: Based on the generated center coordinates, major semi-axis length, minor semi-axis length, dip, dip angle and self-rotation angle, and combined with the spatial coordinate constraint relationship, determine the specific attitude of each elliptic slice in the reservoir space; Step S25: Repeat steps S21 to S24 to generate elliptical fractures until the preset number or density of fractures is reached. Eliminate elliptical fragments that exceed the boundary of the three-dimensional thermal reservoir simulation domain and those that excessively overlap with other fractures to form a three-dimensional random fracture model.

2. The method for stochastic description of fractures in a thermal reservoir as described in claim 1, characterized in that, Step S1 includes: The core geometric parameters include: center coordinates , used to characterize the location of the crack in three-dimensional space; Long half-axis length and short half axis length , used to characterize the extent of crack propagation; tendency and tilt angle , used to characterize the spatial orientation of fractures; Self-rotation angle , used to characterize the rotational attitude of the tilted elliptical slice in its own plane; The specific random distribution model is as follows: center coordinates It follows a three-dimensional Poisson distribution; Long half-axis length It follows a gamma distribution; Short half-axis length The ratio of the minor axis to the major axis is determined by multiplying the minor axis ratio by the major axis length, and the minor axis ratio follows a normal distribution. inclination It follows a Fisher distribution; Self-rotation angle It follows a von Mises distribution.

3. The method for stochastic description of fractures in a thermal reservoir as described in claim 2, characterized in that, The length of the long semi-axis The probability density function of the gamma distribution is: In the formula, The shape parameter of the gamma distribution. This is the inverse scaling parameter. For gamma function, The length of the semi-major axis of the ellipse; Elliptical plate minor semi-axis length Can be with the length of the long half-axis The probability density function can be set at a fixed ratio, or represented solely by a normal distribution. If a normal distribution is used, its probability density function is... In the formula, This is the mean of the shorter semi-axis length. The standard deviation is determined by fitting field statistical data and can reflect the discrete characteristics of the elliptical morphology of fractures in actual thermal reservoirs. The tilt angle The probability density function of the Fisher distribution is: In the formula, The lumped parameter of the Fisher distribution reflects the degree of clustering of fracture dip angles. The lumped parameters The calculation formula is obtained by analyzing the crack dip angle data collected on-site. ,in The number of cracks, The resultant vector of the unit normal vector of the fracture; The self-rotation angle The probability density function of the von Mises distribution is: In the formula, The rotation angle of the elliptical disc itself. For the advantageous rotation angle, For angle lumped parameters, It is a zeroth-order modified Bessel function of the first kind.

4. The method for stochastic description of fractures in a thermal reservoir as described in claim 2, characterized in that, The spatial coordinate constraint relationship is a transformation from the local coordinate system of the elliptical slice to the global coordinate system, and the specific expression is as follows: In the formula, These are the coordinates of the center point of the ellipse in the global coordinate system. , These are the lengths of the major and minor semi-axis of the ellipse, respectively. As a tendency, The angle of inclination, The rotation angle of the elliptical disc itself. These are the coordinates of the elliptic in its local coordinate system; the expression for the elliptic in its local coordinate system is: .

5. The method for stochastic description of fractures in a thermal reservoir as described in claim 1, characterized in that, The criterion for judging excessive overlap of other cracks is: the overlapping area exceeds a preset threshold of the area of ​​the ellipse itself.

6. The method for stochastic description of fractures in a thermal reservoir as described in claim 1, characterized in that, The preset number or density of fractures is determined based on the on-site statistical fracture density of the thermal reservoir. The three-dimensional thermal reservoir simulation domain It is a cuboid region.

7. An electronic device, characterized in that, The device includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the stochastic description method of thermal reservoir fractures as described in any one of claims 1-6.

8. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores instructions that, when executed by a computer, perform the random description method of thermal reservoir fractures as described in any one of claims 1-6.

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