Method and device for determining fault fracture zone

Abstract

The invention provides a fault fracture zone determination method and device, and the method comprises the steps: obtaining three-dimensional seismic data of a target stratum, and determining fault detection data from the three-dimensional seismic data; calculating a covariance matrix for local seismic sub-bodies in the fault detection data, and representing the fault detection data through a gray level image; detecting a first boundary surface and a second boundary surface of the fault fracture zone from the grayscale image through an edge detection operator in image processing; enhancing the first boundary surface and the second boundary surface; and determining a range limited by the enhanced first boundary surface and the enhanced second boundary surface as a fault fracture zone, and determining the distance between the first boundary surface and the second boundary surface as the width of the fault fracture zone. According to the scheme, the technical problem that the data accuracy is not high due to the fact that only the fault plane is researched and the fault fracture zone is not considered in the prior art is solved, and the technical effect of effectively improving the stratum description accuracy is achieved.

Description

Technical Field

[0001] The present application belongs to the field of geological exploration technology, and in particular, relates to a method and device for determining a fault fracture zone. Background Art

[0002] In three-dimensional seismic exploration, fault detection and characterization are important contents of seismic data interpretation. Through fault detection and characterization, more detailed research can be conducted on the structural development characteristics and reservoir control of the study area. Since faults of different scales and levels play different roles in geological evolution and oil and gas migration and accumulation, especially under the combined action of extension and strike-slip, fault development will form a certain scale of fault fracture zone, which is usually accompanied by the dissolution of surface water and underground hydrothermal fluid along the fracture zone. The characteristics of the fault fracture zone itself affect the performance of the oil and gas migration channel, or can be directly used as an oil and gas storage space. In the interpretation of faults in three-dimensional seismic data, fault detection is generally performed through coherence body, variance body, curvature body, ant tracking, edge detection, deep learning fracture detection and other methods.

[0003] However, in different lithology and different types of faults, the lateral width of the fault fracture zone is generally not large, at a few meters or even below the meter level. The discontinuity characteristics reflected in the seismic data span one to several seismic traces horizontally. When using technologies such as seismic coherence volume, ant volume, and deep learning fracture detection, the width of the fracture zone is ignored. Instead, it is directly approximated as a fault plane, ignoring the influence of the width of the fracture zone.

[0004] There is currently no effective solution for how to accurately determine and identify fault fracture zones. Summary of the invention

[0005] The purpose of the present application is to provide a method and device for determining a fault fracture zone, which can realize accurate identification of the fault fracture zone, so as to make a more accurate judgment on dissolution and oil and gas migration and accumulation.

[0006] The present application provides a method and device for determining a fault fracture zone, which is implemented as follows:

[0007] A method for determining a fault fracture zone, the method comprising:

[0008] Acquire three-dimensional seismic data of a target stratum, and determine fault detection data from the three-dimensional seismic data;

[0009] Calculating a covariance matrix for a local seismic subvolume in the fault detection data, and representing the fault detection data by a grayscale image;

[0010] Detecting a first boundary surface and a second boundary surface of the fault fracture zone from the grayscale image by using an edge detection operator in image processing;

[0011] Performing enhancement processing on the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix;

[0012] The range defined by the enhanced first boundary surface and the second boundary surface is determined as the fault fracture zone, and the distance between the first boundary surface and the second boundary surface is determined as the width of the fault fracture zone.

[0013] In one embodiment, the first boundary surface and the second boundary surface are enhanced by two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix, including:

[0014] Smoothing the image in the direction parallel to the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix;

[0015] The image in the direction perpendicular to the first boundary surface and the second boundary surface is sharpened by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix.

[0016] In one embodiment, smoothing the image in a direction parallel to the first boundary surface and the second boundary surface includes:

[0017] Low-pass filtering is performed according to the following formula to smooth the image in the direction parallel to the first boundary surface and the second boundary surface:

[0018]

[0019] Where i = s1, s2, s1 represents the first boundary surface, s2 represents the second boundary surface, G i represents the Gaussian filter, ε1 and ε2 represent two orthogonal eigenvectors in the covariance matrix parallel to the cross-section direction, ε3 represents an eigenvector in the covariance matrix perpendicular to the cross-section direction, σ i1 , σ i2 , σ i3 represents the Gaussian operator standard deviation, where

[0020] Performing sharpening processing on the image in the direction perpendicular to the first boundary surface and the second boundary surface, including: calculating the second-order partial derivative of the image in the direction perpendicular to the first boundary surface and the second boundary surface according to the following operator to perform sharpening processing:

[0021]

[0022] Among them, LoG i represents the Laplace operator.

