Underground small-scale fracture-cavity body earthquake effective identification method, system, equipment and medium

Abstract

The invention belongs to the technical field of oil and gas seismic exploration and development, and relates to an effective identification method for an underground small-scale fracture-cavity body earthquake, which mainly adopts a method for interpreting a horizon result based on a tectonic ground, constructing stratum reflection energy background data and stripping a background from original seismic data. Seismic signals related to the small-scale fracture-cavity body in the stratum are enhanced; by combining geological laws and drilling data, generality tracking of effective space characteristic values is carried out, and characteristic space engraving of a geologic body is achieved. According to the method, the spatial features of the geologic body covered under the stratum background energy are engraved, the understanding of the description precision and the distribution rule of the underground geologic body is improved by combining the geologic rule understanding, the drilling data and the like, and a powerful basis is provided for well position optimization and deployment of oil reservoir development and old well measure management.

Description

Technical Field

[0001] The present invention belongs to the technical field of oil and gas seismic exploration and development, and specifically relates to a method, system, equipment and medium for effectively identifying earthquakes of underground small-scale fractures and caves. Background Art

[0002] Exploration and development practices have shown that fracture networks and high-quality reservoirs associated with strike-slip fault zones are key factors in oil and gas migration and accumulation. With the deepening of oil and gas exploration, smaller-scale fracture-network-pore systems have become the main research objects of explorers for the exploration and development of deep fracture-vuggy reservoirs, and are the key areas for concentrated and efficient oil and gas exploration. However, according to previous research, the geophysical characteristics of small-scale fracture-network-pore systems are very weak. Under the seismic response of formations with strong wave impedance differences, the geophysical characteristics of small-scale fracture-network-pore systems are basically difficult to distinguish. The prediction accuracy of sensitive attributes such as conventional coherence, structural curvature, uniform root amplitude, and instantaneous amplitude for micro-scale fracture-network-pore systems is very low, and cannot meet the needs of current oil and gas exploration and development.

[0003] Therefore, there is an urgent need to develop an effective method for extracting and enhancing seismic signals related to small-scale fracture networks and pore systems, so as to realize the identification and spatial carving of weak signals hidden under strong background energy, so as to meet the actual needs of further exploration and development. Summary of the invention

[0004] The purpose of the present invention is to provide a method for effectively identifying small-scale underground fractures and caves by seismic analysis, which solves the problem of effectively characterizing small-scale heterogeneous fractures and caves in deep to ultra-deep strata.

[0005] The present invention is achieved through the following technical solutions:

[0006] An effective method for identifying small-scale underground fracture-cavity earthquakes comprises the following steps:

[0007] 1) Obtain seismic data and drilling data of a certain work area, carry out fine calibration of seismic data and drilling data, and obtain calibration results;

[0008] According to the calibration results, continuous tracking and interpretation of the top and bottom phase axes of the target layer are carried out to obtain the structural horizons of the top and bottom surfaces of the target layer;

[0009] According to the structural layers of the top and bottom surfaces of the target layer, original seismic data between the top and bottom surfaces of the target layer are obtained;

[0010] 2) Filter the original seismic data between the top and bottom layers of the target layer, complete the vertical small window and horizontal small range filtering, obtain the target data, and determine the seismic reflection characteristics of the target layer based on the target data;

[0011] 3) Based on the seismic reflection characteristics, the target data is considered to consist of two parts of data, including formation background energy field data and formation heterogeneity data;

[0012] 4) Removing the formation background energy field data from the target data to obtain formation heterogeneity data;

[0013] 5) Based on the calibration results and the formation heterogeneity data, obtain the energy anomaly phenomenon of the formation heterogeneity data; determine whether the energy anomaly phenomenon of the formation heterogeneity data matches one or more of the phenomena indicating the reservoir;

[0014] If not, return to step 2) to adjust the vertical hour window and the horizontal small range, and repeat steps 2) to 5) until the energy anomaly phenomenon of the formation heterogeneity data matches at least one of the phenomena indicating the reservoir.

[0015] Furthermore, in step 2), if the longitudinal hour window is less than 5 sampling points and the sampling rate is greater than 4ms or 5m, resampling is required, and the resampling sampling rate is 1ms or 2m;

[0016] The lateral small range is less than 9 adjacent seismic traces. If the lateral structural changes are drastic, the analysis is conducted along the survey line with the smallest structural change.

