Fault automatic interpretation method and device, computer equipment and storage medium

Abstract

The invention discloses a fault automatic interpretation method and device, computer equipment and a storage medium, and the method comprises the steps: carrying out the pre-stack anisotropy inversion of an input azimuth gather, obtaining a fracture strength horizon slice, and carrying out the statistics of a histogram of the fracture strength horizon slice, performing fault automatic interpretation on the histogram according to a preset threshold value to obtain a fault attribute slice, then extracting a fracture communication region of the fracture strength slice, and performing statistics on the extension length of the fracture communication region and filtering the region which does not meet the area threshold value to obtain the fracture communication region; and finally, skeleton extraction is performed on the fracture connected region to obtain a center line of the connected region, and a fault polygon is obtained, so that the fracture development direction can be accurately predicted, the fracture direction can be uniquely determined, the fault can be automatically explained, and the fast-paced requirement of oil-gas exploration and development is met.

Description

Technical Field

[0001] The present application relates to the technical field of oil and gas exploration, and in particular to a method, device, computer equipment and storage medium for automatic fault interpretation. Background Art

[0002] The oil and gas reservoirs formed by the accumulation of oil and gas in fracture-type closures are called fracture-type oil and gas reservoirs. Fracture-type oil and gas reservoirs occupy a very important position in the world's oil and natural gas production and reserves. The production of fracture-type oil and gas reservoirs accounts for more than half of the world's total oil and natural gas production. In domestic oil and gas exploration, fracture-type oil and gas reservoirs are an important exploration field. When exploring fracture-type oil and gas reservoirs, the most important thing is to analyze and understand the characteristics of fracture development. When fractures develop in the reservoir, they show anisotropic characteristics to the outside, so anisotropic parameters are used to analyze the characteristics of fracture development.

[0003] With the development of acquisition and processing technology and the improvement of anisotropy theory, fracture prediction technology has become diversified, from post-stack to pre-stack, and the prediction accuracy has gradually improved. For vertically arranged parallel fractures, they can be equivalent to the HTI medium (Horizontal Transverse Isotropy, i.e., transversely isotropic medium with a horizontal symmetry axis) model for study. The anisotropic combination parameters calculated in the prior art have large errors and cannot accurately describe the fracture development characteristics.

[0004] The rock physics model of fractured media describes the relationship between anisotropic parameters and reservoir fracture density, and the Ruger reflection coefficient formula gives the relationship between amplitude, anisotropic parameters and azimuth. Based on this, CRP (common reflection point) data sets of multiple azimuths are input to calculate anisotropic parameters to predict the fracture development characteristics of the reservoir, including fracture density and fracture extension direction. However, with the acceleration of the pace of oil and gas exploration and development, the efficiency of manual interpretation of faults is low and it is difficult to meet the needs of production. Therefore, how to automatically interpret faults has become one of the many problems that researchers in this field need to solve. Summary of the invention

[0005] The purpose of this application is to overcome the existing technical defects and provide a method, device, computer equipment and storage medium for automatic fault interpretation, which can accurately predict the direction of fracture development, uniquely determine the fracture direction, automatically interpret faults, and meet the fast-paced needs of oil and gas exploration and development.

[0006] The purpose of this application is achieved through the following technical solutions:

[0007] In a first aspect, the present application proposes a method for automatic fault interpretation, the method comprising:

[0008] Perform prestack anisotropic inversion on the input azimuth gather to obtain fracture strength slices along the layer, wherein the fracture strength slices along the layer represent fracture density and fracture direction;

[0009] Counting the histogram of the fracture strength along the layer slices, and automatically interpreting the histogram according to a preset threshold to obtain a fault attribute slice;

[0010] Extracting the fracture connected area of ​​the fracture strength slice, and respectively counting the extension length of the fracture connected area and filtering the area that does not meet the area threshold to obtain the fracture connected area;

[0011] The skeleton of the fracture connected area is extracted to obtain the center line of the connected area and the fault polygon.

[0012] In one possible implementation, the formula used for prestack anisotropy inversion is:

[0013]

[0014] in: R is the reflection coefficient, θ is the incident angle, For the measuring line, is the normal direction of the crack surface, R0 is the vertical incidence reflection coefficient, B iso is the AVO gradient of isotropic medium, B ani is the AVO gradient of anisotropic medium, α, β, Z, G are the longitudinal wave velocity, shear wave velocity, longitudinal wave impedance and shear modulus respectively, δ V and γ are anisotropy parameters.