[0023] In one embodiment, detecting a first boundary surface and a second boundary surface of a fault fracture zone from the grayscale image by using an edge detection operator in image processing includes:

[0024] Performing denoising on the grayscale image by Gaussian filtering;

[0025] After denoising is completed, determining the gradient of the grayscale image;

[0026] Filtering out non-edge pixels in the grayscale image to make the blurred boundary clearer, and retaining the maximum value of the gradient intensity at each pixel during the filtering process;

[0027] The possible boundaries are determined by a double threshold approach;

[0028] Possible boundaries are tracked, and weak boundaries connected to strong boundaries in pixel positions are determined as boundary pixel points, so as to detect the first boundary surface and the second boundary surface of the fault fracture zone from the grayscale image.

[0029] In one embodiment, after determining the range defined by the enhanced first boundary surface and the second boundary surface as the fault fracture zone and determining the distance between the first boundary surface and the second boundary surface as the width of the fault fracture zone, the method further includes:

[0030] Determining whether the extension characteristics of the fault fracture zone meet preset quality indicators;

[0031] When it is determined that the preset quality index is met, a fault polygon is formed according to the determined fault fracture zone and the determined width of the fault fracture zone;

[0032] Based on the formed fault polygons, oil and gas migration and accumulation channels or fault-controlled dissolution reservoirs are generated.

[0033] A device for determining a fault fracture zone, comprising:

[0034] An acquisition module, used for acquiring three-dimensional seismic data of a target stratum, and determining fault detection data from the three-dimensional seismic data;

[0035] A calculation module, used for calculating a covariance matrix for a local seismic subvolume in the fault detection data, and representing the fault detection data through a grayscale image;

[0036] A detection module, used for detecting a first boundary surface and a second boundary surface of the fault fracture zone from the grayscale image by using an edge detection operator in image processing;

[0037] An enhancement module, used for enhancing the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix;

[0038] The determination module is used to determine the range defined by the first boundary surface and the second boundary surface after the enhancement process as the fault fracture zone, and determine the distance between the first boundary surface and the second boundary surface as the width of the fault fracture zone.

[0039] In one embodiment, the enhancement module includes:

[0040] A smoothing unit, used for smoothing the image in the direction parallel to the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix;

[0041] The sharpening unit is used to sharpen the image in the direction perpendicular to the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix.

[0042] In one embodiment, the device for determining the fault fracture zone further comprises:

[0043] A drawing module, for forming a fault polygon according to the determined fault shattering zone and the determined width of the fault shattering zone after determining the range defined by the enhanced first boundary surface and the second boundary surface as the fault shattering zone and determining the distance between the first boundary surface and the second boundary surface as the width of the fault shattering zone;

[0044] The generation module is used to generate oil and gas migration and accumulation channels or fault-controlled dissolution reservoirs based on the formed fault polygons.

[0045] An electronic device comprises a processor and a memory for storing instructions executable by the processor, wherein the steps of the above method are implemented when the processor executes the instructions.

[0046] A computer-readable storage medium stores a computer program / instruction, which implements the steps of the above method when executed by a processor.

[0047] The method and device for determining the fault fracture zone provided in the present application use edge detection methods to track the boundary of the fracture zone according to the width characteristics of the fault fracture zone, use the two boundary surfaces corresponding to the upper and lower plates of the fault to characterize the fault and fracture zone response, and carry out enhancement processing on the two boundary surfaces of the fault fracture zone to make the result more refined, and change from the conventional research only on the fault surface to the characterization of the fault fracture zone body, which can effectively improve the accuracy of the research on oil and gas migration and accumulation channels or fault-controlled reservoirs. The above scheme solves the technical problem of low data accuracy caused by the existing research only on the fault surface without considering the fault fracture zone, and achieves the technical effect of effectively improving the accuracy of stratigraphic characterization. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0049] Figure 1 This is a method flow chart of an embodiment of a method for determining a fault fracture zone provided by the present application;

[0050] Figure 2 It is a method flow chart of the section enhancement technology for protecting the width of the fault fracture zone provided by the present application;

[0051] Figure 3 It is a schematic diagram of the fracture zone boundary surfaces S1, S2 and the simplified cross section S provided in this application;

[0052] Figure 4 It is an enhanced cross-sectional rendering of direct cross-sectional detection provided by the present application;

[0053] Figure 5 It is a cross-sectional enhancement effect diagram of the width of the protection fault fracture zone provided by the present application;

[0054] Figure 6 It is a hardware structure block diagram of an electronic device for a method for determining a fault fracture zone provided by the present application;

[0055] Figure 7 It is a schematic diagram of the module structure of an embodiment of a device for determining a fault fracture zone provided in the present application. DETAILED DESCRIPTION

[0056] In order to enable those skilled in the art to better understand the technical solutions in this application, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the drawings in the embodiments of this application. Obviously, the described embodiments are only part of the embodiments of this application, not all of them. Based on the embodiments in this application, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this application.

