A method for modeling a discrete fracture network oriented to a fault damage zone

Abstract

The application discloses a kind of discrete fracture network modeling methods for fault damage zone, comprising: constructing three-dimensional calculation domain, determining fault position and occurrence, and establishing local coordinate system accordingly;Uniformly distributed background fracture is generated in calculation domain;For fault-controlled fracture, power law distribution based on fault distance is used to generate fracture center position satisfying normal heterogeneous distribution characteristics, and uniformly sampled in tangential direction parallel to fault, mapped to global space by coordinate transformation;Based on statistical distribution, the occurrence and size parameters of the fracture are generated, and a three-dimensional fracture geometry model is constructed;Superimpose background fracture and fault-controlled fracture to form a complete fracture network, and output data files compatible with modeling software.The application can accurately characterize the spatial heterogeneous distribution characteristics of fracture density decay with distance in fault damage zone, and the geological authenticity and engineering applicability of the model are significantly improved.

Description

Technical Field

[0001] This invention relates to the field of rock mass fracture network modeling technology, and in particular to a discrete fracture network modeling method for fault damage zones. Background Technology

[0002] Fractured rock masses are widely found in underground engineering and geological formations, exhibiting complex fracture networks. In engineering practices such as groundwater development, oil and gas extraction, geothermal utilization, and carbon dioxide geological storage, the structural characteristics of these fracture networks have a decisive influence on the seepage properties and fluid migration paths of the rock mass. Fault-damaged zones, as areas with highly developed fractures, exhibit significantly increased fracture density and enhanced connectivity, often forming dominant seepage channels within the geological body. Therefore, accurately characterizing the fracture network structure of fault-damaged zones is crucial for a deeper understanding and prediction of underground fluid behavior.

[0003] Currently, discrete fracture network (DFN) modeling is a mainstream method for characterizing fracture network structures. This method constructs a refined three-dimensional fracture network model by explicitly defining the geometry of each fracture (such as location, size, and orientation), which can better reflect the statistical characteristics and spatial configuration of the fracture system.

[0004] However, existing DFN modeling methods have significant limitations when applied to fault-damaged areas. In reality, fracture parameters (such as density and size) within fault-damaged areas typically exhibit regular changes with increasing distance from the fault (e.g., decaying according to a power law, exponential, or logarithmic relationship), demonstrating strong spatial heterogeneity. Traditional DFN methods mostly rely on overall regional statistical parameters (such as average density and average size) to generate fractures, usually assuming or defaulting to a spatially uniform distribution or only a weakly heterogeneous distribution of fracture parameters. This approach lacks a quantitative modeling mechanism that directly correlates the probability of fracture generation or attribute parameters with spatial coordinates (especially the distance to the fault), thus failing to accurately reflect the spatial variation of fracture parameters in fault-damaged areas.

[0005] Furthermore, current commercial fracture network modeling software (such as FracMan) typically only provides uniform random distribution or simple global statistical distribution models in its built-in fracture generation algorithms, lacking the ability to control parameter distribution based on spatial location functions (such as probability density functions that vary with distance). This makes it difficult for engineers to conveniently and automatically generate fracture networks that conform to the actual heterogeneous distribution characteristics of fault damage zones within existing software frameworks, thus limiting the geological realism of the constructed models and their applicability in specific engineering projects (such as seepage simulation and stability analysis).

[0006] In summary, to address the critical issue that existing DFN modeling methods struggle to accurately characterize the spatial heterogeneous distribution of fractures in fault-damaged zones, a novel modeling approach is urgently needed. This method should integrate geostatistical laws to achieve the quantitative and heterogeneous generation of fracture parameters based on spatial location (especially distance from the fault), and its output should be compatible with existing mainstream modeling software for direct application in numerical simulations and analyses in engineering practice. Summary of the Invention

[0007] This invention addresses the shortcomings of existing technologies by providing a discrete fracture network modeling method for fault damage zones.

