Buried hill reservoir multi-scale fracture zone prediction method, device, medium and equipment

Abstract

The present application relates to a kind of buried hill reservoir's multiscale fracture zone prediction method, device, medium and equipment, utilize Gaussian curvature attribute to predict macro scale buried hill weathering fracture dominant enrichment area, utilize f-k transform technique to depict buried hill inside high angle fracture, predict large scale structural fracture enrichment area, utilize ant body attribute to predict buried hill mesoscale fracture zone enrichment area, based on wavelet transform technique, extract the low frequency and high frequency components of three scale fracture zone prediction attributes of curvature attribute, f-k transform attribute, ant body attribute, design low frequency end and high frequency end fusion rule, realize the fusion of three scale fracture zone prediction attributes.The method of the present application can comprehensively represent the development characteristics of buried hill multiscale fracture network, and then guide reserves production and well pattern design.

Description

Technical Field

[0001] This invention relates to the field of buried hill oil and gas field development technology in the Bohai Sea, specifically to a method, apparatus, medium and equipment for predicting multi-scale fracture zones in buried hill reservoirs. Background Technology

[0002] The degree of fracture development is the most important factor controlling the quality of buried hill reservoirs. Buried hills contain fracture systems of different scales, ranging from microfractures to faults. These fractures couple to form a fracture network system, affecting reservoir quality and connectivity. Fracture prediction results have a significant impact on reserve development and well placement in buried hill oil and gas fields. However, existing fracture prediction methods mainly describe single-scale fracture zones and cannot describe the overall planar distribution of multi-scale fracture zones in buried hills. This results in significant uncertainty in using single-scale fracture zone prediction results to guide reserve development and well placement. Summary of the Invention

[0003] The purpose of this invention is to provide a multi-scale fracture zone prediction method, device, medium and equipment for buried hill reservoirs, so as to solve the problem that there is a large uncertainty in the existing technology of using single-scale fracture zone prediction results to guide reserve utilization and well location deployment.

[0004] To achieve the above objectives, the present invention adopts the following technical solution:

[0005] This invention provides a multi-scale fracture zone prediction method for buried hill reservoirs, comprising:

[0006] The temporal stratigraphy of the buried hill top is precisely tracked and interpreted to form a time grid. The Gaussian curvature attribute of the time grid is extracted as the prediction result of the dominant enrichment area of ​​the weathering fracture in the buried hill at the macro scale of the oilfield.

[0007] The FK transform technique was used to characterize the high-angle fractures inside the buried hill, and the amplitude slices along the layer of the FK transform properties were extracted as the prediction results of the large-scale structural fracture enrichment area in the oilfield.

[0008] Using the direction and angle of fault development in the oilfield area as constraints, we trace and interpret micro-fractures from the original seismic data using ant-body attributes, and extract the layer-by-layer amplitude slices of ant-body attributes as the prediction results of mesoscale fault zones in buried hills of the oilfield.

[0009] The extracted Gaussian curvature attribute, FK transform attribute, and ant body attribute were decomposed into low-frequency and high-frequency components using wavelet transform technology. The decomposed low-frequency and high-frequency components were fused according to the fusion rule. The fusion result of the three attributes was obtained by wavelet inverse transform and used as the comprehensive prediction result of multi-scale fracture zone in buried hill of oilfield.

[0010] Furthermore, it also includes a method for processing values ​​in the Gaussian curvature attribute that are less than a threshold constant: A threshold processing formula is used to perform threshold processing on values ​​in the Gaussian curvature attribute that are less than a threshold constant. The threshold processing formula is as follows:

[0011] ;

[0012] Where A is the Gaussian curvature attribute after thresholding, C is the Gaussian curvature attribute before thresholding, and C0 is the designed threshold constant, which is obtained through actual seismic profile calibration.

[0013] Furthermore, it also includes a method for characterizing high-angle faults within buried hills using the FK transform technique: the original seismic data is transformed to the FK domain using the FK transform technique, non-high-angle reflection signals are suppressed in the FK domain, and the result of the suppressed non-high-angle reflection signals is transformed back to the spatiotemporal domain using the inverse FK transform technique to obtain the high-angle fault characterization data volume.

