Three-dimensional space carving method and system for strike-slip faults based on multi-dimensional gradient voting

Abstract

The present invention discloses a three-dimensional spatial carving method and system for strike-slip faults based on multidimensional gradient voting. The method extracts discontinuous attributes of strike-slip faults based on post-stack seismic data of a target area; establishes a multidimensional gradient square matrix, and performs matrix decomposition on the multidimensional gradient matrix to obtain eigenvalues ​​and eigenvectors of the multidimensional gradient matrix; uses the matrix as the initial seed point, performs thresholding on all seed points, obtains seed points required for voting, and performs voting calculation on the obtained seed points; superimposes all voting results, and decomposes the eigenvalues ​​of the voting results; traverses all seed points and superimposes them to obtain a multidimensional gradient voting data body, performs statistical comparison with reference to drilling and logging data information, determines the threshold range of strike-slip faults and cracks, performs thresholding on the multidimensional gradient voting data body, and realizes three-dimensional spatial carving of strike-slip faults. The method can enhance the integrity and continuity of strike-slip faults, facilitates the calculation of the quantitative volume of strike-slip faults, and solves the problems of large carving errors and unclear structural features in the prior art.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas exploration, and relates to a three-dimensional space carving method and system for strike-slip faults based on multi-dimensional gradient voting. Background Art

[0002] Strike-slip faults are both oil and gas migration pathways and oil and gas enrichment sites. Accurate characterization of strike-slip faults is the key to the exploration and development of carbonate reservoirs.

[0003] Strike-slip faults are characterized by small throws and steep dips. Identifying them on seismic profiles and describing their spatial location and volume are recognized challenges. In industry, the spatial quantitative description of carbonate strike-slip fault systems primarily relies on three-dimensional spatial carving methods.

[0004] However, due to the limitations of the lateral resolution of seismic data, the strike-slip faults represented by the discontinuity attributes extracted based on seismic data are large in lateral scale. In addition, due to the influence of noise in the seismic data, its discontinuity attributes often have problems such as blurred boundaries, excessive fragmentation, and loss of detailed information, which leads to large scale errors in the threshold carving results and unclear structural features. Summary of the Invention

[0005] The purpose of the present invention is to solve the problems in the prior art and provide a three-dimensional spatial carving method and system for strike-slip faults based on multi-dimensional gradient voting, extracting discontinuous attributes that are more sensitive to strike-slip faults, such as instantaneous amplitude, coherence volume, GST (structural gradient tensor), AFE (automatic fault extraction) and other attributes. Based on the attributes, a multi-dimensional gradient matrix is ​​established, and the eigenvalues ​​and eigenvectors of the matrix obtained by decomposition are used as initial seed points. The seed points are thresholded to obtain the required seed points, and the obtained seed points are voted. All the voting calculation results are superimposed to form a final voting data body. Drilling and logging are used to perform statistics and determine the threshold conditions. At the same time, the discontinuous attributes are thresholded to achieve three-dimensional spatial carving of strike-slip faults.

[0006] In order to achieve the above object, the present invention adopts the following technical solutions:

[0007] The three-dimensional space carving method of strike-slip faults based on multi-dimensional gradient voting includes the following steps:

[0008] S1: Extract discontinuity attribute data of strike-slip faults based on post-stack seismic data in the target area;

[0009] S2: Establish a multidimensional gradient square matrix based on the discontinuous attribute data, and perform matrix decomposition on the multidimensional gradient square matrix to obtain the eigenvalues ​​and eigenvectors of the multidimensional gradient square matrix;

[0010] S3: Using the eigenvalues ​​and eigenvectors of the multidimensional gradient square matrix as initial seed points, thresholding all initial seed points to obtain the seed points required for voting, and performing voting calculations on the obtained seed points required for voting to obtain voting results;

[0011] S4: Superimpose all voting results in S3 and decompose the eigenvalues ​​of the voting results;

[0012] S5: By traversing all seed points and superimposing them, a multidimensional gradient voting data volume is obtained. Statistical comparison is performed with reference to drilling or logging data information to determine the threshold range of strike-slip faults. The multidimensional gradient voting data volume is thresholded to achieve three-dimensional spatial carving of strike-slip faults.

[0013] A further improvement of the present invention is:

[0014] In step S1, the structural gradient tensor, coherence volume, variance volume or maximum likelihood attribute of the target area is obtained to preliminarily describe the strike-slip fault and obtain the discontinuity attribute of the strike-slip fault.