[0008] To achieve the above-mentioned objectives, the technical solution adopted by the present invention is as follows:

[0009] A discrete fracture network modeling method for fault-damaged zones, used in geological engineering numerical simulation, generates a three-dimensional fracture network model for seepage or mechanical analysis, specifically including the following steps:

[0010] S1. Construct a three-dimensional computational domain, set the fault plane within the computational domain, determine the fault center location and its attitude parameters, including dip angle and dip direction; calculate the normal vector of the fault plane based on the fault geometric parameters, and establish a local coordinate system based on the normal vector;

[0011] S2. Generate background cracks within the computational domain. The spatial location of the background cracks is represented by the crack center point. , , The coordinates are uniformly distributed in the range of their respective coordinate axes in the global coordinate system.

[0012] S3. Generating fault-controlled fractures within the computational domain, including:

[0013] S31. In the local coordinate system, generate the coordinates of the fracture center in the tangential direction parallel to the fault plane, wherein the tangential coordinates follow a uniform random distribution.

[0014] S32. Generate the normal distance from the fracture center to the fault plane, wherein the normal distance follows a power-law distribution;

[0015] S33. Combine the tangential coordinates generated in step S31 with the normal distance generated in step S32 to obtain the coordinates of the fracture center in the local coordinate system.

[0016] S34. The coordinates of the fracture center in the local coordinate system are mapped to the global coordinate system through coordinate transformation to obtain the actual location distribution of the fault-controlled fracture in three-dimensional space.

[0017] S4. Generate fracture orientation parameters, wherein the orientation parameters are described using a Fisher distribution and mapped to a preset average orientation direction through orientation transformation;

[0018] S5. The size parameters of the generated crack, wherein the size parameters are described by a log-normal distribution;

[0019] S6. Based on the fracture center location, size and orientation generated in steps S2 to S5, construct a three-dimensional fracture geometric model;

[0020] S7. Superimpose the background fractures and the fault-controlled fractures to construct a complete discrete fracture network model of the fault damage zone, and output the fracture geometry, spatial location and attribute parameters according to a preset data format.

[0021] Further, in step S1, the unit normal vector of the fault plane According to the fault dip angle and tendencies In Cartesian coordinates, it is defined as:

[0022] .

[0023] The local coordinate system has the fault center as its origin and includes mutually orthogonal coordinates. axis, shaft and Axis; where, The axial direction is taken as the unit normal vector of the fracture surface. direction, The axial direction is taken as the fault dip direction. axial direction from shaft and The axis is determined according to the right-hand rule.

[0024] Further, in step S2, the coordinates of the center point of the background fracture are generated in the following way: within the boundary of the computational domain, respectively for... , , Independent random sampling is performed in three coordinate directions, so that

[0025]

[0026] Where U represents a uniform distribution. These represent the lower and upper limits for sampling in each coordinate direction, respectively.

[0027] Further, in step S32, the normal distance Follows a power-law distribution ,in The power-law decay exponent, The normal distance is generated using an inverse transform sampling method, and its expression is:

[0028] , For interval Uniformly distributed random numbers on the array.

[0029] Furthermore, step S32 also includes: performing positive and negative expansion processing on the generated normal distance samples to characterize the distribution characteristics of fractures on both sides of the fault.

[0030] Furthermore, in step S31, the tangential coordinates are included in the local coordinate system. shaft and The components along the axial direction are uniformly distributed: ,in These are the computational domains in the local tangential coordinate system. , The boundary range in the direction.

[0031] Furthermore, in step S4, the method for generating fracture orientation parameters includes:

[0032] S41. In the local spherical coordinate system, generate the initial direction unit vector of the fracture based on the Fisher distribution. ;

[0033] S42. Using a direction cosine matrix constructed based on a preset average dip angle and average dip direction. The initial direction unit vector The rotation mapping to the average attitude direction in the global coordinate system yields... ;

[0034] S43. Perform inverse calculation of the orientation parameters on the rotated direction vector to obtain the dip angle and dip direction of the fracture.

[0035] Further, in step S5, the crack size parameter Follows a log-normal distribution ,in and These are the mean and standard deviation in the logarithmic space, respectively; based on the mean in the actual space... and standard deviation The distribution parameters satisfy: .