[0014] Furthermore, it also includes a method for suppressing non-high-angle reflection signals: Non-high-angle reflection signals exhibit a difference in distribution area compared to high-angle reflection signals in the fk domain. The signal suppression formula is used to suppress signals outside the distribution area of ​​high-angle reflection signals in the fk domain, thereby suppressing the non-high-angle reflection signals. The signal suppression formula is:

[0015] ;

[0016] Where B represents the result after suppressing non-high-angle reflection signals in the fk domain, C represents the result of transforming the original seismic data to the fk domain, and I represents the distribution area of ​​high-angle signals after transformation to the fk domain.

[0017] Furthermore, it also includes a method for designing fusion rules for multiple low-frequency components: low-frequency subband fusion rules are designed based on the Laplace energy formula, and these rules can be expressed as:

[0018] ;

[0019] in This represents the fusion result of the low-frequency subband coefficients at sample point (i, j). This represents the sum of the Laplace energies of the k-th attribute. This represents the low-frequency subband coefficient of the k-th attribute at sample point (i, j).

[0020] Furthermore, it also includes a fusion rule design method for multiple high-frequency components: a high-frequency subband fusion rule is designed based on the root mean square energy configuration of the attribute high-frequency subband coefficients and the high-frequency subband fusion weight calculation formula. The high-frequency subband fusion rule can be expressed as:

[0021] ;

[0022] ;

[0023] ;

[0024] in, , , These represent the high-frequency subband fusion results at sample point (i, j) in the horizontal, vertical, and diagonal directions, respectively. This represents the high-frequency subband fusion weight of the k-th attribute at sample point (i, j) along a specific direction n. Let be the high-frequency subband coefficient of the k-th attribute at sample point (i, j) along a specific direction n, where n represents one of the three directions: horizontal h, vertical v, or diagonal d.

[0025] Based on the above-mentioned multi-scale fracture zone prediction method for buried hill reservoirs, this invention also provides an analysis apparatus for the method, comprising:

[0026] The first processing unit is used to finely track and interpret the temporal strata on the top of the buried hill, form a time grid, and extract the Gaussian curvature attribute of the time grid as the prediction result of the dominant enrichment area of ​​the weathering fracture in the buried hill at the macro scale of the oilfield.

[0027] The second processing unit is used to characterize the high-angle fractures inside the buried hill using the FK transform technology, and extract the amplitude slices along the layer of the FK transform attributes as the prediction results of the large-scale structural fracture enrichment area in the oilfield.

[0028] The third processing unit is used to track and interpret micro-fractures from the original seismic data using the direction and angle of fracture development in the oilfield area as constraints, and extract the ant body attributes along the layer amplitude slices as the prediction results of the mesoscale fault zone in the buried hill of the oilfield.

[0029] The fourth processing unit is used to decompose the extracted Gaussian curvature attribute, FK transform attribute, and ant body attribute into low-frequency and high-frequency components using wavelet transform technology. The decomposed low-frequency and high-frequency components are fused according to the fusion rules, and the fusion result of the three attributes is obtained by inverse wavelet transform, which serves as the comprehensive prediction result of multi-scale fracture zones in buried hills of oilfields.

[0030] Based on the above-described method for predicting multi-scale fracture zones in buried hill reservoirs, this invention also provides a computer-readable storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described method for predicting multi-scale fracture zones in buried hill reservoirs.

[0031] Based on the above-described method for predicting multi-scale fracture zones in buried hill reservoirs, this invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The device is characterized in that the processor executes the computer program to implement the steps of the above-described method for predicting multi-scale fracture zones in buried hill reservoirs.