[0015] In step S2, the multidimensional gradient square matrix established is:

[0016]

[0017] Among them, I represents each sampling point, and x and y represent two directions in the plane.

[0018] Decompose the multidimensional gradient square matrix:

[0019] G=λ1e1e1 T +λ2e2e2 T (λ1≥λ2≥0) (2)

[0020] Among them, λ i (i=1,2) represents the eigenvalue; e i (i=1,2) represents the eigenvector.

[0021] In step S3, thresholding all seed points to obtain the seed points required for voting includes:

[0022] The difference between the eigenvalues ​​λ1 and λ2 is calculated, and the point where the difference satisfies λ1-λ2>λ2 is recorded as the seed point required for voting.

[0023] The step S3 further comprises the following steps:

[0024] The seed point required for each vote is used as the voter seed point, and each other seed point is used as the receiver seed point for voting. During the voting process, the attenuation function DF determines the change in the voting field strength centered on the seed point:

[0025]

[0026] Where θ represents the angle between the tangent line of the curvature circle from the voter's seed point to the receiver's seed point and the straight line formed by the two points; The arc length of the arc of curvature between two points; Indicates the curvature of the arc; Controls the degree of curvature attenuation; σ represents the voting scale factor, and its value is set by the user;

[0027] During the voting process, the voting operator received by the receiver seed point from the voter seed point is:

[0028]

[0029] Among them, N P Represents the normal vector of the receiver seed point.

[0030] The step S4 comprises the following steps:

[0031] Superimpose the neighborhood voting results of each seed point to form a new two-dimensional matrix

[0032]

[0033] Among them, V represents the cumulative votes; K represents the number of pixels in the neighborhood of the voting area center;

[0034] Decompose formula (5) into:

[0035] V=(λ1-λ2)e1e1 T +λ2(e1e1 T +e2e2 T ) (6)

[0036] Among them, e1e1 T represents the stick tensor, λ1-λ2 represents the significance of the stick tensor; e1e1 T +e2e2 T represents the spherical tensor, and λ2 represents the significance of the circular tensor.

[0037] The strike-slip fault 3D space carving system based on multi-dimensional gradient voting includes a data extraction module, a matrix construction and decomposition module, a seed voting module, a voting result decomposition module, and a 3D space carving module.

[0038] The data extraction module extracts discontinuity attribute data of strike-slip faults based on post-stack seismic data in the target area;

[0039] The matrix construction and decomposition module builds a multidimensional gradient square matrix based on discontinuous attribute data, and performs matrix decomposition on the multidimensional gradient square matrix to obtain the eigenvalues ​​and eigenvectors of the multidimensional gradient square matrix;

[0040] The seed voting module is used to use the eigenvalues ​​and eigenvectors of the multidimensional gradient square matrix as initial seed points, threshold all initial seed points, obtain the seed points required for voting, and perform voting calculations on the obtained seed points required for voting;

[0041] The voting result decomposition module is used to superimpose all voting calculation results and decompose the eigenvalues ​​of the voting calculation results;

[0042] The three-dimensional space carving module is used to traverse all seed points and superimpose them to obtain a multi-dimensional gradient voting data volume. Statistical comparison is performed with reference to drilling and logging data information to determine the threshold range of strike-slip faults and cracks. The multi-dimensional gradient voting data volume is thresholded to achieve three-dimensional space carving of strike-slip faults.

[0043] A terminal device comprises a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the methods of the present invention when executing the computer program.

[0044] A computer-readable storage medium stores a computer program, wherein the computer program, when executed by a processor, implements the steps of any method according to the present invention.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] The present invention discloses a three-dimensional spatial carving method for strike-slip faults based on multidimensional gradient voting. Based on post-stack seismic data of the target area, the discontinuous attributes of the strike-slip faults are extracted. Small-scale voting through discrete seed points can refine the structural characteristics of the strike-slip faults in the attributes, reduce the amplification effect, improve the resolution, enhance the integrity and continuity of the strike-slip faults, and facilitate the calculation of the quantitative volume of the strike-slip faults. The three-dimensional carving of the strike-slip faults formed by the present invention makes the subsequent quantitative description of the strike-slip faults more accurate, can mine deep attribute information, reduce errors, make the structural characteristics of the three-dimensional carving clearer, and can provide more accurate connectivity analysis and reserve description. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the embodiments. It should be understood that the following drawings only illustrate certain embodiments of the present invention and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on these drawings without paying any creative work.