[0036] Furthermore, in step S6, the three-dimensional fracture geometry model is described using a continuous disk model, and each fracture is uniquely determined by its center position, attitude parameters, and radius. To meet the requirements of numerical calculation and data export, the boundary of the continuous disk is discretized, the circumference is uniformly divided into multiple discrete points, and the fracture geometry in the local coordinate system is mapped to the three-dimensional global coordinate system through coordinate transformation.

[0037] Furthermore, in step S7, the preset data format is a fracture data file format compatible with the FracMan software.

[0038] Compared with the prior art, the advantages of the present invention are as follows:

[0039] 1. This invention achieves precise and quantitative characterization of the core heterogeneous feature of fracture density "attenuation with distance" in fault damage zone at the algorithm level through a decomposition-based fracture generation mechanism of "normal heterogeneity and tangential uniformity". This solves the key technical problem that existing methods cannot characterize the continuous change of fracture parameters with spatial location.

[0040] 2. This invention establishes a complete technical process, from fault geometry definition and local coordinate system construction to parameter sampling based on geostatistical laws (power law, Fisher distribution, log-normal distribution), to coordinate transformation and model integration. This framework transforms geological understanding into computable modeling rules through mathematical models and geometric methods, significantly improving the geological rationality and theoretical consistency of the model.

[0041] 3. The generated fracture network strictly conforms to the preset geostatistical model in terms of spatial distribution, orientation, and size, thus more realistically reflecting the structural characteristics of the fault-damaged zone. Engineering numerical simulations based on this high-fidelity model yield more reliable results and can provide better scientific basis for engineering decisions.

[0042] 4. By adjusting parameters with clear geological significance, such as the power-law decay exponent and Fisher lumped parameters, users can systematically control the heterogeneity and directional concentration of the generated fracture network, achieving flexible and controllable modeling of complex fracture networks, and the results are highly repeatable in a statistical sense.

[0043] 5. This invention designs a data output interface compatible with mainstream modeling software in the industry. The generated model can be directly imported for subsequent analysis and simulation, which opens up the process from innovative algorithm to engineering application and greatly improves the practical value and promotion efficiency of the method.

[0044] 6. By comparing and verifying the statistical characteristics output by the model with the preset input parameters, this invention ensures the macroscopic statistical consistency of the modeling results, provides users with a direct method to evaluate the accuracy of the model, and enhances the credibility of the constructed model. Attached Figure Description

[0045] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention 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.

[0046] Figure 1 This is an overall flowchart of the method in an embodiment of the present invention.

[0047] Figure 2 This is a schematic diagram of the construction of a local coordinate system based on the fault plane in an embodiment of the present invention.

[0048] Figure 3 This is a schematic diagram illustrating the transformation between the global coordinate system and the local coordinate system in an embodiment of the present invention.

[0049] Figure 4 This is a schematic diagram of uniform random sampling of the center points of background cracks within the computational domain in an embodiment of the present invention.

[0050] Figure 5 This is a power-law distribution diagram of the normal distances between the fracture centers on both sides of the fault in an embodiment of the present invention.

[0051] Figure 6 This is a schematic diagram of the coordinate transformation of the crack center in an embodiment of the present invention.

[0052] Figure 7 This is a schematic diagram of the process for generating fracture orientation based on Fisher distribution in an embodiment of the present invention.

[0053] Figure 8 This is a schematic diagram illustrating the generation of crack sizes that follow a log-normal distribution in an embodiment of the present invention.

[0054] Figure 9 This is a schematic diagram of the discretization of the continuous disk crack in an embodiment of the present invention.

[0055] Figure 10 This is a schematic diagram of the overall fracture network model in an embodiment of the present invention.

[0056] Figure 11 This is a diagram showing the modeling results of the discrete fracture network in the fault damage zone in an embodiment of the present invention.

[0057] Figure 12 This is a diagram showing the orientation and distribution characteristics of the background fracture group in an embodiment of the present invention.

[0058] Figure 13 This is a diagram showing the dip angle distribution characteristics of the background fracture group in an embodiment of the present invention.

[0059] Figure 14 This is a diagram showing the orientation and distribution characteristics of fault-controlled fracture groups in an embodiment of the present invention.