[0057] For the interpretation of faults in three-dimensional seismic data, faults are currently mainly detected through coherence bodies, variance bodies, curvature bodies, ant tracking, edge detection, deep learning fracture detection and other methods. However, there are few characterizations of fault fracture zones. In this case, based on the production needs of fault-controlled reservoirs, on the basis of fault data detected by conventional seismic coherence bodies and other technologies, the edge detection method is further used to track the boundary of the fracture zone according to the width characteristics of the fault fracture zone, and the two boundary surfaces corresponding to the upper and lower plates of the fault are used to characterize the fault and fracture zone response. At the same time, the two boundary surfaces of the fault fracture zone are enhanced to make the results more refined, and the conventional research only on the fault surface is transformed into the characterization of the fault fracture zone body, so that a more detailed study of oil and gas migration and accumulation channels or fault-controlled reservoirs can be carried out.

[0058] Figure 1 It is a method flow chart of an embodiment of the method for determining the fault fracture zone provided by the present application. Although the present application provides method operation steps or device structures as shown in the following embodiments or drawings, more or fewer operation steps or module units may be included in the method or device based on routine or without creative labor. In the steps or structures where there is no necessary causal relationship logically, the execution order of these steps or the module structure of the device is not limited to the execution order or module structure described in the embodiments of the present application and shown in the drawings. When the method or module structure is applied to an actual device or terminal product, it can be connected according to the method or module structure shown in the embodiments or drawings for sequential execution or parallel execution (for example, a parallel processor or a multi-threaded processing environment, or even a distributed processing environment).

[0059] Specifically, Figure 1 As shown, the above-mentioned method for determining the fault fracture zone may include the following steps:

[0060] Step 101: Acquire three-dimensional seismic data of a target stratum, and determine fault detection data from the three-dimensional seismic data;

[0061] Step 102: Calculate the covariance matrix of the local seismic subvolume in the fault detection data, and characterize the fault detection data by a grayscale image;

[0062] For example, based on three-dimensional seismic data, the coherence volume and other algorithms can be used to calculate the fault detection data, and the covariance matrix can be calculated for the local seismic sub-volume, and the two orthogonal eigenvectors parallel to the cross section are set as ε1 and ε2, and the eigenvector perpendicular to the cross section is set as ε3. Then, the fault detection result data is used in grayscale image mode, and the edge detection operator in image processing is used to detect the two boundaries s1 and s2 of the fault fracture zone. The fault is the fracture zone defined by the two surfaces s1 and s2.

[0063] Step 103: Detecting a first boundary surface and a second boundary surface of the fault fracture zone from the grayscale image by using an edge detection operator in image processing;

[0064] There are many edge detection algorithms for images. When implementing, different edge detection algorithms can be selected according to requirements. Specifically, in this example, a method of detecting the first boundary surface and the second boundary surface of the fault fracture zone from the grayscale image by using the edge detection operator in image processing is provided, which may include the following steps:

[0065] S1: De-noising the grayscale image by Gaussian filtering;

[0066] S2: After denoising is completed, determining the gradient of the grayscale image;

[0067] S3: filtering out non-edge pixels in the grayscale image to make the blurred boundary clearer, and retaining the maximum value of the gradient intensity at each pixel during the filtering process;

[0068] S5: Determine possible boundaries through a double threshold approach;

[0069] S6: Track possible boundaries, and determine weak boundaries connected to strong boundaries in pixel positions as boundary pixel points, so as to detect a first boundary surface and a second boundary surface of the fault fracture zone from the grayscale image.

[0070] Step 104: performing enhancement processing on the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix;

[0071] Specifically, during implementation, the first boundary surface and the second boundary surface are enhanced by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix. The image in the direction parallel to the first boundary surface and the second boundary surface can be smoothed by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix; the image in the direction perpendicular to the first boundary surface and the second boundary surface can be sharpened by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix.

[0072] Specifically, the smoothing process is performed on the image in the direction parallel to the first boundary surface and the second boundary surface, and low-pass filtering may be performed according to the following formula to smooth the image in the direction parallel to the first boundary surface and the second boundary surface:

[0073]

[0074] Where i = s1, s2, s1 represents the first boundary surface, s2 represents the second boundary surface, G i represents the Gaussian filter, ε1 and ε2 represent two orthogonal eigenvectors in the covariance matrix parallel to the cross-section direction, ε3 represents an eigenvector in the covariance matrix perpendicular to the cross-section direction, σ i1 , σ i2 , σ i3 represents the Gaussian operator standard deviation, where

[0075] The image in the direction perpendicular to the first boundary surface and the second boundary surface is sharpened by calculating the second-order partial derivative of the image in the direction perpendicular to the first boundary surface and the second boundary surface according to the following operator to perform the sharpening process:

[0076]

[0077] Among them, LoG i represents the Laplace operator

[0078] Step 105: Determine the range defined by the enhanced first boundary surface and the second boundary surface as the fault fracture zone, and determine the distance between the first boundary surface and the second boundary surface as the width of the fault fracture zone.