[0048] Figure 1 This is a flow chart of a method for three-dimensional space carving of strike-slip faults based on multi-dimensional gradient voting according to an embodiment of the present invention;

[0049] Figure 2 This is a discontinuity attribute map of post-stack seismic data according to an embodiment of the present invention;

[0050] Figure 3 This is a rendering of a three-dimensional grid model of an Ordovician carbonate strike-slip fault provided by an embodiment of the present invention;

[0051] Figure 4 This is a rendering of the three-dimensional porosity model of the Ordovician carbonate strike-slip fault provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0052] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0053] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0054] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0055] In the description of the embodiments of the present invention, it should be noted that if the terms "upper," "lower," "horizontal," "inner," etc. appear, the orientation or positional relationship indicated is based on the orientation or positional relationship shown in the accompanying drawings, or the orientation or positional relationship in which the inventive product is typically placed when in use. These terms are merely for the convenience of describing the present invention and simplifying the description, and do not indicate or imply that the device or component referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. In addition, the terms "first," "second," etc. are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0056] In addition, if the term "horizontal" appears, it does not mean that the component must be absolutely horizontal, but can be slightly tilted. For example, "horizontal" only means that its direction is more horizontal than "vertical", and does not mean that the structure must be completely horizontal, but can be slightly tilted.

[0057] In the description of the embodiments of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to internal connections between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0058] The present invention is described in further detail below with reference to the accompanying drawings:

[0059] See also Figure 1 The embodiment of the present invention discloses a three-dimensional spatial carving method for strike-slip faults based on multi-dimensional gradient voting, which extracts discontinuity attributes that are more sensitive to strike-slip faults, such as instantaneous amplitude, coherence volume, GST (structural gradient tensor), AFE (automatic fault extraction) and other attributes. Based on these attributes, drilling and logging are used to perform statistics and determine threshold conditions, and at the same time, thresholds are set for the discontinuity attributes to achieve three-dimensional spatial carving of strike-slip faults.

[0060] Step 1: Based on the post-stack seismic data, discontinuity attributes sensitive to strike-slip faults are extracted from the seismic data in the target layer range, such as structural gradient tensor, coherence volume, variance volume, maximum likelihood attributes, etc., to preliminarily describe the strike-slip faults.

[0061] Step 2: Decompose the discontinuous attribute data into multi-dimensional gradient quadratic code G. Taking two dimensions as an example,

[0062]

[0063] Where I is each sampling point, x and y are two directions in the plane; taking the square makes the gradients with the same direction but different directions can enhance each other and not cancel each other.

[0064] For the second-order non-negative matrix G, it can be decomposed into

[0065] G=λ1e1e1 T +λ2e2e2 T (λ1≥λ2≥0) (2)

[0066] where λ i (i=1,2) represents the eigenvalue; e i (i=1,2) represents the eigenvector.

[0067] Step 3: When point I is a breakpoint, the data is highly anisotropic, and the eigenvalues ​​of the multidimensional gradient matrix are expressed as λ1-λ2>>λ2. This highly anisotropic point is recorded as the seed point. The seed point is superimposed on the voting field to improve the continuity and integrity of the feature information. According to the Gestalt principle, during the voting process, the decay function (DF) determines the intensity change of the voting field centered on the seed point.

[0068]

[0069] Where: θ is the angle between the tangent line of the curvature circle from the voter seed point to the receiver seed point and the straight line formed by the two points. The arc length of the arc of curvature between two points; Indicates the curvature of the arc; Controls the degree of curvature attenuation; σ is the voting scale factor, the size of which is set by the user.

[0070] During the voting process, the voting operator received by the receiving seed point from the voter seed point is:

[0071]

[0072] where N P is the normal vector of the receiver seed point.

[0073] Step 4: Overlay the neighborhood voting results of each seed point to form a new two-dimensional matrix:

[0074]

[0075] Where V represents the cumulative voting result; K represents the number of pixels in the neighborhood of the voting area center. The tensor after voting can be decomposed into:

[0076] V=(λ1-λ2)e1e1 T +λ2(e1e1 T +e2e2T ) (6)

[0077] Where: e1e1 T It is defined as a stick tensor, and λ1-λ2 represents the significance of the stick tensor;

[0078] e1e1 T +e2e2 T Defined as a spherical tensor, λ2 represents the significance of the circular tensor. If λ1-λ2>λ2, the dominant tensor is a rod tensor, and the seed point is most likely located on a characteristic curve with e1 as the normal. If λ1≈λ2>0, the seed point is likely located at the intersection of multiple characteristic curves, or is located in a region where all directions are similar and there are no linear features. When both λ1 and λ2 are extremely small, the point is likely an outlier.