[0015] In a possible implementation manner, the step of calculating the histogram of the fracture strength along the layer slices and automatically interpreting the histogram according to a preset threshold to obtain the fault attribute slices includes:

[0016] Counting the histogram of the fracture strength along the layer slices to obtain a fracture strength histogram;

[0017] Generate a cumulative probability curve according to the fracture strength histogram, and set the fracture strength of the cumulative probability as a preset threshold;

[0018] A fault attribute matrix is ​​obtained by slicing along the layer according to the preset threshold and the fracture strength.

[0019] In a possible implementation, the fault attribute matrix M potential The generation formula of (i,j) is:

[0020]

[0021] Among them, M intensity(i,j) is the fracture strength along the layer slice, m threshold is the preset threshold.

[0022] In a possible implementation manner, a graphics algorithm is used to extract the fracture connected region of the fault attribute slice.

[0023] In a possible implementation, the step of extracting the fracture connected region of the fault attribute slice includes:

[0024] By marking the target pixels in the fault attribute slice, each individual connected region forms a marked block to obtain the fractured connected region.

[0025] In a possible implementation, the step of performing skeleton extraction on the fracture connected region to obtain the center line of the connected region and obtain the fault polygon includes:

[0026] The fracture connected area is thinned to a pixel width, and the center line of the fault is extracted to obtain the fault polygon

[0027] In a second aspect, the present application also proposes a fault automatic interpretation device, the device comprising:

[0028] An inversion module is used to perform pre-stack anisotropic inversion on the input azimuth gather to obtain fracture strength slices along the layer, wherein the fracture strength slices along the layer represent fracture density and fracture direction;

[0029] A statistical module, used for statistically analyzing the histogram of the fracture strength along the layer slices, and automatically interpreting the histogram according to a preset threshold to obtain a fault attribute slice;

[0030] A fracture region extraction module is used to extract the fracture connected region of the fracture strength slice, and respectively count the extension length of the fracture connected region and filter the region that does not meet the area threshold to obtain the fracture connected region;

[0031] The fault centerline extraction module is used to perform skeleton extraction on the fracture connected area to obtain the centerline of the connected area and obtain the fault polygon.

[0032] In a third aspect, the present application further proposes a computer device, comprising a processor and a memory, wherein the memory stores a computer program, and the computer program is loaded and executed by the processor to implement the automatic fault interpretation method as described in any one of the first aspects.

[0033] In a fourth aspect, the present application further proposes a computer-readable storage medium, in which a computer program is stored. The computer program is loaded and executed by a processor to implement the automatic fault interpretation method as described in any one of the first aspects.

[0034] The above-mentioned main scheme of the present application and its further options can be freely combined to form multiple schemes, all of which are schemes that can be adopted and claimed for protection in the present application; and in the present application, (non-conflicting options) options and other options can also be freely combined. After understanding the scheme of the present application, those skilled in the art can understand that there are multiple combinations based on the prior art and common knowledge, all of which are technical schemes to be protected by the present application, and they are not exhaustively listed here.

[0035] The present application discloses a fault automatic interpretation method, device, computer equipment and storage medium, the method comprising: performing pre-stack anisotropic inversion on the input azimuth gather to obtain fracture strength slices along the layer, statistically analyzing the histogram of fracture strength slices along the layer, automatically interpreting the histogram according to a preset threshold to obtain fault attribute slices, extracting the fracture connected area of ​​the fault attribute slices, and statistically analyzing the extension length of the fracture connected area and filtering the area that does not meet the area threshold to obtain the fracture connected area, performing skeleton extraction on the fracture connected area to obtain the center line of the connected area, and obtaining the fault polygon. It can accurately predict the direction of fracture development, uniquely determine the fracture direction, automatically interpret faults, and meet the fast-paced needs of oil and gas exploration and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 A schematic flow chart of a fault automatic interpretation method proposed in an embodiment of the present application is shown.

[0037] Figure 2 A schematic diagram of the fracture strength slice along the layer proposed in the embodiment of the present application is shown.

[0038] Figure 3 The breaking strength statistical histogram proposed in the embodiment of the present application is shown.

[0039] Figure 4 A schematic diagram of fault attribute slicing proposed in an embodiment of the present application is shown.

[0040] Figure 5 A schematic diagram of the fracture connection area proposed in an embodiment of the present application is shown.

[0041] Figure 6a A 4-connected line contact diagram proposed in an embodiment of the present application is shown.

[0042] Figure 6b The 8-connected point contact diagram proposed in the embodiment of the present application is shown.

