Strike-slip fracture identification method and device based on multiple seismic attribute fusion technology

Abstract

The invention relates to the technical field of oil-gas exploration, and discloses a strike-slip fracture identification method and device based on a multi-seismic attribute fusion technology, and the method comprises the steps: firstly obtaining the seismic data and geological background data of a target region, and then carrying out the recognition of a strike-slip fracture based on the geological background and seismic data; seismic section interpretation is carried out, coherence, curvature, tensor thickness, symmetry illuminance attributes and maximum likelihood attributes are calculated, and finally, according to the fracture scale, optimal attributes are determined and quantitative fusion is carried out to identify the strike-slip fault zone. According to the method, for fractures of different scales, different attributes are preferably selected for quantitative fusion, the advantage complementation effect between different features is achieved, the fracture recognition precision and sensitivity are improved, and researchers are effectively assisted in research work in the aspects of fracture and well location.

Description

Technical Field

[0001] The present invention relates to the technical field of oil and gas field development, and in particular to a strike-slip fault identification method and device based on multiple seismic attribute fusion technology. Background Art

[0002] Faults are a very important element in the evaluation of seismic exploration traps. Early exploration of oil fields was mainly based on structural traps, and faults in structural traps play a vital role. Faults can serve as channels for oil and gas migration, and short-distance and long-distance migration may exist horizontally and vertically. This type of fault is called "oil source fault" or "oil control fault"; faults can also achieve oil and gas blocking, especially the reverse fault. Due to the existence of the fault, the target reservoir layer just docks with the dense mudstone; or a fault nose structure or a fault block structure is formed.

[0003] Faults are important research objects in the field of structural geology. According to the relative movement of the two plates of the fault, they can be divided into normal faults, reverse faults and strike-slip faults. With the fault plane as the boundary, it can be divided into upper and lower (left and right) plates. There is relative movement between the two plates of the fault. Usually, the plate with strong activity (large slip) is the active plate, and the other plate is the passive plate. In the study of normal and reverse faults, the identification of active and passive plates based on earthquakes, field outcrops and other means is more common, but there is no systematic analysis and research on the identification of active and passive plates of strike-slip faults.

[0004] However, the fault conditions in the formation are often complicated. For example, the same formation may contain other types of fault zones besides strike-slip fault zones, such as tensional fault zones. The above-mentioned different types of fault zones have different formation matrices and different effects on oil and gas reservoirs, but their morphological characteristics are similar, which can easily interfere with the identification of strike-slip fault zones. There are often technical problems such as large errors and poor accuracy in identifying strike-slip fault zones.

[0005] The invention patent with publication number CN111796323A discloses a method and system for identifying the boundary and main section of a strike-slip fault, which determines the boundary of the strike-slip fault zone and the main section of the strike-slip fault by calculating three attributes of the gradient structure tensor, coherence and amplitude change rate at the marker layer. The above prior art involves the calculation of seismic attributes such as gradient structure tensor and coherence, but does not comprehensively consider the characterization characteristics of different seismic attributes. Therefore, the error is large when identifying strike-slip faults, and faults of different scales cannot be well identified. Summary of the invention

[0006] In order to solve the problems and shortcomings existing in the above-mentioned prior art, the present invention proposes a strike-slip fault identification method and device based on multiple seismic attribute fusion technology. This method targets faults of different scales and preferably performs quantitative fusion of different attributes to achieve the complementary advantages between different features, thereby improving the recognition accuracy and sensitivity of faults and effectively assisting researchers in conducting research on faults and well locations.

[0007] In order to achieve the above-mentioned object of the invention, the technical solution of the present invention is as follows:

[0008] A strike-slip fault identification method based on multiple seismic attribute fusion technology mainly includes the following steps:

[0009] Obtain seismic data and geological background information of the target area;

[0010] Based on the geological background and seismic data, interpret the seismic profile and calculate seismic attributes such as coherence attributes, curvature attributes, tensor thickness attributes, symmetry illumination attributes and maximum likelihood attributes;

[0011] According to the scale of the fault, the preferred seismic attributes are determined and quantitatively fused to identify the strike-slip fault zone.

