Reservoir fracture identification method and system based on ant body and edge detection

Abstract

The invention provides a reservoir fracture identification method and system based on ant body and edge detection. The method comprises the following steps: step 1, obtaining seismic data of a work area to be detected; 2, calculating variance volume data of the seismic data according to the obtained seismic data; step 3, performing edge detection on the obtained variance volume data to obtain a data volume after data edge extraction; 4, performing multiple ant tracing on an edge detection result to obtain fault development information; according to the method, the illusion caused by poor data quality is considered, and the purpose of accurately identifying the information of the breaking joint body is achieved by enhancing the data of the tiny breaking joint body and the place with weak signals through edge detection.

Description

Technical Field

[0001] The invention belongs to the technical field of geophysics and oil and gas exploration and development, and in particular relates to a reservoir fracture identification method and system based on ant body and edge detection. Background Art

[0002] Fractured oil and gas reservoirs are a very important type of oil and gas reservoirs, and the fractures and faults in them are of great significance to the storage and migration of oil and gas. Therefore, accurate prediction of the spatial distribution of fault bodies can effectively improve the efficiency of oil and gas exploration and development and reduce the cost of exploration and development. Especially in the late stage of exploration, as the development potential of simple structural oil and gas reservoirs is exhausted, the accurate identification of small-scale fault bodies plays a guiding role in the subsequent development under complex geological conditions in the middle and late stages of exploration.

[0003] The method of fault identification is mainly based on extracting seismic attributes from logging data or seismic data. Seismic attributes are commonly used technical means for fault interpretation, and commonly used seismic attributes include coherence, curvature, ant body, etc. However, for complex reservoirs, the effect of conventional methods is not very ideal. Even for the same seismic data, the fault body results of various attributes may be different. When multiple attributes are different, accurately reflecting the development of fault bodies is the difficulty of the current interpretation of seismic attribute fault bodies. In addition, under complex geological conditions, conventional attributes cannot accurately reflect fault information. The Chinese invention patent with application publication number CN1090001801A discloses a fault variable scale identification method based on multiple iterations of ant colony algorithm. The multiple ant bodies described in this method are just multiple iterations based on the first ant body to enhance the display effect, without changing the orientation of the fault body and the spatial distribution of the fault body. For data with poor data quality, the first ant body fault body interpretation results are often wrong, which makes the subsequent fracture body results have large errors. Summary of the invention

[0004] The purpose of the present invention is to provide a reservoir fracture identification method and system based on ant body and edge detection, which solves the defect of large result error in the existing reservoir fracture identification method.

[0005] The present invention takes into account the illusion caused by poor data quality, and enhances the data of tiny fractures and places with weak signals through edge detection, so as to achieve the purpose of accurately identifying fracture information.

[0006] In order to achieve the above object, the technical solution adopted by the present invention is:

[0007] The present invention provides a reservoir fracture identification method based on ant body and edge detection, comprising the following steps:

[0008] Step 1, obtaining seismic data of the work area to be measured;

[0009] Step 2, calculating the variance volume data of the seismic data according to the obtained seismic data;

[0010] Step 3, performing edge detection on the obtained variance volume data to obtain a data volume after extracting the data edge;

[0011] Step 4: Perform multiple ant tracing on the edge detection results to obtain fault development information.

[0012] Preferably, the variance corresponding to each group of data in the seismic data is calculated using the following formula:

[0013]

[0014] Where x is the seismic data; L is the number of seismic record samples used in calculating the variance; J is the data of the Jth point in the seismic data; N is the number of adjacent channels used; w i is the triangular weighted function of the variance volume data; D is the variance corresponding to each set of data.

[0015] Preferably, in step 3, edge detection is performed on the obtained variance volume data using the following formula:

[0016] G i,j =f i+1,j,k +f i-1,j,k +f i,j+1,k +f i,j-1,k +f i,j,k+1 f i,j,k-1 -6f i,j

[0017] Among them, i is the i-th sampling point, j is the j-th seismic trace, k is the k-th seismic trace in the direction perpendicular to j, and f is the variance volume data; G i,j It is the value of each point in the data volume after extracting the data edge.