[0043] Figure 7 A schematic diagram of searching for connected areas proposed in an embodiment of the present application is shown.

[0044] Figure 8 The fault polygon proposed in the embodiment of the present application is shown. DETAILED DESCRIPTION

[0045] The following describes the embodiments of the present application through specific examples, and those skilled in the art can easily understand other advantages and effects of the present application from the contents disclosed in this specification. The present application can also be implemented or applied through other different specific embodiments, and the details in this specification can also be modified or changed in various ways based on different viewpoints and applications without departing from the spirit of the present application. It should be noted that the following embodiments and features in the embodiments can be combined with each other without conflict.

[0046] Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without making any creative work shall fall within the scope of protection of this application.

[0047] In the prior art, the methods for predicting fractures using seismic data are roughly divided into: post-stack seismic attribute analysis method and multi-wave multi-component prediction method. Post-stack seismic attributes mainly include coherence, curvature, ant body, etc., which can predict large and medium-scale faults and fractures. Coherence detects the discontinuity of geological bodies based on the similarity of adjacent channels of seismic waves; curvature attributes characterize the degree of formation folding based on the degree of deformation of the formation. The basic assumption is that there is a monotonic mapping relationship between the degree of formation structure and the degree of fracture development. For structural blank areas where fractures are developed, curvature attributes cannot be applied.

[0048] When performing AVAZ inversion, the anisotropic AVO gradient Bani (also known as the pseudo-anisotropic parameter) is used to describe the intensity of fracture development, and the parameters are used to represent the fracture surface normal. However, when the inversion solution formula is substituted for the parameter, the calculated anisotropic gradient Bani is ambiguous, which in turn affects the value of the fracture surface normal. The anisotropic combination parameters calculated in this way have large errors and cannot accurately characterize the fracture development characteristics. However, with the acceleration of the pace of oil and gas exploration and development, the efficiency of manual interpretation of faults is low and it is difficult to meet the needs of production. Therefore, how to automatically interpret faults has become one of the many problems that researchers in this field need to solve.

[0049] Therefore, in order to solve the above-mentioned problems, the embodiment of the present application proposes a method for automatic interpretation of faults, which performs skeleton extraction on the connected areas of the faults to obtain fault polygons, can accurately predict the direction of crack development, uniquely determine the direction of cracks, and automatically interpret faults to meet the fast-paced needs of oil and gas exploration and development. It will be described in detail below.

[0050] Please refer to Figure 1 , Figure 1 The flowchart of a fault automatic interpretation method proposed in an embodiment of the present application is shown, which includes the following steps:

[0051] Step S100: Perform pre-stack anisotropic inversion on the input azimuth gather to obtain fracture strength slices along the layer.

[0052] Step S200: Count the histogram of fracture strength along the layer slices, and perform automatic fault interpretation on the histogram according to a preset threshold to obtain fault attribute slices.

[0053] Step S300: extract the fracture connected regions of the fault attribute slice, and respectively count the extension lengths of the fracture connected regions and filter the regions that do not meet the area threshold to obtain the fracture connected regions.

[0054] Step S400: extract the skeleton of the fracture connected area to obtain the fault polygon.

[0055] The fracture strength slices along the layer represent the fracture density and fracture direction. The fracture strength slices along the layer are obtained by performing prestack anisotropic inversion on the input azimuth gathers. Figure 2 A schematic diagram of fracture strength slices along layers proposed in an embodiment of the present application is shown, a histogram of fracture strength slices along layers is statistically calculated, the histogram is automatically interpreted according to a preset threshold to obtain fault attribute slices, the fracture connected areas of the fault attribute slices are extracted, and the extension lengths of the fracture connected areas are statistically calculated and the areas that do not meet the area threshold are filtered to obtain the fracture connected areas, the skeleton of the fracture connected areas is extracted to obtain the fault polygons, which can accurately predict the direction of fracture development, uniquely determine the fracture direction, automatically interpret the faults, and meet the fast-paced needs of oil and gas exploration and development.

[0056] When seismic waves propagate to the interface, reflection and transmission phenomena occur. Under the condition of satisfying Snell's law, based on the basic stress-strain relationship, and the strain-displacement relationship, and under the premise of satisfying the displacement continuity and stress continuity boundary conditions on the interface, the Zoeppritz equation describing the reflection coefficient and transmission coefficient for longitudinal wave incidence and anisotropic media can be obtained. At this time, the Zoeppritz equation can accurately give the seismic wave reflection coefficient and transmission coefficient, but the Zoeppritz equation is a nonlinear equation and is difficult to be directly used for inversion calculations. Most of the later generations simplified it based on the Zoeppritz equation.