[0012] The method of determining the preferred attributes and performing quantitative fusion to identify the strike-slip fault zone includes: normalizing the selected seismic attributes, then performing quantitative fusion calculation according to weighted calculations of different proportions to establish a fusion body, and identifying the strike-slip fault zone based on the fault characteristics of the geological body in the fusion body.

[0013] Preferably, the coherent attribute calculation method includes:

[0014] According to the seismic data, the sampling point distribution map in the target area is obtained, and the maximum coherence value of each sampling point is calculated;

[0015] According to the maximum coherence value of each sampling point, the coherence property map of the area is obtained.

[0016] Preferably, calculating the maximum coherence value of each sampling point comprises:

[0017] A sampling point coordinate system and a diamond boundary map are set for the sampling point, wherein the sampling point serves as the origin of the sampling point coordinate system and the intersection of the major and minor axes of the diamond boundary map, the major axis of the diamond boundary map coincides with the X axis of the sampling point coordinate system, and the minor axis of the diamond boundary map coincides with the Y axis of the sampling point coordinate system;

[0018] Taking the sampling point as the rotation center, the diamond boundary map is rotated to obtain the valid points in the diamond boundary map;

[0019] A time window is set, and the coherence value corresponding to each rotation angle is calculated according to the data in the time window of the valid point in the diamond boundary diagram, so as to determine the maximum coherence value of the sampling point.

[0020] Preferably, the curvature attributes include minimum negative curvature, maximum positive curvature, maximum curvature, minimum curvature, Gaussian curvature and average curvature, and the calculation method of the curvature attributes includes:

[0021] Extract seismic attributes along the layers;

[0022] According to the extracted seismic attributes along the layers, the second-order derivative of the seismic attributes is calculated;

[0023] Based on the second-order derivatives of the seismic attributes, the curvature factor is calculated;

[0024] Depending on the curvature factor, different curvature properties are calculated.

[0025] Based on the same inventive concept, the present invention also discloses a strike-slip fault identification device based on multiple seismic attribute fusion technology, the device includes a data acquisition module, a data processing module and a strike-slip fault identification module; wherein,

[0026] Data acquisition module, used to obtain seismic data and geological background information of the target area;

[0027] Data processing module for interpreting seismic profiles and calculating coherence, curvature, tensor thickness and symmetry illumination properties based on geological background and seismic data;

[0028] The strike-slip fault identification module is used to determine the preferred attributes according to the scale of the fault and perform quantitative fusion to identify the strike-slip fault zone.

[0029] A computer device comprises a memory, a processor and a computer program stored in the memory and executable in the processor. When the processor executes the computer program, the steps of the above-mentioned strike-slip fault identification method based on the fusion technology of multiple seismic attributes are implemented.

[0030] A computer-readable storage medium stores a computer program, which, when executed in a computer processor, implements the steps of the above-mentioned strike-slip fault identification method based on multiple seismic attribute fusion technology.

[0031] Beneficial effects of the present invention:

[0032] 1. The present invention identifies strike-slip faults based on a fusion technology of multiple seismic attributes. Taking into account the different characteristics of different types of coherence bodies in characterizing the characteristics of different fault zones, as well as the mutual relationship between karst characteristics and strike-slip fault zones, a fusion body is established by acquiring multiple attributes such as coherence, curvature, tensor thickness, and symmetry illumination, and then the above attributes are integrated to identify the strike-slip fault zone. The fault characteristics of the geological body in the fusion body are then used to identify the strike-slip fault zone, thereby solving the technical problems of large errors and poor accuracy in identifying the strike-slip fault zone in the existing methods, and achieving the technical effect of being able to integrate the characterization characteristics of different seismic attributes, effectively distinguish tensile fault zones, and accurately identify the strike-slip fault zone.