[0017] Furthermore, in step 2), the seismic reflection characteristics include background reflection characteristics and inhomogeneous reflection characteristics.

[0018] Furthermore, the background reflection characteristics include continuous wave crest reflections and continuous wave trough reflections;

[0019] The inhomogeneous reflection characteristics include strong energy reflection and chaotic reflection intertwined with multiple peaks and troughs.

[0020] Further, in step 3), the target data is regarded as the addition of two matrices, the target data is called matrix D, and the two matrices are named A and E respectively; wherein the A matrix corresponds to the formation background energy field data, and the E matrix corresponds to the formation heterogeneity data;

[0021] The A matrix is ​​reconstructed using the maximum cross-correlation analysis method, specifically:

[0022] First, the target data is flattened based on a certain structural layer to obtain layer flattened data;

[0023] When reconstructing each data trace, the cross-correlation value between the trace and several adjacent traces in the layer-leveled data is calculated, and the trace with the maximum cross-correlation value and the minimum seismic trace energy is taken as the layer-leveled reconstructed data of the trace;

[0024] All seismic traces in the layer-leveling data are reconstructed in sequence to obtain the layer-leveling stratigraphic background energy field data;

[0025] The flattened stratum background energy field data is reverse-flattened to restore the original structural layer to the original structural form, thereby obtaining the stratum background energy field data of the target data;

[0026] In order to deal with the smoothness between the reconstructed traces, the average of adjacent traces is taken before deflating.

[0027] Further, step 4) is specifically as follows: for the target data and the formation background energy field data, an E=DA operation is performed to remove the formation background energy field data from the target data to obtain formation heterogeneity data.

[0028] Furthermore, in step 5), the phenomena indicating the reservoir include drilling emptying, leakage, abnormal logging gas measurement value or abnormal drilling time.

[0029] The present invention also discloses an effective earthquake identification system for underground small-scale fractures and caves, comprising:

[0030] Data acquisition module, used to obtain seismic data and drilling data of a certain work area;

[0031] The calibration module is used to carry out fine calibration of seismic data and drilling data and obtain calibration results;

[0032] The continuous tracking interpretation module is used to carry out continuous tracking interpretation of the event axes of the top and bottom surfaces of the target layer according to the calibration results, and obtain the structural horizons of the top and bottom surfaces of the target layer; and obtain the original seismic data between the top and bottom surface horizons of the target layer according to the structural horizons of the top and bottom surfaces of the target layer;

[0033] The preprocessing module is used to filter the original seismic data between the top and bottom layers of the target layer, complete the filtering processing of the vertical hour window and the horizontal small range, obtain the target data, and determine the seismic reflection characteristics of the target layer according to the target data;

[0034] The formation background energy volume field building module is used to regard the target data as two parts of data based on the seismic reflection characteristics, including the formation background energy field data and the formation heterogeneity data;

[0035] A formation background energy field removal module is used to remove formation background energy field data from target data to obtain formation heterogeneity data;

[0036] An analysis module is used to obtain an energy anomaly phenomenon of the formation heterogeneity data based on the calibration results and the formation heterogeneity data; and to determine whether the energy anomaly phenomenon of the formation heterogeneity data matches one or more of the phenomena indicating the reservoir;

[0037] If not, the vertical small window and the horizontal small range in the preprocessing module are adjusted until at least one of the reservoir phenomena indicated by the energy anomaly of the formation heterogeneity data matches.

[0038] The present invention also discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for effectively identifying small-scale underground fractures and caves are implemented.

[0039] The present invention also discloses a computer-readable storage medium, which stores a computer program, and is characterized in that when the computer program is executed by a processor, the steps of the method for effectively identifying earthquakes of small-scale underground fractures and caves are implemented.