[0060] Figure 15 This is a diagram showing the dip angle distribution characteristics of the fault-controlled fracture group in an embodiment of the present invention.

[0061] Figure 16 This is a radius distribution feature diagram of the background fracture group in an embodiment of the present invention.

[0062] Figure 17 This is a radius distribution feature diagram of the fault-controlled fracture group in an embodiment of the present invention.

[0063] Figure 18 This is a power-law distribution verification diagram of the spatial scale (normal distance) of the crack in an embodiment of the present invention. Detailed Implementation

[0064] 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, not all, of the embodiments of the present invention. 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.

[0065] This invention discloses a discrete fracture network modeling method for fault damage zones, such as... Figure 1 As shown, the main steps include initialization of the computational domain and fault parameters, generation of background fracture centers, generation of fault-controlled fractures, generation of fracture orientation, and generation of fracture size.

[0066] (1) Initialization of computational domain and fault parameters:

[0067] Construct a three-dimensional cubic computational domain with a side length of . The fault center coordinates are set as follows: Fault attitude parameters include dip angle and tendencies Calculate the unit normal vector of the fault plane based on the fault attitude parameters:

[0068]

[0069] A local coordinate system is constructed based on the normal vector. With the fault center as the origin, its construction method is as shown in the attached figure. Figure 2 As shown. In the local coordinate system:

[0070] The positive direction of the axis is along the dip direction;

[0071] The positive direction of the axis is along the direction of the normal vector on the fault;

[0072] The positive direction of the axis is determined according to the right-hand rule;

[0073] Reference Appendix Figure 3 An orthogonal basis is constructed through vector cross product, and a coordinate transformation matrix between the global and local coordinate systems is further established.

[0074]

[0075] The meanings of each rotation angle are as follows:

[0076] : Around the global coordinate system The rotation angle of the shaft can be determined by tilting. Determined, the range of values ​​is: ;

[0077]

[0078] The angle of rotation about the horizontal axis after rotation, which is equal to the angle of inclination. The range of values ​​is ;

[0079] : is the planar rotation angle in the local coordinate system.

[0080] (2) Background fracture center formation:

[0081] Reference Appendix Figure 4 In the global coordinate system Independent random sampling is performed in three coordinate directions. The sampling in each direction follows a uniform distribution, and the sampling range corresponds to the boundary of the computational domain, i.e.:

[0082]

[0083] in, They are random variables The lower and upper limits of the values.

[0084] Finally, the three sampled coordinate components are combined to form the three-dimensional coordinates of the fracture center point. .

[0085] (3) Faults control fracture formation:

[0086] The fracture network consists of background fractures and fault-controlled fractures. These two types of fractures are generated independently within the same computational domain and spatially superimposed to form a complete three-dimensional fracture network model. Fault-controlled fractures are generated using a method of "normally heterogeneous, tangentially homogeneous." Specifically, the distribution of fracture centers in the normal direction follows a power-law characteristic, while they are uniformly distributed along the tangential direction within the fault plane. The normal distance from the fracture center to the fault plane is... Follows a power-law distribution Based on the inverse transform sampling method, the normal distance can be expressed as:

[0087]

[0088] in, For interval Uniformly distributed random numbers; The power-law decay exponent, The distance from the fracture center to the fault is the normal distance. This represents the range of values ​​for the normal distance from the fracture center to the fault.

[0089] To characterize the distribution features of fractures on both sides of the fault, the generated normal distances were subjected to positive and negative propagation processing, resulting in the following diagram. Figure 5 The diagram shows the set of normal distances between the fracture centers on both sides of the fault. The fracture centers are located in the tangential direction parallel to the fault plane. and Follows a uniform distribution:

[0090]

[0091] in, These are the computational domains in the local tangential coordinate system. , The boundary range in the direction. This is used to construct the position vector of the fracture center in the local coordinate system.

[0092]

[0093] The transformation expression for mapping to the global coordinate system via coordinate transformation is as follows:

[0094]

[0095]

[0096] The meanings of each rotation angle are as follows:

[0097] : Around the global coordinate system The rotation angle of the axis can be determined by the fault dip. Determined, the range of values ​​is: ;

[0098]

[0099] The rotation angle about the horizontal axis after rotation is equal to the fault dip angle. The range of values ​​is ;

[0100] : is the planar rotation angle in the local coordinate system.