[0079] That is, the above method can be used to enhance the fault fracture zone boundary surfaces s1 and s2, and the ranges defined by s1 and s2 are combined into a complete fault fracture zone, and the distance between the two surfaces is the width of the fault fracture zone. Since the fault fracture zone is effectively protected, the plane mapping fault characterization of the target layer can more realistically reflect the development law of the fault, and can achieve the purpose of cross-section enhancement to protect the width of the low-order fault fracture zone.

[0080] Based on this, after determining the range defined by the enhanced first boundary surface and the second boundary surface as the fault fracture zone, and determining the distance between the first boundary surface and the second boundary surface as the width of the fault fracture zone, a fault polygon can be formed according to the determined fault fracture zone and the determined width of the fault fracture zone; and an oil and gas migration and accumulation channel or a fault-controlled dissolution reservoir can be generated according to the formed fault polygon. In the prior art, fault polygons are generally generated directly after the coherent body detection section is enhanced. However, in this example, the width of the fault fracture zone is considered according to the two boundary surfaces, so that the fault polygon can be generated more accurately.

[0081] The above method is described below in conjunction with a specific embodiment. However, it should be noted that this specific embodiment is only for better illustrating the present application and does not constitute an improper limitation on the present application.

[0082] In this case, starting from the production needs of fault-controlled reservoirs, on the basis of fault data detected by conventional seismic coherence body and other technologies, edge detection methods are further used to track the boundary of the fracture zone according to the width characteristics of the fault fracture zone, and the two boundary surfaces corresponding to the upper and lower plates of the fault are used to characterize the fault and fracture zone response. At the same time, the two boundary surfaces of the fault fracture zone are enhanced to make the effect more refined, and the conventional research only on the fault surface is transformed into the characterization of the fault fracture zone body, which has a stronger guiding significance for the research on oil and gas migration and accumulation channels or fault-controlled reservoirs.

[0083] Specifically, the section reinforcement technology for protecting the width of the fault fracture zone can be as follows: Figure 2 As shown, the following steps may be included:

[0084] Step 201: Sub-3D seismic coherence volume fault detection:

[0085] Based on three-dimensional seismic data, the coherence volume and other algorithms are used to calculate the fault detection data. The covariance matrix is ​​calculated for the local seismic sub-volume, and the two orthogonal eigenvectors parallel to the cross section are set as ε1 and ε2, and the eigenvector perpendicular to the cross section is set as ε3.

[0086] Step 202: Fracture and rupture zone boundary detection:

[0087] The fault detection result data is processed in grayscale image format, and the edge detection operator in image processing is used to detect the two boundaries s1 and s2 of the fault fracture zone. The fault is the fracture zone defined by the two surfaces s1 and s2.

[0088] Step 203: Enhancement of the fracture zone boundary surface:

[0089] The fault fracture zone boundary surfaces corresponding to s1 and s2 are enhanced respectively, and the continuity is improved by smoothing and sharpening.

[0090] This is different from the existing conventional section enhancement method, which only enhances a single section. For conventional section enhancement, it is only necessary to detect the abnormal thinning of the coherent body and improve the continuity without considering the width of the broken zone. In this case, the fault broken zone boundary surface is decomposed and enhanced separately, so that the detection result can retain the fault broken zone information. Image enhancement processing is used, and image processing is performed by combining Gaussian-Laplace filtering with skeleton processing. The image is edge filtered by LoG filtering to play a role in smoothing and sharpening. Smoothing is performed in the direction parallel to the boundary surface, and sharpening is performed in the direction perpendicular to the boundary surface.

[0091] Specifically, a Gaussian filter G can be applied to perform low-pass filtering to smooth the image, and the expression is:

[0092]

[0093] Where i = s1, s2, σ i1 , σ i2 , σ i3 represents the standard deviation of the Gaussian operator, satisfying

[0094] By sharpening the Laplace operator (performing a second-order partial derivative in the vertical direction), the LoG operator can be expressed as:

[0095]

[0096] Where i = s1, s2

[0097] The LoG operator is used to realize the diffusion of the two boundary surfaces of the fracture zone and enhance the continuity.

[0098] Step 204: determine whether the fault extension characteristics meet the quality control requirements, if so, execute step 205, if not, execute step 203;

[0099] Step 205: Fault plane mapping:

[0100] After the fault fracture zone boundary surfaces s1 and s2 are enhanced, the ranges defined by s1 and s2 are combined into a complete fault fracture zone, and the distance between the two surfaces is the width of the fault fracture zone. Since the fault fracture zone is protected, the plane mapping fault characterization of the target layer can truly reflect the fault development law.