[0040] Compared with the prior art, the present invention has the following beneficial technical effects:

[0041] The present invention is to establish an effective seismic identification method for underground small-scale fractures and caves. It is a method for identifying formation heterogeneity by removing formation background energy. It mainly adopts a method based on tectonic interpretation of the formation results, constructs formation reflection energy background data and strips the background from the original seismic data to enhance the seismic signals related to small-scale fractures and caves in the formation; finally, by combining geological laws and drilling data to track the commonality of effective spatial characteristic values, the characteristic space carving of the geological body is realized. The carving of the spatial characteristics of the geological body hidden under the formation background energy is realized. By combining the understanding of geological laws, drilling data, etc., the understanding of the description accuracy and distribution law of underground geological bodies is improved, which provides a strong basis for the optimization and deployment of well sites for oil reservoir development and the treatment of old wells. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 A schematic diagram of scanning methods for reconstructing data A;

[0043] Figure 2 It is a superimposed display diagram of the original seismic data of a certain area and the data sections of the results of different modeling parameters;

[0044] Figure a is the original seismic profile; Figure b is the profile of 49 modeling intensities; Figure c is the profile of 25 modeling intensities; Figure d is the profile of 9 modeling intensities;

[0045] Figure 3 It is a superimposed display of the original seismic data of a certain area and the heterogeneous characteristic data results of different modeling parameters;

[0046] Figure a is the original seismic profile; Figure b is the profile of 49 modeling intensities; Figure c is the profile of 25 modeling intensities; Figure d is the profile of 9 modeling intensities;

[0047] Figure 4 The plane diagram of the root mean square attributes of the target layer obtained from the original seismic data of a certain area;

[0048] Figure 5 It is a plane diagram of the root mean square attributes of the target layer obtained based on the heterogeneous characteristic data of the present invention. DETAILED DESCRIPTION

[0049] In order to make the purpose, technical solution and advantages of the present invention more clear, the following is further described in detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention, that is, the embodiments described are only part of the embodiments of the present invention, not all embodiments.

[0050] The components described and shown in the drawings and embodiments of the present invention may be arranged and designed in various configurations. Therefore, the detailed description of the embodiments of the present invention provided in the following drawings is not intended to limit the scope of the claimed invention, but merely represents a selected embodiment of the present invention. Based on the drawings and embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0051] It should be noted that the terms "comprises", "includes" or any other variations are intended to cover non-exclusive inclusion, so that a process, element, method, article or equipment that includes a series of elements includes not only those elements, but also includes other elements not explicitly listed, or also includes elements inherent to the process, element, method, article or equipment.

[0052] The features and performances of the present invention are further described in detail below in conjunction with the embodiments.

[0053] The specific contents are as follows:

[0054] 1) Conduct detailed interpretation of structural layers based on seismic data

[0055] First, the seismic data and drilling data of a certain work area are obtained, and the fine calibration of the seismic data and drilling data is carried out to obtain the calibration results; based on the calibration results, continuous tracking and interpretation of the phase axes of the top and bottom surfaces of the target layer are carried out to obtain the structural horizons of the top and bottom surfaces of the target layer; based on the structural horizons of the top and bottom surfaces of the target layer, the original seismic data between the top and bottom surface horizons of the target layer are obtained.

[0056] According to the calibration results, the continuous tracking interpretation of the seismic phase axis is carried out to achieve the closure of the main survey line and the contact survey line. The final interpretation of the structural layer needs to reach a density of 1x1. After the structural layer interpretation is completed, the layer sample point interpolation is performed again to ensure that there are no gaps in the layer value of each sample point in the analysis area. In addition, when the layer thickness changes drastically, it is necessary to complete the top and bottom interpretation of the target layer to be analyzed.

[0057] 2) Target layer residual noise suppression preprocessing

[0058] The original seismic data between the top and bottom layers of the target layer are filtered, wherein the filter may be a median filter, a mean filter, etc., to complete the filtering processing of the vertical hour window and the horizontal small range to obtain the target data.

[0059] The seismic reflection characteristics of the target layer are determined based on the target data, such as continuous peak reflection, continuous trough reflection, chaotic reflection, and strong energy reflection intertwined with multiple peaks and troughs.

[0060] 3) Establishing the formation background energy body based on principal component analysis

[0061] The background energy body field construction is the key to the present invention. The present invention constructs the target data into a data matrix D, and the data matrix D is regarded as the addition of two matrices (A+E), in which one A matrix is ​​low-rank (due to certain background structural information inside, each row or column is linearly related), and the other E matrix is ​​sparse (it is information related to geological bodies such as heterogeneous fracture-cavity reservoirs, and each geological body is unrelated and considered to be sparse). Then the A matrix is ​​regarded as the formation background energy field, and the E matrix is ​​regarded as the energy field related to geological bodies such as heterogeneous fracture-cavity reservoirs, that is, heterogeneous data.