[0033] 2. The present invention performs seismic attribute analysis on the seismic data body, then extracts the seismic attribute body along the layer of the target layer through the seismic layer data, and finally performs curvature analysis on the seismic attribute body along the layer through the newly developed curvature analysis technology to obtain the seismic curvature body along the layer. Through the seismic curvature body along the layer, this technology can finely characterize the morphology of faults, cracks, and river channels, as well as the effectiveness of reservoirs, thereby making up for the lack of accuracy of conventional methods in identifying faults and cracks, assisting researchers in working on faults and cracks, and can effectively calculate seismic attributes, with better fault directionality recognition capabilities. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The foregoing and following detailed description of the present invention will become more apparent when read in conjunction with the following drawings, in which:

[0035] Figure 1 is a flow chart of the method of the present invention;

[0036] Figure 2 It is a structural diagram of the device of the present invention;

[0037] Figure 3 This is a schematic diagram of the hierarchical sequence fracture identification of the present invention;

[0038] Figure 4 Schematic diagram of the maximum likelihood attribute of the present invention;

[0039] Figure 5 It is a schematic diagram of the coherent properties of the present invention;

[0040] Figure 6 It is a schematic diagram of the symmetrical lighting properties of the present invention;

[0041] Figure 7 It is a schematic diagram of curvature properties of the present invention;

[0042] Figure 8 This is a schematic diagram of the principal component fusion attributes of the present invention;

[0043] Fig. 9 It is a schematic diagram of CMY fusion properties of the present invention. DETAILED DESCRIPTION

[0044] In order to enable those skilled in the art to better understand the technical solutions in the present invention, the technical solutions for achieving the purpose of the present invention will be further described below through specific embodiments. It should be noted that the technical solutions claimed for protection in the present invention include but are not limited to the following embodiments. Based on the embodiments in the present invention, all other embodiments obtained by those skilled in the art without creative work shall fall within the scope of protection of the present invention.

[0045] Faults are important research objects in the field of structural geology. According to the relative movement of the two plates of the fault, they can be divided into normal faults, reverse faults and strike-slip faults. With the fault plane as the boundary, it can be divided into upper and lower (left and right) plates. There is relative movement between the two plates of the fault. Usually, the plate with strong activity (large slip) is the active plate, and the other plate is the passive plate. In the study of normal and reverse faults, the identification of active and passive plates based on earthquakes, field outcrops and other means is more common, but there is no systematic analysis and research on the identification of active and passive plates of strike-slip faults.

[0046] However, the fault conditions in the formation are often complicated. For example, the same formation may contain other types of fault zones besides strike-slip fault zones, such as tensional fault zones. The above-mentioned different types of fault zones have different formation matrices and different effects on oil and gas reservoirs, but their morphological characteristics are similar, which can easily interfere with the identification of strike-slip fault zones. There are often technical problems such as large errors and poor accuracy in identifying strike-slip fault zones.

[0047] At present, although some existing fault identification methods involve the calculation of tensor, coherence and other seismic attributes, these attributes are used separately when identifying faults, and the process of attribute fusion is not considered. Therefore, existing identification methods usually have problems such as large identification errors and poor accuracy.

[0048] Based on this, an embodiment of the present invention proposes a method and device for identifying strike-slip faults based on a fusion technology of multiple seismic attributes. The method acquires multiple seismic attributes such as coherence, curvature, tensor thickness, and symmetry illumination, and establishes a fusion body by integrating the above seismic attributes; then, the fracture characteristics of the geological body in the fusion body are used to identify the strike-slip fault zone, thereby achieving the technical effect of integrating the characterization characteristics of different seismic attributes, effectively distinguishing tensile fault zones, and accurately identifying strike-slip fault zones.

[0049] In order to facilitate the understanding of the technical solution of the present invention, the present invention first introduces and illustrates a method for identifying strike-slip faults based on a fusion technology of multiple seismic attributes.

[0050] This embodiment discloses a method for identifying strike-slip faults based on multiple seismic attribute fusion technology. Figure 1 , this method mainly includes the following steps.

[0051] Step S1. Obtain seismic data and geological background information of the target area.

[0052] Step S2. Based on the geological background and seismic data, interpret the seismic profile and calculate various seismic attributes such as coherence, curvature, tensor thickness, symmetry illumination, etc.