[0032] The present invention, by adopting the above technical solution, has the following beneficial effects:

[0033] This invention utilizes Gaussian curvature properties to predict macroscopic weathering fracture enrichment areas in buried hills, employs FK transform technology to characterize high-angle fractures within buried hills to predict large-scale tectonic fracture enrichment areas, and utilizes ant-body properties to predict mesoscale fracture zone enrichment areas in buried hills. Based on wavelet transform technology, it extracts the low-frequency and high-frequency components of the fracture zone prediction attributes at three scales: curvature properties, FK transform properties, and ant-body properties. It designs fusion rules for the low-frequency and high-frequency ends to achieve the fusion of fracture zone prediction attributes at three scales, thereby comprehensively characterizing the multi-scale fracture network development characteristics of buried hills and guiding reserve utilization and well pattern design. Attached Figure Description

[0034] Various other advantages and benefits will become apparent to those skilled in the art upon reading the following detailed description of preferred embodiments. The accompanying drawings are for illustrative purposes only and are not intended to limit the invention. Throughout the drawings, the same reference numerals denote the same parts. In the drawings:

[0035] Figure 1 This is a schematic block diagram illustrating the steps of a multi-scale fracture zone prediction method for buried hill reservoirs provided in an embodiment of the present invention;

[0036] Figure 2 This is a data demonstration diagram of the Gaussian curvature attribute of a multi-scale fracture zone prediction method for buried hill reservoirs provided in an embodiment of the present invention;

[0037] Figure 3 This is a data demonstration diagram of the fk transform properties of a multi-scale fracture zone prediction method for buried hill reservoirs provided in an embodiment of the present invention;

[0038] Figure 4 This is a data demonstration diagram of the ant body attributes of a multi-scale fracture zone prediction method for buried hill reservoirs provided in an embodiment of the present invention;

[0039] Figure 5 This is a data demonstration diagram illustrating a multi-scale fracture zone prediction method for buried hill reservoirs provided in this embodiment of the invention, which utilizes wavelet transform attribute fusion to obtain a comprehensive prediction of multi-scale fracture zones. Detailed Implementation

[0040] Exemplary embodiments of the invention will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided to enable a more thorough understanding of the invention and to fully convey the scope of the invention to those skilled in the art.

[0041] Traditional methods for predicting fracture zones using a single scale have significant uncertainties in guiding reserve development and well placement. This invention provides a multi-scale fracture zone prediction method, apparatus, medium, and equipment for buried hill reservoirs. It utilizes Gaussian curvature properties to predict macro-scale weathering fracture enrichment zones in buried hills, employs FK transform technology to characterize high-angle fractures within the buried hill to predict large-scale tectonic fracture enrichment zones, and utilizes ant-body properties to predict meso-scale fracture zone enrichment zones. Based on wavelet transform technology, it extracts the low-frequency and high-frequency components of the three scale fracture zone prediction attributes (curvature, FK transform, and ant-body properties), and fuses these three scale attributes to comprehensively characterize the multi-scale fracture network development characteristics of buried hills, thereby guiding reserve development and well pattern design.

[0042] The present invention will be described in detail below through embodiments.

[0043] Example

[0044] like Figure 1 As shown, this invention provides a multi-scale fracture zone prediction method for buried hill reservoirs, comprising:

[0045] The temporal stratigraphy of the buried hill top is precisely tracked and interpreted to form a time grid. The Gaussian curvature attribute of the time grid is extracted as the prediction result of the dominant enrichment area of ​​the weathering fracture in the buried hill at the macro scale of the oilfield.

[0046] The FK transform technique was used to characterize the high-angle fractures inside the buried hill, and the amplitude slices along the layer of the FK transform properties were extracted as the prediction results of the large-scale structural fracture enrichment area in the oilfield.

[0047] Using the direction and angle of fault development in the oilfield area as constraints, we trace and interpret micro-fractures from the original seismic data using ant-body attributes, and extract the layer-by-layer amplitude slices of ant-body attributes as the prediction results of mesoscale fault zones in buried hills of the oilfield.

[0048] The extracted Gaussian curvature attribute, FK transform attribute, and ant body attribute were decomposed into low-frequency and high-frequency components using wavelet transform technology. The decomposed low-frequency and high-frequency components were fused according to the fusion rule. The fusion result of the three attributes was obtained by wavelet inverse transform and used as the comprehensive prediction result of multi-scale fracture zone in buried hill of oilfield.