[0101] like Figure 3 As shown in the figure, it is a schematic diagram of the fault fracture zone, where s1 and s2 represent the boundary surfaces of the fault fracture zone, and s represents the simplified section. Figure 4 The following is a schematic diagram of the stratigraphic enhancement process directly targeting the cross section. Figure 5 Shown is a schematic diagram of the enhanced stratigraphic treatment to protect the width of the fault fracture zone.

[0102] That is, through sub-3D seismic coherence volume fault detection, fracture and rupture zone boundary surface detection, fracture and rupture zone boundary surface enhancement processing, fault plane formation Figure 4 The section enhancement of protecting the width of the low-order fault shattering zone is realized in three steps. Specifically, on the coherent volume data, the edge detection operator in image processing is applied to detect the two boundary surfaces of the fault shattering zone, and the Gaussian-Laplace filter is applied to smooth and sharpen the two boundary surfaces to achieve enhancement processing, replacing the conventional simplified method of only enhancing the fault surface, thereby playing a role in protecting the fault shattering zone. The section enhancement technology of protecting the width of the fault shattering zone improves the precision of fault characterization, transforming from the conventional simplified method of targeting the fault surface to the characterization of the fault shattering zone body, considering the width parameter of the fault shattering zone, and providing more accurate characterization results for faults formed by composite stresses such as extension and strike-slip, providing strong technical support for the study of oil and gas migration and accumulation channels or fault-controlled dissolution reservoirs. In terms of characterization accuracy, the existing methods generally detect low-order faults and enhance them through a single section, pursuing the regularity of the spatial extension of the fault section, and not considering the development of the fault shattering zone. In this case, the width characteristics of the fault shattering zone development are considered, and the fault shattering zone with a lateral width greater than 10 meters can be detected. Furthermore, when mapping fault polygons, the existing method generally generates fault polygons directly after enhancing the coherent body detection section. In this case, the width of the fault fracture zone is considered based on the two boundary surfaces, so that the fault polygons can be generated more accurately. This can provide favorable support for the study of the role of oil and gas migration and accumulation channels of faults formed by composite stresses such as extension and strike-slip, fault sealing, fault-controlled dissolution reservoirs, etc., so as to carry out more refined oil and gas exploration and development.

[0103] The method embodiments provided in the above embodiments of the present application can be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on an electronic device as an example, Figure 6 This is a hardware structure block diagram of an electronic device for a method for determining a fault fracture zone provided by the present application. Figure 6As shown, the electronic device 10 may include one or more (only one is shown in the figure) processors 02 (the processor 02 may include but is not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA), a memory 04 for storing data, and a transmission module 06 for communication functions. It can be understood by those skilled in the art that Figure 6 The structure shown is only for illustration and does not limit the structure of the above electronic device. Figure 6 More or fewer components as shown, or with Figure 6 Different configurations are shown.

[0104] The memory 04 can be used to store software programs and modules of application software, such as program instructions / modules corresponding to the method for determining the fault fracture zone in the embodiment of the present application. The processor 02 executes various functional applications and data processing by running the software programs and modules stored in the memory 04, that is, the method for determining the fault fracture zone of the above-mentioned application is realized. The memory 04 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some examples, the memory 04 may further include a memory remotely arranged relative to the processor 02, and these remote memories may be connected to the electronic device 10 via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0105] The transmission module 06 is used to receive or send data via a network. The specific example of the above network may include a wireless network provided by a communication provider of the electronic device 10. In one example, the transmission module 06 includes a network adapter (Network Interface Controller, NIC), which can be connected to other network devices through a base station so as to communicate with the Internet. In one example, the transmission module 06 can be a radio frequency (Radio Frequency, RF) module, which is used to communicate with the Internet wirelessly.

[0106] At the software level, the above-mentioned fault zone determination device can be as follows: Figure 7 As shown, including:

[0107] An acquisition module 701 is used to acquire three-dimensional seismic data of a target stratum and determine fault detection data from the three-dimensional seismic data;

[0108] A calculation module 702 is used to calculate a covariance matrix for a local seismic subvolume in the fault detection data, and to represent the fault detection data through a grayscale image;

[0109] A detection module 703 is used to detect a first boundary surface and a second boundary surface of the fault fracture zone from the grayscale image by using an edge detection operator in image processing;

[0110] An enhancement module 704 is used to enhance the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix;

[0111] The determination module 705 is used to determine the range defined by the enhanced first boundary surface and the second boundary surface as the fault fracture zone, and determine the distance between the first boundary surface and the second boundary surface as the width of the fault fracture zone.

[0112] In one embodiment, the enhancement module 704 may include: a smoothing unit, used to smooth the image in the direction parallel to the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix; a sharpening unit, used to sharpen the image in the direction perpendicular to the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix.