[0079] Step 5: Traverse all seed points in steps 3 and 4 to calculate the multidimensional gradient voting data volume. Statistical comparison is performed with reference to drilling and logging data information to determine the threshold range of strike-slip faults and cracks. The multidimensional gradient voting data volume is thresholded to achieve three-dimensional spatial carving of strike-slip faults.

[0080] Through the above specific steps, a three-dimensional space carving method for strike-slip faults based on multi-dimensional gradient voting can be formed.

[0081] The method disclosed in the embodiment of the present invention has the following advantages:

[0082] 1. Multidimensional gradient voting can enhance the structural discontinuity information in seismic attributes and improve the integrity and continuity of strike-slip faults.

[0083] 2. Through small-scale voting of discrete seed points, the structural features of strike-slip faults in the attributes can be refined, the resolution can be improved, and it is easier for personnel to interpret;

[0084] 3. The three-dimensional spatial carving method of strike-slip faults based on multi-dimensional gradient voting makes the subsequent quantitative description of strike-slip faults more accurate, which is manifested as more precise connectivity analysis and reserve description.

[0085] The embodiment of the present invention discloses a specific implementation process:

[0086] The embodiment of the present invention discloses a method for carving strike-slip faults in Ordovician carbonate rocks, which specifically includes the following steps:

[0087] Step 1: Extract post-stack seismic discontinuity attributes

[0088] The maximum likelihood attributes of the post-stack earthquakes were extracted using 5 grids in the vertical and horizontal directions to preliminarily describe the strike-slip fault. Figure 2 .

[0089] Step 2: Establish multidimensional gradient square coding and eigenvalue decomposition

[0090] Based on the maximum likelihood attributes of the strike-slip fault obtained in step 1 of the embodiment of the present invention, the differential gradient of each point in the three-dimensional space of the attribute body is calculated in the three coordinate directions in the space, and a multidimensional gradient square matrix is ​​established in the encoding format in step 2, that is, each grid point corresponds to a multidimensional gradient matrix.

[0091] Perform matrix decomposition for each multidimensional gradient matrix,

[0092] G=λ1e1e1 T +λ2e2e2 T (λ1≥λ2≥0) (2)

[0093] where λ i (i=1,2) represents the eigenvalue; e i (i=1,2) represents the feature vector, which is used for subsequent voting calculations.

[0094] Step 3: Calculation of voting operator in voting domain

[0095] In this embodiment of the present invention, the eigenvalues ​​and eigenvectors of all gridded multidimensional gradient matrices obtained in step 2 are used to obtain the initial seed points. In the horizontal direction, we interpolate the eigenvalues ​​λ1 and λ2. When the interpolated value meets the threshold condition, we consider the anisotropy exhibited by the point attribute to be strong. By applying a threshold to the entire model, we can obtain the seed points required for voting. Each seed point is then used as a voter seed point, and all other seed points are used as receiver seed points for voting.

[0096] During the voting process, the decay function (DF) determines the change in voting strength centered on the seed point.

[0097] The expression for voting strength is

[0098]

[0099] See also Figure 3 , Schematic diagram of voting rules, C represents the center of the circle, seed point O represents the voter, seed point P represents the receiver, the double arrow represents the normal direction, and θ is the angle between the tangent line of the curvature circle of seed point O and the straight line OP. N O and N P are the normal vectors of point O and point P respectively; represents the arc length of OP; Indicates the curvature of the arc; Controls the degree of curvature attenuation; σ is the voting scale factor, the size of which is defined by the user.

[0100] The voting operator received by point P from point O is

[0101]

[0102] Among them, N P =N O [-sin(2θ),cos(2θ)] T .

[0103] Step 4: Superimpose voting results and perform eigenvalue decomposition of voting results

[0104] By superimposing all voting fields of each central seed point and accumulating all voting results, a new matrix can be formed at each seed point:

[0105]

[0106] Where: V represents the cumulative votes; K represents the number of pixels in the neighborhood of the voting area center.