[0018] Preferably, in step 4, the multiple ant tracking includes two passive ant tracking and one active ant tracking.

[0019] Preferably, in step 4, multiple ant tracing is performed on the edge detection result, and the specific method is:

[0020] The edge detection results were input into the Petrel software for the first passive ant tracking to obtain the first ant body;

[0021] Using the first ant body to perform a first active ant tracking to obtain a second ant body;

[0022] Using the second ant body to perform second passive ant tracking to obtain a final tracking result;

[0023] The tracing result is judged whether it is qualified according to the existing fault body information of the work area to be tested, and the final fault development information is obtained.

[0024] Preferably, whether the tracing result is qualified is judged according to the existing fault body information of the work area to be measured, and the final fault development information is obtained. The specific method is:

[0025] The obtained tracing results are superimposed and displayed with the existing fracture body information to obtain a superimposed display diagram;

[0026] Whether the tracing result is qualified is judged according to the obtained superimposed display image. When there is no mass in the fault body in the superimposed display image, and the trend and distribution are clear, the tracing result is considered qualified, and the obtained tracing result is used as the fault development information.

[0027] A reservoir fracture identification system based on ant body and edge detection, comprising:

[0028] A data acquisition unit, used for acquiring seismic data of the work area to be measured;

[0029] A variance calculation unit, used for calculating variance volume data of the seismic data according to the obtained seismic data;

[0030] An edge detection unit is used to perform edge detection on the obtained variance volume data to obtain a data volume after extracting the data edge;

[0031] The ant tracing unit is used to perform multiple ant tracing on the edge detection results to obtain the fault development information of the work area to be tested.

[0032] A computer-readable storage medium storing one or more programs, the one or more programs including instructions, which when executed by a computing device, cause the computing device to perform the method described.

[0033] A computing device comprising:

[0034] One or more processors, a memory, and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include steps for executing the method.

[0035] A chip, comprising: a memory having a computer program stored therein;

[0036] A processor is used to execute the computer program in the memory to implement the steps of the method.

[0037] Compared with the prior art, the present invention has the following beneficial effects:

[0038] The present invention provides a reservoir fracture identification method based on ant body and edge detection, which mainly improves the poor characterization effect of conventional attributes on fault bodies under complex geological conditions. Specifically: three-dimensional edge detection is introduced into attribute body extraction, and edge detection is performed on the variance body to enhance the recognition ability of small fault bodies; secondly, after edge detection of the variance body, multiple ant body tracing is performed to obtain high-precision small-scale fault body development identification results, providing data support for subsequent development work. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 It is a technical flow chart of the fracture identification technology of fractured oil reservoir based on ant body and edge detection of the present invention;

[0040] Figure 2 is a randomly selected cross-well seismic record section;

[0041] Figure 3 Part of the seismic attribute profiles obtained by conventional methods and the profiles extracted by the method of the present invention;

[0042] Figure 4 The method of the present invention is used to extract the fracture body and verify the seismic data;

[0043] Figure 5 This is a slice of the fault block where Well B24 is located;

[0044] Figure 6 This is the conventional method sectioning of the B1 well area;

[0045] Figure 7 Multiple ant body slices based on edge detection are superimposed on the existing fault interpretation results.

[0046] Figure 8 Schematic diagram of a computer device provided by an embodiment of the present invention

[0047] Fig. 9 The block diagram is a chip provided according to an embodiment of the present invention. DETAILED DESCRIPTION

[0048] In the following description, specific details such as specific system structures, technologies, etc. are provided for the purpose of illustration rather than limitation, so as to provide a thorough understanding of the embodiments of the present application. However, it should be clear to those skilled in the art that the present application may also be implemented in other embodiments without these specific details. In other cases, detailed descriptions of well-known systems, devices, circuits, and methods are omitted to prevent unnecessary details from obstructing the description of the present application.