[0113] In one embodiment, the above-mentioned fault rupture zone determination device may also include: a drawing module, which is used to determine the range defined by the first boundary surface and the second boundary surface after enhancement processing as the fault rupture zone, and determine the distance between the first boundary surface and the second boundary surface as the width of the fault rupture zone, and then form a fault polygon according to the determined fault rupture zone and the determined width of the fault rupture zone; a generation module is used to generate an oil and gas migration and accumulation channel or a fault-controlled dissolution reservoir according to the formed fault polygon.

[0114] In one embodiment, smoothing the image in a direction parallel to the first boundary surface and the second boundary surface may include: performing low-pass filtering according to the following formula to smooth the image in a direction parallel to the first boundary surface and the second boundary surface:

[0115]

[0116] Where i = s1, s2, s1 represents the first boundary surface, s2 represents the second boundary surface, G i represents the Gaussian filter, ε1 and ε2 represent two orthogonal eigenvectors in the covariance matrix parallel to the cross-section direction, ε3 represents an eigenvector in the covariance matrix perpendicular to the cross-section direction, σ i1 , σ i2 , σ i3 represents the Gaussian operator standard deviation, where

[0117] Performing sharpening processing on the image in the direction perpendicular to the first boundary surface and the second boundary surface, including: calculating the second-order partial derivative of the image in the direction perpendicular to the first boundary surface and the second boundary surface according to the following operator to perform sharpening processing:

[0118]

[0119] Among them, LoG i represents the Laplace operator.

[0120] In one embodiment, detecting the first boundary surface and the second boundary surface of the fault rupture zone from the grayscale image by using an edge detection operator in image processing can include: denoising the grayscale image by Gaussian filtering; after denoising, determining the gradient of the grayscale image; filtering out non-edge pixels in the grayscale image to make the fuzzy boundaries clear, and retaining the maximum value of the gradient intensity at each pixel point during the filtering process; determining possible boundaries by a double threshold method; tracking possible boundaries, and determining weak boundaries connected to strong boundaries in pixel positions as boundary pixels, so as to detect the first boundary surface and the second boundary surface of the fault rupture zone from the grayscale image.

[0121] In one embodiment, after determining the range defined by the first boundary surface and the second boundary surface after enhancement processing as the fault fracture zone and determining the distance between the first boundary surface and the second boundary surface as the width of the fault fracture zone, it is also possible to determine whether the extension characteristics of the fault fracture zone meet the preset quality indicators; when it is determined that the preset quality indicators are met, a fault polygon is formed according to the determined fault fracture zone and the determined width of the fault fracture zone; based on the formed fault polygon, an oil and gas migration and accumulation channel or a fault-controlled dissolution reservoir is generated.

[0122] The embodiment of the present application also provides a specific implementation of an electronic device capable of implementing all the steps in the method for determining a fault fracture zone in the above embodiment, wherein the electronic device specifically includes the following contents: a processor, a memory, a communication interface, and a bus; wherein the processor, the memory, and the communication interface communicate with each other through the bus; the processor is used to call a computer program in the memory, and when the processor executes the computer program, all the steps in the method for determining a fault fracture zone in the above embodiment are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0123] Step 1: Acquire three-dimensional seismic data of a target stratum, and determine fault detection data from the three-dimensional seismic data;

[0124] Step 2: Calculate the covariance matrix of the local earthquake sub-volume in the fault detection data, and characterize the fault detection data by a grayscale image;

[0125] Step 3: Detecting a first boundary surface and a second boundary surface of the fault fracture zone from the grayscale image by using an edge detection operator in image processing;

[0126] Step 4: performing enhancement processing on the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix;

[0127] Step 5: The range defined by the enhanced first boundary surface and the second boundary surface is determined as the fault fracture zone, and the distance between the first boundary surface and the second boundary surface is determined as the width of the fault fracture zone.

[0128] The embodiments of the present application also provide a computer-readable storage medium capable of implementing all the steps in the method for determining a fault fracture zone in the above embodiments. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, all the steps in the method for determining a fault fracture zone in the above embodiments are implemented. For example, when the processor executes the computer program, the following steps are implemented:

[0129] Step 1: Acquire three-dimensional seismic data of a target stratum, and determine fault detection data from the three-dimensional seismic data;

[0130] Step 2: Calculate the covariance matrix of the local earthquake sub-volume in the fault detection data, and characterize the fault detection data by a grayscale image;

[0131] Step 3: Detecting a first boundary surface and a second boundary surface of the fault fracture zone from the grayscale image by using an edge detection operator in image processing;

[0132] Step 4: performing enhancement processing on the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix;

[0133] Step 5: The range defined by the enhanced first boundary surface and the second boundary surface is determined as the fault fracture zone, and the distance between the first boundary surface and the second boundary surface is determined as the width of the fault fracture zone.