[0049] Among them, based on the automatic tracking algorithm, the time strata of the buried mountain top of the oilfield can be accurately tracked and interpreted, and a time grid is formed with a grid parameter of 30x30 to ensure that the time grid accuracy is high enough, so as to be able to depict the undulating shape of the buried mountain top.

[0050] Furthermore, when extracting the Gaussian curvature attribute of the time grid as the prediction result of the dominant enrichment area of ​​the buried hill weathering fracture at the macro scale of the oilfield, it is necessary to process the values ​​of the Gaussian curvature attribute that are less than the threshold constant. The processing method includes: applying a threshold processing formula to the values ​​of the Gaussian curvature attribute that are less than the threshold constant. The threshold processing formula is as follows:

[0051] ;

[0052] Where A is the Gaussian curvature attribute after thresholding, C is the Gaussian curvature attribute before thresholding, and C0 is the designed threshold constant, which is obtained through actual seismic profile calibration.

[0053] Furthermore, the multi-scale fracture zone prediction method for buried hill reservoirs of the present invention also includes a method for characterizing high-angle fractures within the buried hill using the fk transform technique. Specifically, the original seismic data is transformed to the fk domain using the fk transform technique, non-high-angle reflection signals are suppressed in the fk domain, and the result of the suppressed non-high-angle reflection signals is transformed back to the spatiotemporal domain using the inverse fk transform technique to obtain the high-angle fracture characterization data volume.

[0054] As described above, the method for suppressing non-high-angle reflected signals includes: Non-high-angle reflected signals exhibit a difference in distribution area compared to high-angle reflected signals in the fk domain; the signal suppression formula is used to suppress signals outside the distribution area of ​​high-angle reflected signals in the fk domain, thereby suppressing the non-high-angle reflected signals. The signal suppression formula is:

[0055] ;

[0056] Where B represents the result after suppressing non-high-angle reflection signals in the fk domain, C represents the result of transforming the original seismic data to the fk domain, and I represents the distribution area of ​​high-angle signals after transformation to the fk domain.

[0057] Furthermore, wavelet transform technology is used to decompose the extracted Gaussian curvature attribute, FK transform attribute, and ant body attribute into low-frequency and high-frequency components, respectively. Specifically, short-time Fourier transform can be used to obtain the low-frequency and high-frequency subbands of the three attributes.

[0058] As mentioned above, low-frequency subbands reflect the overall characteristics of the properties. The multi-scale fracture zone prediction method for buried hill reservoirs in this invention also includes a method for designing fusion rules for multiple low-frequency components. Specifically, it involves designing low-frequency subband fusion rules based on the Laplace energy formula. These low-frequency subband fusion rules can be expressed as:

[0059] ;

[0060] in This represents the fusion result of the low-frequency subband coefficients at sample point (i, j). This represents the sum of the Laplace energies of the k-th attribute. This represents the low-frequency subband coefficient of the k-th attribute at sample point (i, j).

[0061] The formula for calculating the Laplace energy is as follows:

[0062] ;

[0063] in, This represents the Laplace energy of the k-th attribute at sample point (i, j). This represents the low-frequency subband coefficient of the k-th attribute at sample point (i, j); This represents the distance the window has been shifted.

[0064] Furthermore, high-frequency subbands primarily reflect the details and edge features of attributes. Based on the root-mean-square energy of the attribute high-frequency subband coefficients, high-frequency subband fusion rules are designed separately. Overall, high-frequency subband coefficients with larger root-mean-square energy are assigned larger fusion weights to enhance the preservation of attribute edge features and detailed information during the fusion process. The multi-scale fracture zone prediction method for buried hill reservoirs in this invention also includes a fusion rule design method for multiple high-frequency components. Specifically, it designs high-frequency subband fusion rules based on the root-mean-square energy of the attribute high-frequency subband coefficients and the high-frequency subband fusion weight calculation formula. The high-frequency subband fusion rules can be expressed as:

[0065] ;

[0066] ;

[0067] ;

[0068] in, , , These represent the high-frequency subband fusion results at sample point (i, j) in the horizontal, vertical, and diagonal directions, respectively. This represents the high-frequency subband fusion weight of the k-th attribute at sample point (i, j) along a specific direction n. Let be the high-frequency subband coefficient of the k-th attribute at sample point (i, j) along a specific direction n, where n represents one of the three directions: horizontal h, vertical v, or diagonal d.