[0101] in, Let be the rotation matrix from the global coordinate system to the local coordinate system. The coordinates of the fault center are... This is the three-dimensional spatial position vector of the fracture center in the local coordinate system of the fault. This is the transformed global coordinate vector of the fracture center. Refer to the appendix for the detailed transformation process. Figure 6 The location distribution of fault-controlled fractures in three-dimensional space is finally obtained through coordinate transformation. Furthermore, the transformed fracture geometry is evaluated for validity and filtered within the computational domain, retaining only fractures located within the effective computational region and eliminating invalid fractures outside the computational domain, thus obtaining the final three-dimensional spatial distribution result of the fault-controlled fractures.

[0102] (4) Formation of fracture orientation:

[0103] Reference Appendix Figure 7 The spatial orientation of the cracks is modeled using the Fisher distribution, whose probability density function satisfies ,in These are lumped parameters used to control the dispersion of fracture orientation around the average orientation. The specific generation process is as follows:

[0104] First, as attached Figure 7 As shown in step 1, the initial direction of the fracture is generated based on the Fisher distribution in the local spherical coordinate system. The polar angle is generated using random variables. With azimuth azimuth angle It follows a uniform distribution in the range [0, 2π].

[0105]

[0106] Polar angle Obtained by inversion sampling from the Fisher distribution probability density function:

[0107]

[0108] As attached Figure 7As shown in step 2, based on the transformation relationship between spherical coordinates and Cartesian coordinates, the unit direction vector of the crack in the local coordinate system is constructed.

[0109]

[0110] This step ensures the concentration of fracture orientation near the dominant orientation.

[0111] Subsequently, a coordinate transformation based on the average orientation matrix is ​​performed to map the fracture direction from the local reference system to the average orientation direction in the global coordinate system (as shown in the attached figure). Figure 7 (as shown in step 3)

[0112]

[0113] Where R is the mean dip angle with average tendency Constructed direction cosine matrix:

[0114]

[0115] The specific unfolding form is as follows:

[0116]

[0117] This transformation achieves a rotational mapping of the fracture orientation from a random initial distribution to the dominant orientation, thereby ensuring the spatial statistical consistency and directional concentration of the fracture network.

[0118] Subsequently, the rotated unit direction vector The attitude parameters are back-calculated to obtain the dip angle and dip direction of the fracture.

[0119] The expression for calculating the inclination angle is:

[0120]

[0121] in The arctangent function is preferred for calculation.

[0122]

[0123] In addition, to ensure the consistency of the crack normal vector direction, constraints are imposed on the generated results to ensure that they meet the following conditions. This avoids the problem of repetitive representation of directions. See the attached diagram for the final schematic. Figure 7 Step 4.

[0124] (5) Crack size generation:

[0125] As attached Figure 8As shown, the crack size is characterized by a log-normal distribution, and its random variable... satisfy:

[0126]

[0127] in, and These are the mean and standard deviation in the logarithmic space, respectively. Based on the given actual space mean... and standard deviation Its distribution parameters can be transformed through the following relationship:

[0128]

[0129] (6) Fractal geometry construction:

[0130] The fracture geometry is physically described using a continuous disk model. Each fracture is uniquely determined by its center location, attitude, and radius, forming a disk in an analytical geometric sense. The local coordinate system of this disk is constructed using the same method as the aforementioned fault local coordinate system to ensure its uniqueness and consistency. Within this local coordinate system, the fracture profile can be expressed as a continuous parametric equation:

[0131]

[0132] To meet the requirements of numerical calculation and crack data file export, while maintaining geometric accuracy, the continuous disk contour is discretized, and the circumference is uniformly divided into multiple discrete points (preferably 32). See attached... Figure 9 As shown, the angular parameters of the discrete points are:

[0133]

[0134] The corresponding fracture boundary point in the local coordinate system is:

[0135]

[0136] Subsequently, based on the rotation matrix determined by the fracture orientation...