[0049] It should be understood that when used in the present specification and the appended claims, the term "comprising" indicates the presence of described features, wholes, steps, operations, elements and / or components, but does not exclude the presence or addition of one or more other features, wholes, steps, operations, elements, components and / or combinations thereof.

[0050] It should also be understood that the term “and / or” used in the specification and appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes these combinations.

[0051] As used in the specification and appended claims of this application, the term "if" can be interpreted as "when" or "uponce" or "in response to determining" or "in response to detecting", depending on the context. Similarly, the phrase "if it is determined" or "if [described condition or event] is detected" can be interpreted as meaning "uponce it is determined" or "in response to determining" or "uponce [described condition or event] is detected" or "in response to detecting [described condition or event]", depending on the context.

[0052] In addition, in the description of the present application specification and the appended claims, the terms "first", "second", "third", etc. are only used to distinguish the descriptions and cannot be understood as indicating or implying relative importance.

[0053] References to "one embodiment" or "some embodiments" etc. described in the specification of this application mean that one or more embodiments of the present application include specific features, structures or characteristics described in conjunction with the embodiment. Therefore, the statements "in one embodiment", "in some embodiments", "in some other embodiments", "in some other embodiments", etc. that appear in different places in this specification do not necessarily refer to the same embodiment, but mean "one or more but not all embodiments", unless otherwise specifically emphasized in other ways. The terms "including", "comprising", "having" and their variations all mean "including but not limited to", unless otherwise specifically emphasized in other ways.

[0054] Figure 1 This is a system framework diagram of the fracture identification technology for fractured oil reservoirs based on ant body and edge detection.

[0055] The technical solution of the present invention is further described below with reference to specific embodiments and with reference to the practical application of seismic data in the B1 well area of ​​the T oil field.

[0056] Example 1

[0057] This embodiment selects a seismic data volume of a certain work area as the data source of this embodiment, and selects a profile passing through the B24 well, such as Figure 2As shown in the figure, the three-dimensional data volume with Inline (main survey line) numbers from 1964 to 2164 is selected with this section as the center for subsequent calculation of the variance volume. Due to the complex geological environment in this work area, the seismic energy is weak, the resolution of seismic records is low, the phase axis is missing in some areas, and the conventional seismic attribute effect is not good (such as Figure 3 As shown, Figure 3 a, b, and c are conventional attributes; Figure 3 d is the original data, Figure 3 e is the result of the invention).

[0058] This embodiment provides a reservoir fracture identification method based on ant body and edge detection, comprising the following steps:

[0059] Step 1, obtain the seismic data of the work area to be measured (101 longitudinal survey lines, 101 connecting survey lines, 25m interval between survey lines, 1876 sampling points per survey line, and 8m sampling interval);

[0060] Step 2: Calculate the variance volume data of the seismic data based on the obtained seismic data.

[0061] Variance volume data is calculated by calculating the variance of the adjacent area of ​​each point in the three-dimensional original seismic data. The value of each point is equal to the variance of an array centered on the point, which reflects the continuity of the signal. For each point, the variance is calculated as follows:

[0062]

[0063] Where x is the seismic data; L is the number of seismic record samples used to calculate the variance; J is the data of the Jth point in the seismic data; N is the number of adjacent channels used, which is set by experience; w i It is the triangular weighted function of the variance volume data. The farther away from the central point, the smaller the value is, and the value range is 0 to 1. D is the variance volume attribute of the seismic data, which represents the variance of an array centered on this point.

[0064] Step 3: Perform edge detection on the obtained variance volume data to obtain a data volume after extracting data edges.

[0065] Edge detection is a technology for extracting the edges of images. The main idea of ​​edge detection is to extract the boundary lines between these changing values ​​based on the changes in the values ​​between the data.