[0053] In this embodiment, the method for calculating the coherence attribute includes the steps of:

[0054] Step 1: Based on the seismic data, obtain the sampling point distribution map within the template area;

[0055] Step 2: Repeat the following sub-steps 1-3 for each sampling point in the sampling point distribution map:

[0056] Sub-step 1: setting a sampling point coordinate system and a diamond boundary map for the sampling point, wherein the sampling point is used as the origin of the sampling point coordinate system and the intersection of the major and minor axes of the diamond boundary map, the major axis of the diamond boundary map coincides with the X axis of the sampling point coordinate system, and the minor axis of the diamond boundary map coincides with the Y axis of the sampling point coordinate system;

[0057] Sub-step 2: Rotate the diamond boundary map with the sampling point as the rotation center to obtain valid points in the diamond boundary map;

[0058] Sub-step 3: Set a time window, calculate the coherence value corresponding to each rotation angle according to the data in the time window of the valid point in the diamond boundary graph, and then determine the maximum coherence value of the sampling point;

[0059] Step 3: Obtain the coherence attribute map of the target area based on the maximum coherence value of each sampling point.

[0060] Specifically, the calculation formula of the coherence value is as follows:

[0061]

[0062] Where C3 is the coherence value, C is a seismic data volume consisting of J channels and N sample points in each channel, DN*J is the covariance matrix, where DN*J is the seismic subvolume consisting of J channels and N sample points participating in the calculation, which is the transpose of DN*J, and T r (C) is the trace of the matrix, representing the energy of the covariance matrix, λ1 is the largest eigenvalue, representing the dominant energy, C jj are the elements on the diagonal of the matrix, λ j is the non-negative eigenvalue of the matrix, J is the number of seismic channels involved in the calculation, and j is the serial number of the seismic channels involved in the calculation.

[0063] In this embodiment, the relevant attribute diagram is shown in the attached Figure 5 .

[0064] In this embodiment, the curvature attribute analysis method includes the following steps:

[0065] Step 1: Extract seismic attributes along the layers;

[0066] Step 2: According to the extracted layer-by-layer seismic attributes, the second-order derivative of the seismic attributes is calculated. The specific calculation process of the second-order derivative of the seismic attributes is as follows:

[0067] [Ix,Iy]=Gradient(seis_attr,resolution)

[0068] Where: Gradient represents the first-order derivative, seis_attr represents the seismic attribute volume, resolution represents the resolution of the derivative, Ix and Iy represent the first-order derivative in the x and y directions respectively;

[0069] [Ixx,Ixy]=Gradient(Ix,resolution)

[0070] [Iyx,Iyy]=Gradient(Iy,resolution)

[0071] Where: Ixx represents the second-order derivative in the x direction, Ixy represents the second-order derivative in the x and y directions, Iyx represents the second-order derivative in the y and x directions, and Iyy represents the second-order derivative in the y direction;

[0072] Step 3: Calculate the curvature factor according to the second-order derivative of the seismic attribute. The calculation expression of the curvature factor is as follows:

[0073]

[0074] Among them, a, b, c, d, and e represent different curvature factors;

[0075] Step 4: According to the curvature factor, different curvature attributes are calculated. The curvature attributes include: minimum negative curvature, maximum positive curvature, maximum curvature, minimum curvature, Gaussian curvature and mean curvature. When identifying strike-slip faults, 1-2 of these curvature attributes are usually selected for identification; among them,

[0076] The calculation expression of the minimum negative curvature is:

[0077] The calculation expression of the maximum positive curvature is:

[0078] The calculation expression of the maximum curvature is:

[0079] The calculation expression of the minimum curvature is:

[0080] The calculation expression of the Gaussian curvature is:

[0081] The calculation expression of the mean curvature is:

[0082] In this embodiment, the maximum likelihood attribute, the coherence attribute, the symmetrical illumination attribute and the curvature attribute schematic diagram refer to the attached Figure 4-Figure 7 .

[0083] Step S3. Determine the preferred seismic attributes according to the scale of the fault, and then quantitatively fuse the selected seismic attributes to identify the strike-slip fault zone.

[0084] In the present invention, it should be noted that the scale of the fault is divided according to the accuracy of seismic data identification. The obvious displacement of the seismic event axis is the main fault, the slight displacement-deflection is the secondary fault, and the weak amplitude change-deflection is the microcrack.