[0137]

[0138] The meanings of each rotation angle are as follows:

[0139] : Around the global coordinate system The rotation angle of the shaft can be determined by the crack tendency. Determined, the range of values ​​is: ;

[0140]

[0141] The rotation angle about the horizontal axis after rotation is equal to the fracture dip angle. The range of values ​​is ;

[0142] : is the planar rotation angle in the local coordinate system.

[0143] The crack geometry in the local coordinate system is mapped to the three-dimensional global coordinate system through spatial transformation, which can be expressed as:

[0144]

[0145] in, The coordinates of the center point of the fractured disk are: This represents the coordinates of the fracture boundary point in the local coordinate system. These are the coordinates of the fracture boundary points in the global coordinate system. Therefore, the continuous disk fracture is approximated as a polygonal fracture structure through discretization and coordinate transformation, and used for subsequent numerical simulation calculations and fracture network input file generation.

[0146] (7) Data format construction:

[0147] To import and compute the fracture network model in FracMan software, a compatible fracture data file format needs to be constructed. The data file employs a hierarchical structure, including a format definition layer, a parameter definition layer, a fracture set layer, and a fracture geometry layer, with each fracture stored as an independent data unit.

[0148] Each fracture data unit includes at least the following information: fracture number, number of vertices (fixed at 32), physical parameters (including permeability Per, compressibility Com, and fracture aperture Aperture), normal vector information, and fracture vertex coordinate sequence. The fracture vertex coordinates are generated from 32 discrete points in the aforementioned geometric construction steps, arranged sequentially to characterize the fracture polygonal geometry; the normal vector describes the fracture spatial attitude; and the physical parameters are used for subsequent seepage and mechanical calculations.

[0149] The above data structure enables a unified expression of fracture geometry and physical properties, while ensuring compatibility with the target software's data format. The final schematic diagram is attached. Figure 10 As shown.

[0150] To verify the effectiveness of the method of this invention, a set of proposed statistical parameters was designed to generate a discrete fracture network model of the fault damage zone. The computational domain size was set to 100m × 100m × 100m, the fault center coordinates were (0m, 0m, 0m), and the fault dip angle was set to... ,tendency .

[0151] The background fracture centers follow a uniform distribution within the computational domain. Their lengths are characterized by a log-normal distribution with a mean of 3.0 m and a standard deviation of 2.0. The fracture attitude follows a Fisher distribution, with mean dip and strike angles of 45° and 30° (corresponding to a strike of 120°), respectively. Lumped parameters... .

[0152] The fault-controlled fracture centers spatially follow a power-law distribution with a decay exponent of 0.8, characterizing their spatial aggregation towards the fault. Fracture lengths are also characterized by a log-normal distribution, with a mean of 5.0 m and a standard deviation of 3.0. Fracture attitudes follow a Fisher distribution, with mean dip angles of 85° and 60° (corresponding to a strike of 150°), respectively. Lumped parameters... .

[0153] Volume density parameters of background fractures and fault-controlled fractures Unified settings .

[0154] The final generated data file was imported into FracMan software, and its built-in functions were used to perform statistical analysis on the crack parameters to verify whether the generated results met the preset parameter requirements. The model display and analysis results are attached. Figure 11-18 As shown.

[0155] Figure 11 The results of discrete fracture network modeling in the fault-damaged area are shown in the figure. The results show that the fractures exhibit certain spatial zoning and directional characteristics. The fracture density is higher near the fault and relatively uniform in the background area, reflecting the superimposed distribution characteristics of background fractures and fault-controlled fractures. Figure 12 and Figure 13 This is a map showing the distribution characteristics of the strike and dip angle of the background fracture group. The results show that the strike of the background fractures fluctuates around 120°, while the dip angle is concentrated around 45°. Figure 14 and Figure 15 This is a map showing the strike and dip distribution characteristics of the fault-controlled fracture group. The results show that the fracture strike is significantly concentrated in the 150° dominant direction, and the dip angle is highly concentrated around 85°, with significant peak characteristics. Figure 16 and Figure 17 This image shows the radius distribution characteristics of background fractures and fault-controlled fractures. The results indicate that the scales of both types of fractures conform to a log-normal distribution, suggesting that the scale generation process is effectively constrained. Figure 18 This is a verification plot of the power-law distribution of the spatial distribution of fractures. The results show that the probability density function of the spatial distribution of fractures has a good fit with the theoretical power-law distribution, indicating that the spatial distribution of fractures satisfies the power-law statistical characteristics.