[0057] When the underground reservoir contains parallel vertical fractures, it is a transversely isotropic medium (HTI medium) with a horizontal symmetry axis. Assume that the velocity and density of the upper and lower layers are not much different and the anisotropic medium is a weakly anisotropic medium. When the fracture strength slices along the layer are obtained according to the prestack anisotropic inversion in step 100, since the reflection coefficient of the medium containing vertical parallel fractures (typical HTI medium) changes not only with the incident angle θ (AVO characteristics) but also with the azimuth angle φ (azimuthal anisotropy characteristics), it is simplified to the following formula through Ruger:

[0058]

[0059] in: R is the reflection coefficient, θ is the incident angle, is the angle between the measuring line and the normal of the crack surface, R0 is the vertical incidence reflection coefficient, B iso is the AVO gradient of isotropic medium, B ani is the AVO gradient of anisotropic medium, α, β, Z, G are the longitudinal wave velocity, shear wave velocity, longitudinal wave impedance and shear modulus respectively, δ V and γ are anisotropic parameters. represents the average of the parameters between the upper and lower layers of the medium, and Δ represents the difference between the parameters between the upper and lower layers of the medium.

[0060] When determining the normal direction of the crack surface along the layer slice of the fracture strength, the normal direction of the crack surface is expanded from the cosine term, and the formula used is:

[0061] R(θ,φ)=a1+(sin 2 θ)a2+(cos2φsin 2 θ)a3+(sin2φsin 2 θ)a4, where R(θ,φ) is the longitudinal wave reflection coefficient, a1=R0, R0 is the vertical incidence reflection coefficient, θ is the incident angle, B iso is the AVO gradient of isotropic medium, B ani is the AVO gradient of anisotropic medium, φ is the angle between the measuring line and the normal of the fracture surface, φ s represents the crack surface normal,

[0062] According to the formula for determining the normal direction of the fracture surface, the inverse equation group is constructed and solved to obtain X I =(a1,a2,a3,a4) T ,pass Calculate the anisotropic gradient B ani and the root mean square amplitude R rms The ratio e fault , e fault Indicates the fracture development intensity.

[0063] For small to medium angles of incidence, the third term in the Ruger equation can be omitted, and the Ruger equation can also be written as:

[0064] in

[0065] R0 represents the reflection coefficient when the longitudinal wave is incident vertically, Biso is the isotropic gradient, B ani is the anisotropic gradient.

[0066] By expanding the cosine term containing the crack azimuth, the above formula can be transformed into the following form:

[0067]

[0068] Where C1=R0,C2=B iso +B ani / 2,

[0069] Assuming that the number of times the common reflection point (CRP) is covered is N, and C1, C2, C3, and C4 are four unknown quantities, the above formula can be

[0070] Simplified to: AX = B (4)

[0071] in

[0072] The above equation is an overdetermined linear equation system. The crack inversion problem of the general algorithm is to solve the unknown quantity X in the above linear equation system. Solving the unknown vector X can solve R0, B iso , B ani and

[0073] R0=C1, B iso =C2-B ani / 2,

[0074] The step of obtaining the fault attribute slice in step S200 includes:

[0075] The fracture strength histogram is obtained by statistically analyzing the fracture strength histogram along the layer slices;

[0076] Generate a cumulative probability curve according to the fracture strength histogram, and set the fracture strength of the cumulative probability as a preset threshold;

[0077] The fault attribute matrix is ​​obtained by slicing along the layer according to the preset threshold and fracture strength.

[0078] Figure 4 A schematic diagram of the fault attribute slice proposed in the embodiment of the present application is shown, in which potential faults are screened by setting a fracture strength threshold. Specifically, a fracture strength histogram of the target reservoir is statistically analyzed, and data greater than the threshold is retained in combination with the fracture strength threshold to perform automatic fault interpretation.

[0079] The fracture strength along the layer slice is a matrix of ni×nx, where ni is the number of line numbers and nx is the number of track numbers. The histogram is statistically analyzed. Figure 3Shows the fracture strength statistical histogram proposed in the embodiment of the present application, and generates a cumulative probability curve. The fracture strength with a cumulative probability set to 80% can be set, a preset threshold is set to 0.4, and a matrix of the same size as the fracture strength matrix is set at the same time, where the fault attribute matrix M potential (i,j) is generated by the formula:

[0080]

[0081] M intensity (i,j) is the fracture strength along the layer slice, m threshold is the preset threshold. If the fracture strength is greater than or equal to the preset threshold, the fault attribute is 1; if the fracture strength is less than the preset threshold, the fault attribute is 0, where i is the line number index (1 < i < ni) and j is the trace number index (1 < j < nx).