[0066] Edge detection of seismic data is to process seismic data as images, and compensate for the poor signal and disappearance of the event axis in complex basin environments through edge detection, thereby reducing the illusion caused by poor data quality.

[0067] Edge detection is implemented based on the edge detection operator. The Laplacian edge detection operator is as follows:

[0068]

[0069] In practical application, it is realized through the discrete form of Laplacian edge detection operator. For a point in seismic data, the edge detection calculation is as follows:

[0070] G i,j =f i+1,j +f i-1,j +f i,j+1 +f i,j-1 -4f i,j

[0071] Among them, i is the i-th sampling point, j is the j-th seismic trace, and f is the variance volume data.

[0072] However, for edge detection of three-dimensional data, the Laplacian edge detection operator in the traditional two-dimensional image field is extended to the three-dimensional case, and k is added as the second horizontal direction; the edge detection operator is rewritten as:

[0073] G i,j =f i+1,j,k +f i-1,j,k +f i,j+1,k +f i,j-1,k +f i,j,k+1 f i,j,k-1 -6f i,j

[0074] Among them, i is the i-th sampling point, j is the j-th seismic trace, k is the k-th seismic trace perpendicular to j, and f is the variance volume data. i,j It is the value of each point in the data volume after extracting the data edge.

[0075] Step 4: Perform multiple ant tracing combining active and passive ant bodies on the edge detection results to obtain tracing results.

[0076] Multiple ant tracing includes two passive ant tracings and one active ant tracing. The purpose is to highlight the small-scale fault body information. After the first ant tracing of the edge detection results, the fault body information is relatively complete. However, at this time, the small-scale fault body is covered by the large-scale fault body. Through multiple ant tracings, the small-scale fault body information is magnified.

[0077] The specific operations are as follows:

[0078] S1: Import edge detection result data into the commercial software Petrel.

[0079] S2: Open the volume attributes, change the attributes type to AntTracking, and change the parameter to passive for passive ant tracing.

[0080] S3: Replace the input data with the ant body output in the second step, and change the parameter to aggressive to perform main ant tracing.

[0081] S4: Replace the input data with the ant body output in the third step, and change the parameter back to passive for passive ant tracing.

[0082] S5: Open the output ant body and check whether the ant body conforms to geological laws and knowledge. If it meets the conditions, proceed to the next step. Otherwise, it is necessary to adjust the parameters in steps S2 to S4, such as changing aggressive in S3 to passive to obtain the tracing result.

[0083] Step 5, using the existing fracture information obtained through existing drilling and core interpretation in the work area to be tested, the existing fracture information is superimposed and displayed with the tracing result obtained in step 4, and whether the tracing result obtained in step 4 is qualified is judged based on the superimposed display diagram. If it is unqualified, the parameters in steps 2 and 4 are optimized based on experience until the tracing result obtained in step 4 is qualified.

[0084] Tune the parameters in step 2 and step 4 based on experience. The specific method is:

[0085] Adjust the number of adjacent channels when calculating the variance volume in step 2;

[0086] Adjust the number of ant traces in step 4, or

[0087] Adjust the passive and active parameters of the ant tracer in step 4.

[0088] The specific method for judging eligibility is:

[0089] When there are no lumps in the fracture body and the direction and distribution are relatively clear, the result is considered qualified, otherwise it is unqualified.

[0090] Example 2

[0091] This embodiment provides a reservoir fracture identification method based on ant body and edge detection, comprising the following steps:

[0092] Step 1: First, use the seismic data to calculate the variance volume, L is 80, N is 3

[0093]

[0094] It is worth noting that N is not in one direction, but in both the Inline and Crossline directions. The variance volume data is the variance of the three-dimensional data, not the variance of the section. i is a proportionality factor that is inversely proportional to the distance.