[0069] The formula for calculating the high-frequency subband fusion weight is as follows:

[0070] ;

[0071] in, This represents the high-frequency subband fusion weight of the k-th attribute at sample point (i, j) along a specific direction n. Let be the high-frequency subband coefficient of the k-th attribute at sample point (i, j) along a specific direction n, where n represents one of the three directions: horizontal h, vertical v, or diagonal d.

[0072] This invention utilizes Gaussian curvature properties to predict macroscopic weathering fracture enrichment areas in buried hills, employs FK transform technology to characterize high-angle fractures within buried hills to predict large-scale tectonic fracture enrichment areas, and utilizes ant-body properties to predict mesoscale fracture zone enrichment areas in buried hills. Based on wavelet transform technology, it extracts the low-frequency and high-frequency components of the fracture zone prediction attributes at three scales: curvature properties, FK transform properties, and ant-body properties. It designs fusion rules for the low-frequency and high-frequency ends to achieve the fusion of fracture zone prediction attributes at three scales, thereby comprehensively characterizing the multi-scale fracture network development characteristics of buried hills and guiding reserve utilization and well pattern design.

[0073] As described above, taking the Archean buried hill reservoir of Bohai A oilfield as an example, the multi-scale fracture zone prediction method of the buried hill reservoir of this invention is used to achieve multi-scale fracture zone prediction. The specific steps are as follows:

[0074] 1. Utilizing an automatic tracking algorithm, the temporal stratigraphy of the buried mountain summit in Oilfield A is precisely tracked and interpreted. A 30x30 grid is used to form a time grid, ensuring sufficient accuracy to characterize the undulating morphology of the buried mountain summit. The Gaussian curvature attribute of the time grid is extracted, and excessively small values ​​are thresholded. For example... Figure 2 As shown, the curvature attribute after the threshold is used as the prediction result of the dominant enrichment area of ​​the buried hill weathering fracture in oilfield A at the macro scale.

[0075] 2. Research indicates that the development of structural fractures in the Archean buried hill reservoirs of the Bohai Sea is mainly controlled by high-angle faults within the buried hills. These high-angle faults exhibit steep, linear reflection characteristics on seismic profiles. The FK transform technique was used to characterize these high-angle faults within the buried hills from the original seismic data of Oilfield A, and further, layer-by-layer amplitude slices along the time grid of the buried hill summit were extracted from the FK transform data volume. For example... Figure 3 As shown, this is the prediction result of the large-scale tectonic fracture enrichment zone in oilfield A;

[0076] 3. Using the near-east-west trend of fault development in the A oilfield area and the dip angle of high-angle faults ranging from approximately 40 to 75 degrees as constraints, the ant-body tracking attribute is used to trace and interpret micro-fractures from the original seismic data. Further, the ant-body attribute is extracted as a slice of the layer-by-layer amplitude along the time grid of the buried hilltop. For example... Figure 4 As shown, this is the prediction result of the mesoscale fault zone in the buried hill of Oilfield A;

[0077] 4. Using wavelet transform, the curvature attribute, FK transform attribute, and ant body attribute are decomposed into low-frequency and high-frequency components. The wavelet used is the short-time Fourier wavelet. The low-frequency components of the three attributes mainly reflect the main contour information of the three attributes, while the high-frequency components include high-frequency components in the horizontal direction, vertical direction, and diagonal direction. Fusion rules for the low-frequency and high-frequency components are designed separately, and these rules are used to fuse the low-frequency and high-frequency components respectively. Finally, the fused result of the three attributes is obtained through inverse wavelet transform. Figure 5 As shown, this is the comprehensive prediction result of the multi-scale fracture network of the buried hill in Oilfield A.

[0078] Based on the above-mentioned multi-scale fracture zone prediction method for buried hill reservoirs, this invention also provides an analysis apparatus for the method, comprising:

[0079] The first processing unit is used to finely track and interpret the temporal strata on the top of the buried hill, form a time grid, and extract the Gaussian curvature attribute of the time grid as the prediction result of the dominant enrichment area of ​​the weathering fracture in the buried hill at the macro scale of the oilfield.