[0134] From the above description, it can be seen that the embodiment of the present application targets the width characteristics of the fault fracture zone, applies edge detection means to track the boundary of the fracture zone, uses the two boundary surfaces corresponding to the upper and lower plates of the fault to characterize the fault and fracture zone response, and simultaneously performs enhancement processing on the two boundary surfaces of the fault fracture zone, so that the result is more refined, and the conventional research only on the fault surface is transformed into the characterization of the fault fracture zone body, which can effectively improve the accuracy of the research on oil and gas migration and accumulation channels or fault-controlled reservoirs. The above scheme solves the technical problem of low data accuracy caused by the existing research only on the fault surface without considering the fault fracture zone, and achieves the technical effect of effectively improving the accuracy of stratigraphic characterization.

[0135] The user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties, and the collection, use and processing of relevant data must comply with the relevant laws, regulations and standards of relevant countries and regions, and provide corresponding operation entrances for users to choose to authorize or refuse.

[0136] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the hardware + program embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0137] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0138] Although the present application provides method operation steps as described in the embodiments or flowcharts, more or fewer operation steps may be included based on conventional or non-creative labor. The order of steps listed in the embodiments is only one way of executing the order of many steps and does not represent the only execution order. When the actual device or client product is executed, it can be executed in the order of the method shown in the embodiments or the drawings or in parallel (for example, in a parallel processor or multi-threaded processing environment).

[0139] The systems, devices, modules or units described in the above embodiments may be implemented by computer chips or entities, or by products with certain functions. A typical implementation device is a computer. Specifically, the computer may be, for example, a personal computer, a laptop computer, a vehicle-mounted human-computer interaction device, a cellular phone, a camera phone, a smart phone, a personal digital assistant, a media player, a navigation device, an email device, a game console, a tablet computer, a wearable device, or a combination of any of these devices.

[0140] Although the present specification embodiment provides the method operation steps as described in the embodiment or flow chart, more or less operation steps may be included based on conventional or non-creative means. The order of steps listed in the embodiment is only one way in the order of execution of many steps, and does not represent a unique execution order. When the device or terminal product in practice is executed, it can be executed in sequence or in parallel (such as a parallel processor or a multi-threaded processing environment, or even a distributed data processing environment) according to the method shown in the embodiment or the accompanying drawings. The term "include", "comprise" or any other variant thereof is intended to cover non-exclusive inclusion, so that the process, method, product or equipment including a series of elements not only includes those elements, but also includes other elements not clearly listed, or also includes elements inherent to such process, method, product or equipment. In the absence of more restrictions, it is not excluded that there are other identical or equivalent elements in the process, method, product or equipment including the elements.

[0141] For the convenience of description, the above devices are described in various modules according to their functions. Of course, when implementing the embodiments of this specification, the functions of each module can be implemented in the same or more software and / or hardware, or the module implementing the same function can be implemented by a combination of multiple sub-modules or sub-units. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0142] Those skilled in the art also know that, in addition to implementing the controller in a purely computer-readable program code, the controller can be made to implement the same function in the form of logic gates, switches, application-specific integrated circuits, programmable logic controllers, and embedded microcontrollers by logically programming the method steps. Therefore, such a controller can be considered as a hardware component, and the devices for implementing various functions included therein can also be considered as structures within the hardware component. Or even, the devices for implementing various functions can be considered as both software modules for implementing the method and structures within the hardware component.

[0143] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0144] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0145] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0146] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0147] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0148] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0149] Those skilled in the art will appreciate that the embodiments of this specification may be provided as methods, systems or computer program products. Therefore, the embodiments of this specification may take the form of complete hardware embodiments, complete software embodiments or embodiments combining software and hardware. Moreover, the embodiments of this specification may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0150] The present specification embodiments may be described in the general context of computer-executable instructions executed by a computer, such as program modules. Generally, program modules include routines, programs, objects, components, data structures, etc. that perform specific tasks or implement specific abstract data types. The present specification embodiments may also be practiced in distributed computing environments where tasks are performed by remote processing devices connected through a communication network. In a distributed computing environment, program modules may be located in local and remote computer storage media, including storage devices.

[0151] Each embodiment in this specification is described in a progressive manner, and the same and similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the system embodiment, since it is basically similar to the method embodiment, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment. In the description of this specification, the description of the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the embodiment of this specification. In this specification, the schematic representation of the above terms does not necessarily target the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner. In addition, in the absence of contradiction, a person skilled in the art can combine and combine the different embodiments or examples described in this specification and the features of different embodiments or examples.

[0152] The above is only an example of the embodiment of the present specification and is not intended to limit the embodiment of the present specification. For those skilled in the art, the embodiment of the present specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiment of the present specification shall be included in the scope of the claims of the embodiment of the present specification.