[0095] Step 2: Use the variance volume data output from the first step as input for edge detection. Different from treating the section as an image for edge detection, the Laplacian edge detection operator in the traditional two-dimensional image field is used:

[0096] G i,j =f i+1,j +f i-1,j +f i,j+1 +f i,j-1 -4f i,j

[0097] Extending to the three-dimensional case, we add k as a second direction in the horizontal plane:

[0098] G i,j =f i+1,j,k +f i-1,j,k +f i,j+1,k +f i,j-1,k +f i,j,k+1 f i,j,k-1 -6f i,j

[0099] The three-dimensional edge detection operator is used to perform edge detection on the variance volume to obtain the final edge detection result.

[0100] Step 3, import the output edge detection results into the commercial software Petrel; perform multiple ant body extraction, mainly including first performing a passive ant tracing to extract the fracture body information, then performing active ant tracing to highlight the small fracture bodies, and finally performing passive ant tracing again to obtain the final fracture body information. In actual application, after the first ant tracing of the edge detection result, the fracture body information is relatively complete. At this time, it can be judged whether the parameters are reasonable. The subsequent two ant tracings are only to enhance the display effect.

[0101] The specific operations are as follows:

[0102] S1: Import edge detection result data into the commercial software Petrel.

[0103] S2: Open the volume attributes, change the attributes type to AntTracking, and change the parameter to passive for passive ant tracing.

[0104] S3: Replace the input data with the ant body output in the second step, and change the parameter to aggressive to perform main ant tracing.

[0105] S4: Replace the input data with the ant body output in the third step, and change the parameter back to passive for passive ant tracing.

[0106] S5: Open the output ant body and check whether the ant body conforms to geological laws and knowledge. If it meets the conditions, proceed to the next step. Otherwise, it is necessary to adjust the parameters in steps S2 to S4, such as changing aggressive in S3 to passive to obtain the tracing result.

[0107] Step 4, using the existing fracture information obtained through drilling and core interpretation, the existing fracture information is superimposed with the tracer result obtained in step 4, and the superimposed display is used to determine whether the tracer result obtained in step 4 is qualified. If it is unqualified, the parameters in steps 1 and 3 are optimized according to experience until the tracer result obtained in step 4 is qualified. Figure 5 The results show that there are no lumps in the fault body, and the trend and distribution are relatively clear. It is believed that the result meets the requirements.

[0108] Figure 2 The conventional properties obtained for the seismic section shown are as follows Figure 3 As shown, for places with poor seismic data, it is easy to create false images and fail to reflect the true fault distribution. However, using the method described in this application, it can be seen that the underground is mainly vertical fractures and high-angle fractures, which is consistent with imaging logging and core drilling. Figure 4 As shown, the dotted line is the logging position. At the arrow point, the well encountered a fault, and stratigraphic repetitions occurred near the fault (including repetitions in logging curves and lithology). In the attributes extracted in this application, the depth interpretation showed the existence of a fault, so it is believed that the method described in this application can detect the distribution of fault bodies.

[0109] Example 3

[0110] Seismic data near the B1 well with Inline (main survey line) numbers from 2356 to 2556 and Crossline (connection survey line) numbers from 1724 to 1924 in the same work area are selected. There are two wells, B1 and B15, in the area. Since the area was developed earlier and the wells are densely located, the interpretation and characterization of the faults are relatively complete. The method in Example 1 is applied to the data to obtain the fault distribution in the area. The fault plane distribution is analyzed, from Figure 6 It can be seen that conventional methods cannot specifically characterize the faults near the north, and there are problems such as missing faults and wrong fault directions. Figure 7 What is shown in FIG. 1 is the fault distribution and direction finally obtained by the method proposed in this patent, which is consistent with the actual situation.