[0107] The matrix after voting is decomposed into:

[0108] V=(λ1-λ2)e1e1 T +λ2(e1e1 T +e2e2 T ) (6)

[0109] Where: e1e1 T Defined as a stick tensor, λ1-λ2 represents the significance of the stick tensor; e1e1 T +e2e2 T Defined as a spherical tensor, λ2 represents the significance of the circular tensor.

[0110] If λ1-λ2>λ2, it means that the dominant tensor is a stick tensor, and the seed point is most likely located on the characteristic curve with e1 as the normal; if λ1≈λ2>0, it means that the seed point is likely to be located at the intersection of multiple characteristic curves, or the point is located in a region where all directions are approximate and there are no linear features; when both λ1 and λ2 are extremely small, it means that the point may be an outlier.

[0111] Step 5: traverse the seed points to form a data volume and threshold carving

[0112] See also Figure 4, traverse all seed points and superimpose them to form the calculation result of multi-dimensional gradient voting, which is the voting body. Statistical comparison is performed with reference to drilling and logging data information to determine the threshold range of strike-slip faults and cracks, and threshold processing is performed on the voting body based on this numerical range. In actual operation, according to the actual situation of drilling and logging, the threshold range is determined after multiple rounds of testing. After the voting body data is thresholded, the three-dimensional spatial carving of strike-slip faults is realized.

[0113] The three-dimensional spatial representation of strike-slip faults obtained using the method disclosed in the embodiments of the present invention can enhance the structural discontinuity characteristics in seismic attributes, intuitively reflecting the spatial location, morphology, and changes of strike-slip faults, while facilitating the calculation of their quantified volume. The three-dimensional spatial sculpture of strike-slip faults established using this method can mine deep-seated attribute information, enhancing the integrity and continuity of strike-slip fault sculpture results. Small-scale voting can refine strike-slip faults, reduce the amplification effect, facilitate the identification of strike-slip fault patterns, and make strike-slip fault sculpture results more realistic.

[0114] The embodiment of the present invention discloses a strike-slip fault three-dimensional space carving system based on multi-dimensional gradient voting, which is characterized by comprising a data extraction module, a matrix construction and decomposition module, a seed voting module, a voting result decomposition module and a three-dimensional space carving module;

[0115] The data extraction module extracts discontinuity attribute data of strike-slip faults based on post-stack seismic data in the target area;

[0116] The matrix construction and decomposition module builds a multidimensional gradient square matrix based on discontinuous attribute data, and performs matrix decomposition on the multidimensional gradient square matrix to obtain the eigenvalues ​​and eigenvectors of the multidimensional gradient square matrix;

[0117] The seed voting module is used to use the eigenvalues ​​and eigenvectors of the multidimensional gradient square matrix as initial seed points, threshold all initial seed points, obtain the seed points required for voting, and perform voting calculations on the obtained seed points required for voting;

[0118] The voting result decomposition module is used to superimpose all voting calculation results and decompose the eigenvalues ​​of the voting calculation results;

[0119] The three-dimensional space carving module is used to traverse all seed points and superimpose them to obtain a multi-dimensional gradient voting data volume. Statistical comparison is performed with reference to drilling and logging data information to determine the threshold range of strike-slip faults and cracks. The multi-dimensional gradient voting data volume is thresholded to achieve three-dimensional space carving of strike-slip faults.

[0120] A schematic diagram of a terminal device provided in one embodiment of the present invention. The terminal device in this embodiment includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of each of the aforementioned method embodiments are implemented. Alternatively, when the processor executes the computer program, the functions of each module / unit in each of the aforementioned device embodiments are implemented.

[0121] The computer program may be divided into one or more modules / units, which are stored in the memory and executed by the processor to accomplish the present invention.

[0122] The terminal device may be a computing device such as a desktop computer, a notebook computer, a PDA, a cloud server, etc. The terminal device may include, but is not limited to, a processor and a memory.

[0123] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0124] The memory may be used to store the computer programs and / or modules, and the processor implements various functions of the terminal device by running or executing the computer programs and / or modules stored in the memory and calling the data stored in the memory.