[0062] The A matrix is ​​reconstructed using the maximum cross-correlation analysis method. Take a 3D seismic data as an example (such as Figure 1 As shown in the figure, when reconstructing each data, the data is first flattened based on the interpreted structural layer, and the cross-correlation value between the data and the adjacent 8 data is calculated. The data with the maximum cross-correlation value and the minimum seismic data energy is taken as the reconstructed data of the data. Finally, the data is reversely flattened to restore the original structural form. All seismic data in the data are reconstructed in turn. In order to deal with the smooth characteristics between the reconstructed data (normal strata without development and structural mutations), the average value between adjacent data is taken before reverse flattening, and finally the stratum background energy field data is obtained.

[0063] 4) Remove the formation background energy field based on the target data

[0064] For the target data and the formation background energy field data, the E=DA operation is implemented to remove the formation background energy field from the original seismic data and obtain the formation heterogeneity data.

[0065] 5) Reliability analysis of well-seismic data for heterogeneous fracture-cavity identification results

[0066] Based on the original calibration results, complete the analysis of reservoir-indicating phenomena such as drilling emptying, leakage, abnormal logging gas measurement, and abnormal drilling time with the heterogeneity data E. Determine whether the abnormal energy phenomenon of the formation heterogeneity data matches one or more of the phenomena indicating the reservoir; if not, return to step 2) to adjust the vertical small window and the horizontal small range and repeat the processing of steps 2) to 5) until at least one of the phenomena indicating the reservoir of the abnormal energy phenomenon of the formation heterogeneity data matches.

[0067] The specific implementation steps are as follows:

[0068] 1) Carry out detailed interpretation of structural layers based on seismic data. First, carry out detailed calibration of seismic data and drilling data to determine the seismic reflection characteristics corresponding to the strata, and carry out continuous tracking interpretation of seismic phase axes to achieve the corresponding interpretation density.

[0069] 2) Filter the original seismic data between the top and bottom layers of the target layer, where the filter can be a median filter, a mean filter, etc., to complete the filtering of the vertical hour window and the horizontal small range to obtain the target data. The vertical hour window is generally less than 5 sampling points. If the sampling rate is greater than 4ms or 5m, it is necessary to consider resampling to 1ms or 2m; the horizontal small range is generally less than 9 adjacent seismic traces. If the horizontal structure changes dramatically, it is necessary to analyze along the survey line direction with the smallest structural change.

[0070] 3) Based on the formation background energy body construction of principal component analysis, the target data matrix D is regarded as the sum of two matrices (A+E), and the A matrix is ​​regarded as the reconstructed data. When reconstructing each data, the data is first flattened based on the interpreted structural layer, and the cross-correlation value between the data and the adjacent N data is calculated. The data with the maximum cross-correlation value and the minimum seismic data energy is taken as the reconstructed data of the data. Finally, the data is reversely flattened to restore the original structural form. All seismic data in the data are reconstructed in turn.

[0071] 4) Based on the original seismic data, the formation background energy field is removed. For the original seismic data D and the formation background energy field data A, the E=DA operation is implemented to remove the formation background energy field from the original seismic data and obtain the formation heterogeneity data E.

[0072] 5) Based on the original calibration results, complete the matching analysis of reservoir phenomena such as drilling emptying, leakage, abnormal logging gas measurement values, and abnormal drilling time with the heterogeneity data E.

[0073] The invention was applied in a three-dimensional work area in the Tarim Basin, and had a significant effect on the characteristics of heterogeneous fractures and caves and reservoirs formed by strike-slip faulting. The fault-reservoir space matching characteristics matched the drilling results, improving the accuracy of seismic characterization of heterogeneous geological bodies. Figure 2 The background energy fields reconstructed for different modeling intensities show that the greater the modeling intensity, the more continuous the separated background energy field is, and the less heterogeneous fracture-cavity information it contains;

[0074] Figure 3 The heterogeneous energy fields corresponding to different modeling intensities. It can be seen that the greater the modeling intensity, the clearer the fracture-cavity information in the heterogeneous data, which is more conducive to identification.