[0082] In step S300, when extracting the fracture-connected regions of the fault attribute slices, a graphics algorithm is used. The extension lengths of the connected regions are statistically counted and numbered in sequence, the regions with small areas are filtered, and according to whether the matrix elements are adjacent, the fault attribute matrix is divided into multiple regions. Each region is internally connected, while the regions are not connected. Each region is numbered according to the connected area ranking. The largest area is numbered 1, and so on. Finally, the fracture-connected regions are obtained (each connected region is a fault development region, including the core part of the fault and the boundaries of the hanging wall and footwall). Figure 5 Shows the schematic diagram of the fracture-connected regions proposed in the embodiment of the present application.

[0083] In a possible implementation manner, the step of extracting the fracture-connected regions of the fault attribute slices includes:

[0084] By marking the target pixels in the fault attribute slices, each individual connected region forms an identified block to obtain the fracture-connected regions.

[0085] The marking of the connected regions is achieved by marking the target pixels in the image, so that each individual connected region forms an identified block. Further, geometric parameters such as the contour, circumscribed rectangle, centroid, and invariant moments of these blocks can be obtained.

[0086] Please refer to Figure 6a and Figure 6b , Figure 6a Shows the 4-connected line contact diagram proposed in the embodiment of the present application. Figure 6b Shows the 8-connected point contact diagram proposed in the embodiment of the present application.

[0087] Two necessary conditions for the connection of every two pixels among them are: whether the positions of two pixels p and q are adjacent, and whether the gray values of the two pixels satisfy a specific similarity criterion (or are equal).

[0088] (1) If q is in the set N4(p), the two pixels are said to be 4-connected;

[0089] (2) If q is in the set N8(p), the two pixels are said to be 8-connected.

[0090] When marking connected regions, scan the image line by line, and call each row of continuous target pixels a run. By traversing each row of the image, the connected regions can be divided, and the connected areas can be counted at the same time. Figure 7 A schematic diagram of searching for connected areas proposed in an embodiment of the present application is shown.

[0091] The first row obtains two groups: [2,6] and [10,13], labeled 1 and 2 respectively.

[0092] The second row also has two clusters: [6,7] and [9,10], both of which are connected to the cluster in the previous row and are marked with the cluster in the previous row, i.e. 1 and 2.

[0093] In the third row, we get two more cliques: [2,4] and [7,8]. Clique [2,4] is not connected to the previous row, so we number it 3. Clique [7,8] is connected to both cliques in the previous row, so we number it the smallest of the two (i.e., 1). We also define (1, 2) as an equivalent pair, and finally correct the equivalent pair numbers.

[0094] In one possible implementation, please refer to Figure 8 , Figure 8 The fault polygon proposed in the embodiment of the present application is shown. The steps of extracting the skeleton of the fracture connected area to obtain the center line of the connected area and obtaining the fault polygon include:

[0095] The connected region of the fracture is thinned to a width of one pixel, the center line of the fault is extracted to obtain the center line of the connected region, and the fault polygon is obtained.

[0096] Read the binary image and display it, remove the interior pixels to preserve the shape wheel, and get the image skeleton.

[0097] A possible implementation of a fault automatic interpretation device is provided below, which is used to execute the various execution steps and corresponding technical effects of the fault automatic interpretation method shown in the above embodiments and possible implementations. The fault automatic interpretation device includes:

[0098] The inversion module is used to perform pre-stack anisotropic inversion on the input azimuth gathers to obtain fracture strength slices along the layer. The fracture strength slices along the layer represent the fracture density and fracture direction.

[0099] The statistical module is used to calculate the histogram of fracture strength along the layer slices, and automatically interpret the histogram according to the preset threshold to obtain the fault attribute slices;

[0100] The fracture region extraction module is used to extract the fracture connected region of the fault attribute slice, and to obtain the fracture connected region by counting the extension length of the fracture connected region and filtering the region that does not meet the area threshold;

[0101] The fault centerline extraction module is used to extract the skeleton of the fracture connected area to obtain the centerline of the connected area and obtain the fault polygon.