[0080] The second processing unit is used to characterize the high-angle fractures inside the buried hill using the FK transform technology, and extract the amplitude slices along the layer of the FK transform attributes as the prediction results of the large-scale structural fracture enrichment area in the oilfield.

[0081] The third processing unit is used to track and interpret micro-fractures from the original seismic data using the direction and angle of fracture development in the oilfield area as constraints, and extract the ant body attributes along the layer amplitude slices as the prediction results of the mesoscale fault zone in the buried hill of the oilfield.

[0082] The fourth processing unit is used to decompose the extracted Gaussian curvature attribute, FK transform attribute, and ant body attribute into low-frequency and high-frequency components using wavelet transform technology. The decomposed low-frequency and high-frequency components are fused according to the fusion rules, and the fusion result of the three attributes is obtained by inverse wavelet transform, which serves as the comprehensive prediction result of multi-scale fracture zones in buried hills of oilfields.

[0083] Based on the above-described method for predicting multi-scale fracture zones in buried hill reservoirs, this invention also provides a computer-readable storage medium storing a computer program thereon, wherein the computer program, when executed by a processor, implements the steps of the above-described method for predicting multi-scale fracture zones in buried hill reservoirs.

[0084] Based on the above-described method for predicting multi-scale fracture zones in buried hill reservoirs, this invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. The device is characterized in that the processor executes the computer program to implement the steps of the above-described method for predicting multi-scale fracture zones in buried hill reservoirs.

[0085] This invention is described based on flowcharts and / or block diagrams of methods, apparatus (systems), and computer program products according to specific embodiments. It should be understood that each block of the flowcharts and / or block diagrams, and combinations of blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing device, generate instructions for implementing the flowcharts and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0086] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0087] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0088] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A multi-scale fracture zone prediction method for buried hill reservoirs, characterized in that, The multi-scale fracture zone prediction method includes: Step 1: Finely track and interpret the temporal strata on the top of the buried hill to form a time grid, and extract the Gaussian curvature attribute of the time grid as the prediction result of the dominant enrichment area of ​​the weathering fracture in the buried hill at the macro scale of the oilfield; When using the extracted Gaussian curvature attribute of the time grid as the prediction result of the dominant enrichment area of ​​the buried hill weathering fracture at the macro scale of the oilfield, it is necessary to process the values ​​of the Gaussian curvature attribute that are less than a threshold constant. The processing method includes: applying a threshold processing formula to process the values ​​of the Gaussian curvature attribute that are less than a threshold constant. The threshold processing formula is as follows: Where A is the Gaussian curvature attribute after thresholding, C is the Gaussian curvature attribute before thresholding, and C0 is the designed threshold constant, which is obtained through actual seismic profile calibration. Step 2: Use the FK transform technique to characterize the high-angle fractures inside the buried hill, and extract the amplitude slices along the layer of the FK transform attributes as the prediction results of the large-scale structural fracture enrichment area in the oilfield. The method for characterizing high-angle faults inside buried hills using the fk transform technique involves: transforming the original seismic data to the fk domain using the fk transform technique; suppressing non-high-angle reflection signals in the fk domain; and then transforming the result of the suppressed non-high-angle reflection signals to the spatiotemporal domain using the inverse fk transform technique to obtain the high-angle fault characterization data volume. The method for suppressing non-high-angle reflection signals is as follows: Non-high-angle reflection signals exhibit a difference in distribution area compared to high-angle reflection signals in the fk domain. The non-high-angle reflection signals are suppressed by using a signal suppression formula in the fk domain to suppress signals outside the distribution area of ​​high-angle reflection signals. The signal suppression formula is: In the formula, B is the result after suppressing non-high-angle reflection signals in the fk domain, C is the result of transforming the original seismic data to the fk domain, and I is the area where the high-angle signal is distributed after being transformed to the fk domain. Step 3: Using the direction and angle of fault development in the oilfield area as constraints, trace and interpret micro-fractures from the original seismic data using ant-body attributes, extract the along-layer amplitude slices of ant-body attributes, and use them as the prediction results of mesoscale fault zones in buried hills of the oilfield. Step 4: Using wavelet transform technology, the extracted Gaussian curvature attribute, FK transform attribute, and ant body attribute are decomposed into low-frequency and high-frequency components respectively. The multiple low-frequency and high-frequency components are fused according to the fusion rule, and the fusion result of the three attributes is obtained by wavelet inverse transform, which serves as the comprehensive prediction result of multi-scale fracture zone in buried hills of oilfields. Among them, the fusion rule design method for multiple low-frequency components adopts the design of low-frequency subband fusion rules based on the Laplace energy formula, and the low-frequency subband fusion rules can be expressed as: ； In the formula, This represents the fusion result of the low-frequency subband coefficients at sample point (i, j). This represents the sum of the Laplace energies of the k-th attribute. This represents the low-frequency subband coefficient of the k-th attribute at sample point (i, j); The method for designing fusion rules for multiple high-frequency components employs a formula for calculating the fusion weights of high-frequency subbands based on the root mean square energy configuration of attribute-based high-frequency subband coefficients. These high-frequency subband fusion rules can be expressed as follows: ； ； ； In the formula, , and These represent the high-frequency subband fusion results at sample point (i, j) in the horizontal, vertical, and diagonal directions, respectively. This represents the high-frequency subband fusion weight of the k-th attribute at sample point (i, j) along a specific direction n; Let be the high-frequency subband coefficient of the k-th attribute at sample point (i, j) along a specific direction n; n represents one of the three directions: horizontal (h), vertical (v), or diagonal (d).