[0085] The fracture geometry can be described by the following parameters:

[0086] Based on the seismic profile interpretation results, the fault growth index, fault drop and fault activity rate are obtained. Based on the fault growth index, fault drop and fault activity rate, the fault stage differential activity is determined. The fault growth index calculation expression is as follows:

[0087] GI = H1 / H2;

[0088] Where GI is the fault growth index, H1 is the hanging wall thickness, and H2 is the footwall thickness;

[0089] The calculation expression of the fault activity rate is as follows:

[0090] VF=D / T;

[0091] Among them, VF is the fault activity rate, D is the fault drop, and T is the deposition time;

[0092] The fault drop is obtained by manual measurement.

[0093] For the main fault, it is mainly manifested as the misalignment of the seismic wave reflection phase axis. This kind of fault can be clearly displayed by using curvature attributes or coherence attributes; for the secondary fault, the method of fusing coherence attributes with curvature attributes can be used for analysis, but the final fault results still need to be verified through profiles, and the seismic noise illusion can be eliminated by combining flat profiles; for smaller faults, some seismic attributes that have stronger response to micro-fractures should be used, such as maximum likelihood attributes, symmetrical illumination attributes, AFE, etc. The identification results of small faults are usually verified using drilling data.

[0094] Therefore, usually, the coherence or curvature attribute or the fusion of these two attributes can only identify large-scale fractures, but it is difficult to identify small-scale and microcracks. Therefore, the maximum likelihood attribute and the symmetric illumination attribute are needed to jointly identify them.

[0095] In the present invention, after selecting the corresponding attributes according to the scale of the fault, the selected seismic attributes are normalized, and then quantitative fusion is calculated according to different weighted proportions to establish a fusion body. According to the fault characteristics of the geological body in the fusion body, the strike-slip fault zone is finally identified. The fusion method can be principal component fusion and CMY fusion, etc. For details, please refer to the attached manual. Figure 8 and attached Fig. 9 .

[0096] Among them, principal component fusion mainly uses the linear projection method to project the data into a new coordinate space, so that the new components are distributed according to the amount of information. The first principal component contains the largest amount of information. After the transformation, the principal component components are independent of each other, and the amount of information contained in the component decreases as the principal component number increases. The first three largest components are selected for fusion.

[0097] CMY fusion is similar to RGB. The three primary colors of an image can be divided into red, green, and blue. There is also a CMY expression method, which uses the image color fusion method to perform attribute fusion.

[0098] When attributes are fused, the degree of participation of different attributes in the attribute fusion process (attribute ratio) is obtained through a large number of attribute analysis tests. Figure 3 ,For the case of the main fault, 30%-40% of the curvature attributes and 60%-70% of the coherence attributes can be taken to establish the fusion body, and then the fault characteristics of the geological body in the fusion body can be finally identified the strike-slip fault zone.

[0099] For secondary faults, the strike-slip fault zone can be identified by taking 63% curvature-coherence fusion and 37% maximum likelihood attribute fusion.

[0100] For the fracture development zone, the strike-slip fault zone can be identified by fusing the 42% maximum likelihood attribute and the 58% symmetry lighting attribute.

[0101] Further, based on the same inventive concept, an embodiment of the present invention also provides a strike-slip fault identification device based on multiple seismic attribute fusion technology, and the device is used to implement the strike-slip fault identification method described above, as described in the following embodiment. As used below, the term "unit" or "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable. Refer to the attached manual for details. Figure 2 Specifically, the device may include: a data acquisition module 201, a data processing module 202 and a strike-slip fault identification module 203. The structure is described in detail below.

[0102] The data acquisition module 201 is used to obtain seismic data and geological background information of the target area;

[0103] The data processing module 202 is used to interpret the seismic profile and calculate the coherence, curvature, tensor thickness and symmetry illumination attributes based on the geological background and seismic data;

[0104] The strike-slip fault identification module 203 is used to determine the preferred attributes according to the scale of the fault and to identify the strike-slip fault zone by quantitative fusion.

[0105] It should be noted that the systems, devices, models or units described in the above embodiments can be implemented by computer chips or entities, or by products with certain functions. For the convenience of description, in this specification, the above devices are described in various units according to their functions. Of course, when implementing the present invention, the functions of each unit can be implemented in the same or multiple software and / or hardware.