[0075] Figure 4 and Figure 5 are respectively the RMS attribute plane diagrams of the target stratum obtained based on the original seismic data of a certain area and the heterogeneous characteristic data of the present invention, and are Figure 5 From the target layer stratigraphic slices processed by this system, it can be seen that the characteristics of heterogeneous fractures and caves and reservoirs formed by strike-slip faulting are significantly enhanced, which improves the recognition accuracy of small-scale fractures and caves.

[0076] The present invention also discloses an effective earthquake identification system for underground small-scale fractures and caves, comprising:

[0077] Data acquisition module, used to obtain seismic data and drilling data of a certain work area;

[0078] The calibration module is used to carry out fine calibration of seismic data and drilling data and obtain calibration results;

[0079] The continuous tracking interpretation module is used to carry out continuous tracking interpretation of the event axes of the top and bottom surfaces of the target layer according to the calibration results, and obtain the structural horizons of the top and bottom surfaces of the target layer; and obtain the original seismic data between the top and bottom surface horizons of the target layer according to the structural horizons of the top and bottom surfaces of the target layer;

[0080] The preprocessing module is used to filter the original seismic data between the top and bottom layers of the target layer, complete the filtering processing of the vertical hour window and the horizontal small range, obtain the target data, and determine the seismic reflection characteristics of the target layer according to the target data;

[0081] The formation background energy volume field building module is used to regard the target data as two parts of data based on the seismic reflection characteristics, including the formation background energy field data and the formation heterogeneity data;

[0082] A formation background energy field removal module is used to remove formation background energy field data from target data to obtain formation heterogeneity data;

[0083] An analysis module is used to obtain an energy anomaly phenomenon of the formation heterogeneity data based on the calibration results and the formation heterogeneity data; and to determine whether the energy anomaly phenomenon of the formation heterogeneity data matches one or more of the phenomena indicating the reservoir;

[0084] If not, the vertical small window and the horizontal small range in the preprocessing module are adjusted until at least one of the reservoir phenomena indicated by the energy anomaly of the formation heterogeneity data matches.

[0085] The present invention also discloses a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the underground small-scale fracture-cavity body seismic effective identification method are implemented, wherein the memory may include a memory, such as a high-speed random access memory, and may also include a non-volatile memory, such as at least one disk memory, etc. The processor, the network interface, and the memory are interconnected through an internal bus, and the internal bus may be an industrial standard architecture bus, a peripheral component interconnection standard bus, an extended industrial standard architecture bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. The memory is used to store programs. Specifically, the program may include a program code, and the program code includes computer operation instructions. The memory may include a memory and a non-volatile memory, and provide instructions and data to the processor.

[0086] The present invention also discloses a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the underground small-scale fracture-cavity body earthquake effective identification method are implemented. Specifically, the computer-readable storage medium includes, but is not limited to, for example, a volatile memory and / or a non-volatile memory. The volatile memory may include a random access memory (RAM) and / or a cache memory (cache), etc. The non-volatile memory may include a read-only memory (ROM), a hard disk, a flash memory, an optical disk, a magnetic disk, etc.

[0087] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, ordinary technicians in the relevant field should understand that the specific implementation methods of the present invention can still be modified or replaced by equivalents. Any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. An effective method for identifying small-scale underground fracture-cavity earthquakes, characterized in that: The following steps are involved: 1) Obtain seismic data and drilling data of a certain work area, carry out fine calibration of seismic data and drilling data, and obtain calibration results; According to the calibration results, continuous tracking and interpretation of the top and bottom phase axes of the target layer are carried out to obtain the structural horizons of the top and bottom surfaces of the target layer; According to the structural layers of the top and bottom surfaces of the target layer, original seismic data between the top and bottom surfaces of the target layer are obtained; 2) Filter the original seismic data between the top and bottom layers of the target layer, complete the vertical small window and horizontal small range filtering, obtain the target data, and determine the seismic reflection characteristics of the target layer based on the target data; 3) Based on the seismic reflection characteristics, the target data is considered to consist of two parts of data, including formation background energy field data and formation heterogeneity data; 4) Removing the formation background energy field data from the target data to obtain formation heterogeneity data; 5) Based on the calibration results and formation heterogeneity data, the energy anomaly of the formation heterogeneity data is obtained; Determine whether the energy anomaly phenomenon of formation heterogeneity data matches one or more of the phenomena indicative of reservoirs; If not, return to step 2) to adjust the vertical hour window and the horizontal small range, and repeat steps 2) to 5) until the energy anomaly phenomenon of the formation heterogeneity data matches at least one of the phenomena indicating the reservoir.