[0102] This preferred embodiment provides a computer device, which can implement the steps in any embodiment of the automatic fault interpretation method provided in the embodiments of the present application. Therefore, the beneficial effects of the automatic fault interpretation method provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0103] Those skilled in the art can understand that all or part of the steps in the various methods of the above embodiments can be completed by instructions, or by controlling related hardware through instructions, and the instructions can be stored in a computer-readable storage medium and loaded and executed by a processor. To this end, an embodiment of the present application provides a storage medium, which stores multiple instructions, and the instructions can be loaded by a processor to execute the steps of any embodiment of the fault automatic interpretation method provided in the embodiment of the present application.

[0104] The storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0105] Since the instructions stored in the storage medium can execute the steps in any of the embodiments of the automatic fault interpretation method provided in the embodiments of the present application, the beneficial effects that can be achieved by any of the automatic fault interpretation methods provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0106] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions and improvements made within the spirit and principles of the present application should be included in the protection scope of the present application.

Claims

1. A fault automatic interpretation method, characterized in that: The method comprises: Perform prestack anisotropic inversion on the input azimuth gather to obtain fracture strength slices along the layer, wherein the fracture strength slices along the layer represent fracture density and fracture direction; Counting the histogram of the fracture strength along the layer slices, and automatically interpreting the histogram according to a preset threshold to obtain a fault attribute slice; Extracting the fracture connected area of ​​the fracture strength slice, and respectively counting the extension length of the fracture connected area and filtering the area that does not meet the area threshold to obtain the fracture connected area; The skeleton of the fracture connected area is extracted to obtain the center line of the connected area and the fault polygon.

2. The automatic fault interpretation method according to claim 1, characterized in that: The formula used for prestack anisotropy inversion is: in: R is the reflection coefficient, θ is the incident angle, For the measuring line, is the normal direction of the crack surface, R0 is the vertical incidence reflection coefficient, B iso is the AVO gradient of isotropic medium, B ani is the AVO gradient of anisotropic medium, α, β, Z, G are the longitudinal wave velocity, shear wave velocity, longitudinal wave impedance and shear modulus respectively, δ V and γ are anisotropy parameters.

3. The automatic fault interpretation method according to claim 1, characterized in that: The step of calculating the histogram of the fracture strength along the layer slices and automatically interpreting the histogram according to a preset threshold to obtain the fault attribute slices includes: Counting the histogram of the fracture strength along the layer slices to obtain a fracture strength histogram; Generate a cumulative probability curve according to the fracture strength histogram, and set the fracture strength of the cumulative probability as a preset threshold; A fault attribute matrix is ​​obtained by slicing along the layer according to the preset threshold and the fracture strength.

4. The automatic fault interpretation method according to claim 3, characterized in that: The fault attribute matrix M potential The formula for generating (i,j) is: Among them, M intensity (i,j) is the fracture strength along the layer slice, m threshold is the preset threshold.

5. The automatic fault interpretation method according to claim 1, characterized in that: A graphics algorithm is used to extract the fracture connected regions of the fault attribute slices.

6. The automatic fault interpretation method according to claim 1, characterized in that: The step of extracting the fracture connected area of ​​the fault attribute slice comprises: By marking the target pixels in the fault attribute slice, each individual connected region forms a marked block to obtain the fractured connected region.

7. The automatic fault interpretation method according to claim 1, characterized in that: The step of performing skeleton extraction on the fracture connected region to obtain the center line of the connected region and obtain the fault polygon comprises: The fracture connected area is thinned to a width of one pixel, and the center line of the fault is extracted to obtain the fault polygon.

8. A fault automatic interpretation device, characterized in that: The device comprises: An inversion module is used to perform pre-stack anisotropic inversion on the input azimuth gather to obtain fracture strength slices along the layer, wherein the fracture strength slices along the layer represent fracture density and fracture direction; A statistical module, used for statistically analyzing the histogram of the fracture strength along the layer slices, and automatically interpreting the histogram according to a preset threshold to obtain a fault attribute slice; A fracture region extraction module is used to extract the fracture connected region of the fracture strength slice, and respectively count the extension length of the fracture connected region and filter the region that does not meet the area threshold to obtain the fracture connected region; The fault centerline extraction module is used to perform skeleton extraction on the fracture connected area to obtain the centerline of the connected area and obtain the fault polygon.

9. A computer device, characterized in that: The computer device comprises a processor and a memory, wherein a computer program is stored in the memory, and the computer program is loaded and executed by the processor to implement the automatic fault interpretation method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, which is loaded and executed by a processor to implement the automatic fault interpretation method according to any one of claims 1 to 7.

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