[0106] Furthermore, in the present specification, adjectives such as first and second may be used merely to distinguish one element or action from another, without necessarily or implying any actual such relationship or order.

[0107] Furthermore, an embodiment of the present invention also provides a computer device, which includes a memory, a processor, and a computer program stored in the memory and executable in the processor, and when the processor executes the computer program, the steps of any of the above methods are implemented.

[0108] Furthermore, an embodiment of the present invention also provides a computer-readable storage medium, which stores a computer program. When the computer program is executed in a computer processor, the steps of any of the above methods are implemented.

[0109] The above description is only a preferred embodiment of the present invention and does not constitute any form of hindrance to the present invention. Any simple modification or equivalent changes made to the above embodiments based on the technical essence of the present invention shall fall within the protection scope of the present invention.

Claims

1. A strike-slip fault identification method based on multiple seismic attribute fusion technology, characterized in that: The following steps are involved: Obtain seismic data and geological background information of the target area; Based on the geological background and seismic data, interpret the seismic profile and calculate the coherence attributes, curvature attributes, tensor thickness attributes, symmetry illumination attributes and maximum likelihood attributes; According to the scale of the fault, the preferred attributes are determined and quantitatively fused to identify the strike-slip fault zone.

2. The strike-slip fault identification method based on multiple seismic attribute fusion technology according to claim 1 is characterized in that: The method of determining the preferred attributes and performing quantitative fusion to identify the strike-slip fault zone includes: normalizing the selected seismic attributes, then performing quantitative fusion calculation according to weighted calculations of different proportions to establish a fusion body, and identifying the strike-slip fault zone based on the fault characteristics of the geological body in the fusion body.

3. The strike-slip fault identification method based on multiple seismic attribute fusion technology according to claim 1 is characterized in that: The coherent attribute calculation method comprises: According to the seismic data, the sampling point distribution map in the target area is obtained, and the maximum coherence value of each sampling point is calculated; According to the maximum coherence value of each sampling point, the coherence property map of the area is obtained.

4. The strike-slip fault identification method based on multiple seismic attribute fusion technology according to claim 3 is characterized in that: Calculating the maximum coherence value of each sampling point includes: A sampling point coordinate system and a diamond boundary map are set for the sampling point, wherein the sampling point serves as the origin of the sampling point coordinate system and the intersection of the major and minor axes of the diamond boundary map, the major axis of the diamond boundary map coincides with the X axis of the sampling point coordinate system, and the minor axis of the diamond boundary map coincides with the Y axis of the sampling point coordinate system; Taking the sampling point as the rotation center, the diamond boundary map is rotated to obtain the valid points in the diamond boundary map; A time window is set, and the coherence value corresponding to each rotation angle is calculated according to the data in the time window of the valid point in the diamond boundary diagram, so as to determine the maximum coherence value of the sampling point.

5. The strike-slip fault identification method based on multiple seismic attribute fusion technology according to claim 1 is characterized in that: The calculation method of the curvature attribute includes: Extract seismic attributes along the layers; According to the extracted seismic attributes along the layers, the second-order derivative of the seismic attributes is calculated; Based on the second-order derivatives of the seismic attributes, the curvature factor is calculated; Depending on the curvature factor, different curvature properties are calculated.

6. The strike-slip fault identification method based on multiple seismic attribute fusion technology according to claim 1 or 5, characterized in that: The curvature attributes include: minimum negative curvature, maximum positive curvature, maximum curvature, minimum curvature, Gaussian curvature and mean curvature.

7. A strike-slip fault identification device based on multiple seismic attribute fusion technology, characterized in that: The device is used to implement the strike-slip fault identification method according to any one of claims 1 to 6, comprising: Data acquisition module, used to obtain seismic data and geological background information of the target area; Data processing module for interpreting seismic profiles and calculating coherence, curvature, tensor thickness and symmetry illumination properties based on geological background and seismic data; The strike-slip fault identification module is used to determine the preferred attributes according to the scale of the fault and perform quantitative fusion to identify the strike-slip fault zone.

8. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable in the processor, characterized in that: When the processor executes the computer program, the method steps described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed in a computer processor, the method according to any one of claims 1 to 6 is implemented.

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