[0125] If the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the present invention implements all or part of the process in the above-mentioned embodiment method, and can also be completed by instructing the relevant hardware through a computer program. The computer program can be stored in a computer-readable storage medium. When the computer program is executed by a processor, it can implement the steps of each of the above-mentioned method embodiments. The computer program includes computer program code, which can be in source code form, object code form, executable file or some intermediate form. The computer-readable medium may include: any entity or device capable of carrying the computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium. It should be noted that the content contained in the computer-readable medium can be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0126] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A three-dimensional space carving method for strike-slip faults based on multi-dimensional gradient voting, characterized by: The following steps are involved: S1: Extract discontinuity attribute data of strike-slip faults based on post-stack seismic data in the target area; S2: Establish a multidimensional gradient square matrix based on the discontinuous attribute data, and perform matrix decomposition on the multidimensional gradient square matrix to obtain the eigenvalues ​​and eigenvectors of the multidimensional gradient square matrix; S3: Using the eigenvalues ​​and eigenvectors of the multidimensional gradient square matrix as initial seed points, thresholding all initial seed points to obtain the seed points required for voting, and performing voting calculations on the obtained seed points required for voting to obtain voting results; S4: Superimpose all voting results in S3 and decompose the eigenvalues ​​of the voting results; S5: By traversing all seed points and superimposing them, a multi-dimensional gradient voting data volume is obtained. Statistical comparison is performed with reference to drilling or logging data information to determine the threshold range of strike-slip faults. The multi-dimensional gradient voting data volume is thresholded to achieve three-dimensional spatial carving of strike-slip faults. In step S2, the multidimensional gradient square matrix established is: in, Represents each sampling point, x and y represent two directions in the plane; Decompose the multidimensional gradient square matrix: in, represents the eigenvalue; represents the eigenvector; In step S3, thresholding all seed points to obtain the seed points required for voting includes: The eigenvalue and Find the difference and satisfy the difference The point is recorded as the seed point required for voting; The step S3 further comprises the following steps: The seed point required for each vote is used as the voter seed point, and each other seed point is used as the receiver seed point for voting. During the voting process, the attenuation function DF determines the change in the voting field strength centered on the seed point: in, The angle between the tangent line of the curvature circle from the voter's seed point to the receiver's seed point and the straight line formed by the two points; The arc length of the arc of curvature between two points; Indicates the curvature of the arc; Controls the degree of curvature attenuation; σ represents the voting scale factor, and its value is set by the user; During the voting process, the voting operator received by the receiver seed point from the voter seed point is: in Represents the normal vector of the receiver seed point; The step S4 comprises the following steps: Superimpose the neighborhood voting results of each seed point to form a new two-dimensional matrix Among them, V represents the cumulative votes; K represents the number of pixels in the neighborhood of the voting area center; Decompose equation (5) into: in, represents the rod tensor, Indicates the significance of the stick tensor; represents the spherical tensor, Represents the significance magnitude of the circular tensor.

2. The strike-slip fault three-dimensional space carving method based on multi-dimensional gradient voting according to claim 1 is characterized in that: In step S1, the structural gradient tensor, coherence volume, variance volume or maximum likelihood attribute of the target area is obtained to preliminarily describe the strike-slip fault and obtain the discontinuity attribute of the strike-slip fault.

3. The strike-slip fault three-dimensional space carving system based on multi-dimensional gradient voting according to the method of claim 1 is characterized in that: It includes data extraction module, matrix construction and decomposition module, seed voting module, voting result decomposition module and three-dimensional space carving module; The data extraction module extracts discontinuity attribute data of strike-slip faults based on post-stack seismic data in the target area; The matrix construction and decomposition module builds a multidimensional gradient square matrix based on discontinuous attribute data, and performs matrix decomposition on the multidimensional gradient square matrix to obtain the eigenvalues ​​and eigenvectors of the multidimensional gradient square matrix; The seed voting module is used to use the eigenvalues ​​and eigenvectors of the multidimensional gradient square matrix as initial seed points, threshold all initial seed points, obtain the seed points required for voting, and perform voting calculations on the obtained seed points required for voting to obtain voting results; The voting result decomposition module is used to superimpose all voting results and decompose the eigenvalues ​​of the voting results; The three-dimensional space carving module is used to traverse all seed points and superimpose them to obtain a multi-dimensional gradient voting data volume. Statistical comparison is performed with reference to drilling and logging data information to determine the threshold range of strike-slip faults and cracks. The multi-dimensional gradient voting data volume is thresholded to achieve three-dimensional space carving of strike-slip faults.

4. A terminal device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 2 are implemented.

5. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 are implemented.

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