[0156] In summary, the fracture network is consistent with the preset statistical model in terms of spatial distribution, attitude characteristics, and spatial distribution, which verifies the effectiveness and feasibility of the method of the present invention in the spatial generation and distribution control of fracture parameters.

[0157] In another embodiment, a discrete fracture network modeling system for fault-damaged zones is provided, which corresponds one-to-one with the discrete fracture network modeling method for fault-damaged zones described in the above embodiment. The system includes:

[0158] The computational domain and coordinate system construction module is configured to perform the following operations: construct a three-dimensional computational domain, determine the location and attitude of the fault in the computational domain, and establish a local coordinate system for the fault;

[0159] The background crack generation module is configured to perform the following operation: generate background cracks whose spatial locations are uniformly distributed within the computational domain;

[0160] The fault-controlled fracture generation module is configured to perform the following operations: generate fault-controlled fractures within the computational domain, wherein the fracture centers have a power-law distribution in the normal distance of the fault local coordinate system and a uniform distribution in the tangential direction.

[0161] The fracture orientation generation module is configured to perform the following operations: generate fracture orientation parameters, which follow a preset Fisher distribution;

[0162] The crack size generation module is configured to perform the following operations: generate crack size parameters, which follow a preset log-normal distribution;

[0163] The fracture geometry model construction module is configured to perform the following operations: construct a three-dimensional fracture geometry model based on the outputs of the background fracture generation module, the fault-controlled fracture generation module, the fracture orientation generation module, and the fracture size generation module;

[0164] The network synthesis and output module is configured to perform the following operations: superimpose the geometric models corresponding to the background fractures and the fault-controlled fractures to form a complete discrete fracture network model, and output it according to a preset data format.

[0165] Specific limitations regarding the discrete fracture network modeling system for fault-damaged areas can be found in the limitations of the discrete fracture network modeling method for fault-damaged areas mentioned above, and will not be repeated here. Each module in the aforementioned discrete fracture network modeling system for fault-damaged areas can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the corresponding operations of each module.

[0166] In another embodiment, a terminal device is provided, comprising a processor and a memory. The memory stores a computer program, which includes program instructions. The processor executes the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing and control core of the terminal, suitable for implementing one or more instructions, specifically suitable for loading and executing one or more instructions to achieve a corresponding method flow or function. The processor described in this embodiment can be used for operating a discrete fracture network modeling method for fault damage zones.

[0167] In another embodiment, a storage medium is provided, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device used to store programs and data. It is understood that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and extended storage media supported by the terminal device. The computer-readable storage medium provides storage space that stores the terminal's operating system. Furthermore, this storage space also stores one or more instructions suitable for loading and execution by a processor; these instructions can be one or more computer programs (including program code). It should be noted that the computer-readable storage medium here can be high-speed RAM or non-volatile memory, such as at least one disk storage device.

[0168] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of the discrete fracture network modeling method for fault damage zones in the above embodiments; one or more instructions in the computer-readable storage medium are loaded and executed by a processor.

[0169] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. This computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0170] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is used as an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above.

[0171] The above-described embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention, and should all be included within the protection scope of the present invention.