[0111] Example 4

[0112] This embodiment provides a reservoir fracture identification system based on ant body and edge detection, including:

[0113] A data acquisition unit, used for acquiring seismic data of the work area to be measured;

[0114] A variance calculation unit, used for calculating variance volume data of the seismic data according to the obtained seismic data;

[0115] An edge detection unit is used to perform edge detection on the obtained variance volume data to obtain a data volume after extracting the data edge;

[0116] The ant tracing unit is used to perform multiple ant tracing on the edge detection results to obtain the fault development information of the work area to be tested.

[0117] Example 5

[0118] This embodiment provides a terminal device, which includes a processor and a memory, wherein the memory is used to store a computer program, wherein the computer program includes program instructions, and the processor is used to execute the program instructions stored in the computer storage medium. The processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gates or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, which is suitable for implementing one or more instructions, and is specifically suitable for loading and executing one or more instructions to implement the corresponding method flow or corresponding function; the processor described in the embodiment of the present invention can be used for the operation of a reservoir fracture identification method based on ant body and edge detection.

[0119] Example 6

[0120] A schematic diagram of a computer device provided in this embodiment.

[0121] See also Figure 8 , the terminal device is a computer device. The computer device 60 of this embodiment includes: a processor 61, a memory 62, and a computer program 63 stored in the memory 62 and executable on the processor 61. When the computer program 63 is executed by the processor 61, the method for calculating the fluid composition in the reservoir transformation wellbore in the embodiment is implemented. To avoid repetition, it is not described one by one here. Alternatively, when the computer program 63 is executed by the processor 61, the functions of each model / unit in the system of embodiment 4 are implemented. To avoid repetition, it is not described one by one here.

[0122] The computer device 60 may be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server. The computer device 60 may include, but is not limited to, a processor 61 and a memory 62. Those skilled in the art will appreciate that Figure 8 This is only an example of the computer device 60 and does not constitute a limitation of the computer device 60. It may include more or fewer components than shown in the figure, or a combination of certain components, or different components. For example, the computer device may also include input and output devices, network access devices, buses, etc.

[0123] The processor 61 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc.

[0124] The memory 62 may be an internal storage unit of the computer device 60, such as a hard disk or memory of the computer device 60. The memory 62 may also be an external storage device of the computer device 60, such as a plug-in hard disk, a smart media card (SMC), a secure digital (SD) card, a flash card, etc., equipped on the computer device 60.

[0125] Furthermore, the memory 62 may include both an internal storage unit of the computer device 60 and an external storage device. The memory 62 is used to store computer programs and other programs and data required by the computer device. The memory 62 may also be used to temporarily store data that has been output or is to be output.

[0126] Example 7

[0127] Fig. 9 A block diagram of a chip provided in this embodiment.

[0128] See also Fig. 9 , the terminal device is a chip, and the chip 600 of this embodiment includes a processor 622, which may be one or more, and a memory 632 for storing a computer program executable by the processor 622. The computer program stored in the memory 632 may include one or more modules, each corresponding to a set of instructions. In addition, the processor 622 may be configured to execute the computer program to execute the above-mentioned reservoir fracture identification method based on ant body and edge detection.

[0129] In addition, the chip 600 may further include a power supply component 626 and a communication component 650, wherein the power supply component 626 may be configured to perform power management of the chip 600, and the communication component 650 may be configured to implement communication, for example, wired or wireless communication, of the chip 600. In addition, the chip 600 may further include an input / output (I / O) interface 658. The chip 600 may operate based on an operating system stored in the memory 632.

[0130] Example 10

[0131] This embodiment also provides a storage medium, specifically a computer-readable storage medium (Memory), which is a memory device in a terminal device for storing programs and data. It is understandable that the computer-readable storage medium here can include both the built-in storage medium in the terminal device and the extended storage medium supported by the terminal device. The computer-readable storage medium provides a storage space, which stores the operating system of the terminal. In addition, one or more instructions suitable for being loaded and executed by the processor are also stored in the storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory, or a non-volatile memory (Non-Volatile Memory), such as at least one disk memory.