Claims

1. A method for determining a fault fracture zone, characterized in that: The method comprises: Acquire three-dimensional seismic data of a target stratum, and determine fault detection data from the three-dimensional seismic data; Calculating a covariance matrix for a local seismic subvolume in the fault detection data, and representing the fault detection data by a grayscale image; Detecting a first boundary surface and a second boundary surface of the fault fracture zone from the grayscale image by using an edge detection operator in image processing; Performing enhancement processing on the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix; The range defined by the enhanced first boundary surface and the second boundary surface is determined as the fault fracture zone, and the distance between the first boundary surface and the second boundary surface is determined as the width of the fault fracture zone.

2. The method according to claim 1, characterized in that The first boundary surface and the second boundary surface are enhanced by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix, including: Smoothing the image in the direction parallel to the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix; The image in the direction perpendicular to the first boundary surface and the second boundary surface is sharpened by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix.

3. The method according to claim 2, characterized in that Smoothing the image in a direction parallel to the first boundary surface and the second boundary surface includes: Low-pass filtering is performed according to the following formula to smooth the image in the direction parallel to the first boundary surface and the second boundary surface: Where i = s1, s2, s1 represents the first boundary surface, s2 represents the second boundary surface, G i represents the Gaussian filter, ε1 and ε2 represent two orthogonal eigenvectors in the covariance matrix parallel to the cross-section direction, ε3 represents an eigenvector in the covariance matrix perpendicular to the cross-section direction, σ i1 , σ i2 , σ i3 represents the Gaussian operator standard deviation, where Performing sharpening processing on the image in the direction perpendicular to the first boundary surface and the second boundary surface, including: calculating the second-order partial derivative of the image in the direction perpendicular to the first boundary surface and the second boundary surface according to the following operator to perform sharpening processing: Among them, LoG i represents the Laplace operator.

4. The method according to claim 1, characterized in that: Detecting a first boundary surface and a second boundary surface of the fault fracture zone from the grayscale image by using an edge detection operator in image processing, including: Performing denoising on the grayscale image by Gaussian filtering; After denoising is completed, determining the gradient of the grayscale image; Filtering out non-edge pixels in the grayscale image to make the blurred boundary clearer, and retaining the maximum value of the gradient intensity at each pixel during the filtering process; The possible boundaries are determined by a double threshold approach; Possible boundaries are tracked, and weak boundaries connected to strong boundaries in pixel positions are determined as boundary pixel points, so as to detect the first boundary surface and the second boundary surface of the fault fracture zone from the grayscale image.

5. The method according to any one of claims 1 to 4, characterized in that After determining the range defined by the enhanced first boundary surface and the second boundary surface as the fault fracture zone, and determining the distance between the first boundary surface and the second boundary surface as the width of the fault fracture zone, the method further includes: Determining whether the extension characteristics of the fault fracture zone meet preset quality indicators; When it is determined that the preset quality index is met, a fault polygon is formed according to the determined fault fracture zone and the determined width of the fault fracture zone; Based on the formed fault polygons, oil and gas migration and accumulation channels or fault-controlled dissolution reservoirs are generated.

6. A device for determining a fault fracture zone, characterized in that: include: An acquisition module, used for acquiring three-dimensional seismic data of a target stratum, and determining fault detection data from the three-dimensional seismic data; A calculation module, used for calculating a covariance matrix for a local seismic subvolume in the fault detection data, and representing the fault detection data through a grayscale image; A detection module, used for detecting a first boundary surface and a second boundary surface of the fault fracture zone from the grayscale image by using an edge detection operator in image processing; An enhancement module, used for enhancing the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix; The determination module is used to determine the range defined by the first boundary surface and the second boundary surface after the enhancement process as the fault fracture zone, and determine the distance between the first boundary surface and the second boundary surface as the width of the fault fracture zone.

7. The device according to claim 6, characterized in that The enhancement module comprises: A smoothing unit, used for smoothing the image in the direction parallel to the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix; The sharpening unit is used to sharpen the image in the direction perpendicular to the first boundary surface and the second boundary surface by using two orthogonal eigenvectors parallel to the cross-sectional direction and one eigenvector perpendicular to the cross-sectional direction in the covariance matrix.

8. The device according to claim 6, characterized in that Also includes: A drawing module, for forming a fault polygon according to the determined fault shattering zone and the determined width of the fault shattering zone after determining the range defined by the enhanced first boundary surface and the second boundary surface as the fault shattering zone and determining the distance between the first boundary surface and the second boundary surface as the width of the fault shattering zone; The generation module is used to generate oil and gas migration and accumulation channels or fault-controlled dissolution reservoirs based on the formed fault polygons.

9. An electronic device comprising a processor and a memory for storing instructions executable by the processor, characterized in that: When the processor executes the instructions, the steps of the method according to any one of claims 1 to 5 are implemented.

10. A computer-readable storage medium having a computer program / instruction stored thereon, characterized in that: When the computer program / instructions are executed by a processor, the steps of the method according to any one of claims 1 to 5 are implemented.

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