Claims

1. A method for modeling discrete fracture networks in fault-damaged zones, characterized in that, The method is used for numerical simulation in geological engineering to generate a three-dimensional fracture network model for seepage or mechanical analysis, and specifically includes the following steps: S1. Construct a three-dimensional computational domain, set the fault plane within the computational domain, determine the fault center location and its attitude parameters, including dip angle and dip direction; calculate the normal vector of the fault plane based on the fault geometric parameters, and establish a local coordinate system based on the normal vector; S2. Generate background cracks within the computational domain. The spatial location of the background cracks is represented by the crack center point. , , The coordinates are uniformly distributed in the range of their respective coordinate axes in the global coordinate system. S3. Generating fault-controlled fractures within the computational domain, including: S31. In the local coordinate system, generate the coordinates of the fracture center in the tangential direction parallel to the fault plane, wherein the tangential coordinates follow a uniform random distribution. S32. Generate the normal distance from the fracture center to the fault plane, wherein the normal distance follows a power-law distribution; S33. Combine the tangential coordinates generated in step S31 with the normal distance generated in step S32 to obtain the coordinates of the fracture center in the local coordinate system. S34. The coordinates of the fracture center in the local coordinate system are mapped to the global coordinate system through coordinate transformation to obtain the actual location distribution of the fault-controlled fracture in three-dimensional space. S4. Generate fracture orientation parameters, wherein the orientation parameters are described using a Fisher distribution and mapped to a preset average orientation direction through orientation transformation; S5. The size parameters of the generated crack, wherein the size parameters are described by a log-normal distribution; S6. Based on the fracture center location, size and orientation generated in steps S2 to S5, construct a three-dimensional fracture geometric model; S7. Superimpose the background fractures and the fault-controlled fractures to construct a complete discrete fracture network model of the fault damage zone, and output the fracture geometry, spatial location and attribute parameters according to a preset data format.

2. The method according to claim 1, characterized in that, In step S1, the unit normal vector of the fault plane According to the fault dip angle and tendencies In Cartesian coordinates, it is defined as: ； The local coordinate system has the fault center as its origin and includes mutually orthogonal coordinates. axis, shaft and Axis; where, The axial direction is taken as the unit normal vector of the fracture surface. direction, The axial direction is taken as the fault dip direction. axial direction from shaft and The axis is determined according to the right-hand rule.

3. The method according to claim 1, characterized in that, In step S2, the coordinates of the center point of the background fracture are generated in the following way: within the boundary of the computational domain, respectively for... , , Independent random sampling is performed in three coordinate directions, so that ； Where U represents a uniform distribution. These represent the lower and upper limits for sampling in each coordinate direction, respectively.

4. The method according to claim 1, characterized in that, In step S32, the normal distance Follows a power-law distribution ,in The power-law decay exponent, The normal distance is generated using an inverse transform sampling method, and its expression is: , For interval Uniformly distributed random numbers on the array.

5. The method according to claim 5, characterized in that, Step S32 further includes: performing positive and negative expansion processing on the generated normal distance samples to characterize the distribution characteristics of fractures on both sides of the fault.

6. The method according to claim 1, characterized in that, In step S31, the tangential coordinates are included in the local coordinate system. shaft and The components along the axial direction are uniformly distributed: ,in These are the computational domains in the local tangential coordinate system. , The boundary range in the direction.

7. The method according to claim 1, characterized in that, In step S4, the method for generating fracture orientation parameters includes: S41. In the local spherical coordinate system, generate the initial direction unit vector of the fracture based on the Fisher distribution. ; S42. Using a direction cosine matrix constructed based on a preset average dip angle and average dip direction. The initial direction unit vector The rotation mapping to the average attitude direction in the global coordinate system yields... ; S43. Perform inverse calculation of the orientation parameters on the rotated direction vector to obtain the dip angle and dip direction of the fracture.

8. The method according to claim 1, characterized in that, In step S5, the crack size parameter Follows a log-normal distribution ,in and These are the mean and standard deviation in the logarithmic space, respectively. Based on the mean in real space and standard deviation The distribution parameters satisfy: .

9. The method according to claim 1, characterized in that, In step S6, the three-dimensional fracture geometry model is described using a continuous disk model. Each fracture is uniquely determined by its center position, orientation parameters, and radius. To meet the requirements of numerical calculation and data export, the boundary of the continuous disk is discretized, and the circumference is uniformly divided into multiple discrete points. The fracture geometry in the local coordinate system is mapped to the three-dimensional global coordinate system through coordinate transformation.

10. The method according to claim 1, characterized in that, In step S7, the preset data format is a fracture data file format compatible with FracMan software.

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