[0132] One or more instructions stored in a computer-readable storage medium can be loaded and executed by a processor to implement the corresponding steps of a reservoir fracture identification method based on ant body and edge detection in the above-mentioned embodiment; one or more instructions in the computer-readable storage medium are loaded and executed by the processor to implement a reservoir fracture identification method based on ant body and edge detection described in Example 1.

[0133] The embodiments described above are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, a person skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. Such modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A reservoir fracture identification method based on ant body and edge detection, characterized in that: The following steps are involved: Step 1, obtaining seismic data of the work area to be measured; Step 2, calculating the variance volume data of the seismic data according to the obtained seismic data; Step 3, performing edge detection on the obtained variance volume data to obtain a data volume after extracting the data edge; Step 4: Perform multiple ant tracing on the edge detection results to obtain fault development information.

2. The reservoir fracture identification method based on ant body and edge detection according to claim 1 is characterized in that: The variance corresponding to each group of data in the seismic data is calculated using the following formula: Where x is the seismic data; L is the number of seismic record samples used in calculating the variance; J is the data of the Jth point in the seismic data; N is the number of adjacent channels used; w i is the triangular weighted function of the variance volume data; D is the variance corresponding to each set of data.

3. The reservoir fracture identification method based on ant body and edge detection according to claim 1 is characterized in that: In step 3, edge detection is performed on the obtained variance volume data using the following formula: G i，j =f i+1，j，k +f i-1，j，k +f i，j+1，k +f i，j-1，k +f i，j，k+1 f i，j，k-1 -6f i，j Among them, i is the i-th sampling point, j is the j-th seismic trace, k is the k-th seismic trace in the direction perpendicular to j, and f is the variance volume data; G i,j It is the value of each point in the data volume after extracting the data edge.

4. The reservoir fracture identification method based on ant body and edge detection according to claim 1 is characterized in that: In step 4, multiple ant tracking includes two passive ant tracking and one active ant tracking.

5. The reservoir fracture identification method based on ant body and edge detection according to claim 4 is characterized in that: In step 4, multiple ant tracing is performed on the edge detection results. The specific method is: The edge detection results were input into the Petrel software for the first passive ant tracking to obtain the first ant body; Using the first ant body to perform a first active ant tracking to obtain a second ant body; Using the second ant body to perform second passive ant tracking to obtain a final tracking result; The tracing result is judged whether it is qualified according to the existing fault body information of the work area to be tested, and the final fault development information is obtained.

6. The reservoir fracture identification method based on ant body and edge detection according to claim 5, characterized in that: The tracing results are judged to be qualified according to the existing fault body information of the work area to be tested, and the final fault development information is obtained. The specific method is: The obtained tracing results are superimposed and displayed with the existing fracture body information to obtain a superimposed display diagram; Whether the tracing result is qualified is judged according to the obtained superimposed display image. When there is no mass in the fault body in the superimposed display image, and the trend and distribution are clear, the tracing result is considered qualified, and the obtained tracing result is used as the fault development information.

7. A reservoir fracture identification system based on ant body and edge detection, characterized in that: include: A data acquisition unit, used for acquiring seismic data of the work area to be measured; A variance calculation unit, used for calculating variance volume data of the seismic data according to the obtained seismic data; An edge detection unit is used to perform edge detection on the obtained variance volume data to obtain a data volume after extracting the data edge; The ant tracing unit is used to perform multiple ant tracing on the edge detection results to obtain the fault development information of the work area to be tested.

8. A computer-readable storage medium storing one or more programs, characterized in that: The one or more programs include instructions, which, when executed by a computing device, cause the computing device to perform the method of any one of claims 1 to 6.

9. A computing device, characterized in that include: One or more processors, a memory and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the one or more programs include steps for executing the method described in any one of claims 1 to 6.

10. A chip, characterized in that: a memory having a computer program stored thereon; A processor, configured to execute the computer program in the memory to implement the steps of the method according to any one of claims 1 to 6.

Images