2. The effective seismic identification method of underground small-scale fractures and caves according to claim 1 is characterized in that: In step 2), if the longitudinal hour window is less than 5 sampling points and the sampling rate is greater than 4ms or 5m, resampling is required, and the resampling rate is 1ms or 2m; The lateral small range is less than 9 adjacent seismic traces. If the lateral structural changes are drastic, the analysis is conducted along the survey line with the smallest structural change.

3. The effective seismic identification method of underground small-scale fractures and caves according to claim 1 is characterized in that: In step 2), the seismic reflection characteristics include background reflection characteristics and inhomogeneous reflection characteristics.

4. The effective seismic identification method of underground small-scale fractures and caves according to claim 3 is characterized in that: Background reflection features include continuous wave crest reflection and continuous wave valley reflection; The inhomogeneous reflection characteristics include strong energy reflection and chaotic reflection intertwined with multiple peaks and troughs.

5. The effective seismic identification method of underground small-scale fractures and caves according to claim 1 is characterized in that: In step 3), the target data is regarded as the addition of two matrices, the target data is called matrix D, and the two matrices are named A and E respectively; the A matrix corresponds to the formation background energy field data, and the E matrix corresponds to the formation heterogeneity data; The A matrix is ​​reconstructed using the maximum cross-correlation analysis method, specifically: First, the target data is flattened based on a certain structural layer to obtain layer flattened data; When reconstructing each data trace, the cross-correlation value between the trace and several adjacent traces in the layer-leveled data is calculated, and the trace with the maximum cross-correlation value and the minimum seismic trace energy is taken as the layer-leveled reconstructed data of the trace; All seismic traces in the layer-leveling data are reconstructed in sequence to obtain the layer-leveling stratigraphic background energy field data; The flattened stratum background energy field data is reverse-flattened to restore the original structural layer to the original structural form, thereby obtaining the stratum background energy field data of the target data; In order to deal with the smoothness between the reconstructed traces, the average of adjacent traces is taken before deflating.

6. The effective seismic identification method of underground small-scale fractures and caves according to claim 5 is characterized in that: Step 4) is specifically as follows: for the target data and the formation background energy field data, E=DA operation is performed to remove the formation background energy field data from the target data to obtain formation heterogeneity data.

7. The effective seismic identification method of underground small-scale fractures and caves according to claim 1 is characterized in that: In step 5), the phenomena indicating the reservoir include drilling emptying, leakage, abnormal logging gas measurement value or abnormal drilling time.

8. An effective earthquake identification system for underground small-scale fractures and caves, characterized in that: include: Data acquisition module, used to obtain seismic data and drilling data of a certain work area; The calibration module is used to carry out fine calibration of seismic data and drilling data and obtain calibration results; The continuous tracking interpretation module is used to carry out continuous tracking interpretation of the event axes of the top and bottom surfaces of the target layer according to the calibration results to obtain the structural horizons of the top and bottom surfaces of the target layer; According to the structural layers of the top and bottom surfaces of the target layer, original seismic data between the top and bottom surfaces of the target layer are obtained; The preprocessing module is used to filter the original seismic data between the top and bottom layers of the target layer, complete the filtering processing of the vertical hour window and the horizontal small range, obtain the target data, and determine the seismic reflection characteristics of the target layer according to the target data; The formation background energy volume field building module is used to regard the target data as two parts of data based on the seismic reflection characteristics, including the formation background energy field data and the formation heterogeneity data; A formation background energy field removal module is used to remove formation background energy field data from target data to obtain formation heterogeneity data; An analysis module, used for obtaining energy anomalies of formation heterogeneity data based on the calibration results and formation heterogeneity data; Determine whether the energy anomaly phenomenon of formation heterogeneity data matches one or more of the phenomena indicative of reservoirs; If not, the vertical small window and the horizontal small range in the preprocessing module are adjusted until at least one of the reservoir phenomena indicated by the energy anomaly of the formation heterogeneity data matches.

9. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the method for effectively identifying small-scale underground fractures and caves according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, the steps of the method for effectively identifying small-scale underground fractures and caves according to any one of claims 1 to 7 are implemented.

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