2. A multi-scale fracture zone prediction device for buried hill reservoirs, characterized in that, include The first processing unit is used to finely track and interpret the temporal strata on the top of the buried hill, form a time grid, and extract the Gaussian curvature attribute of the time grid as the prediction result of the dominant enrichment area of ​​the weathering fracture in the buried hill at the macro scale of the oilfield. When using the extracted Gaussian curvature attribute of the time grid as the prediction result of the dominant enrichment area of ​​the buried hill weathering fracture at the macro scale of the oilfield, it is necessary to process the values ​​of the Gaussian curvature attribute that are less than a threshold constant. The processing method includes: applying a threshold processing formula to process the values ​​of the Gaussian curvature attribute that are less than a threshold constant. The threshold processing formula is as follows: Where A is the Gaussian curvature attribute after thresholding, C is the Gaussian curvature attribute before thresholding, and C0 is the designed threshold constant, which is obtained through actual seismic profile calibration. The second processing unit is used to characterize the high-angle fractures inside the buried hill using the FK transform technology, and extract the amplitude slices along the layer of the FK transform attributes as the prediction results of the large-scale structural fracture enrichment area in the oilfield. The method for characterizing high-angle faults inside buried hills using the fk transform technique involves: transforming the original seismic data to the fk domain using the fk transform technique; suppressing non-high-angle reflection signals in the fk domain; and then transforming the result of the suppressed non-high-angle reflection signals to the spatiotemporal domain using the inverse fk transform technique to obtain the high-angle fault characterization data volume. The method for suppressing non-high-angle reflection signals is as follows: Non-high-angle reflection signals exhibit a difference in distribution area compared to high-angle reflection signals in the fk domain. The non-high-angle reflection signals are suppressed by using a signal suppression formula in the fk domain to suppress signals outside the distribution area of ​​high-angle reflection signals. The signal suppression formula is: In the formula, B is the result after suppressing non-high-angle reflection signals in the fk domain, C is the result of transforming the original seismic data to the fk domain, and I is the area where the high-angle signal is distributed after being transformed to the fk domain. The third processing unit is used to track and interpret micro-fractures from the original seismic data using the direction and angle of fracture development in the oilfield area as constraints, and extract the ant body attributes along the layer amplitude slices as the prediction results of the mesoscale fault zone in the buried hill of the oilfield. The fourth processing unit is used to decompose the extracted Gaussian curvature attribute, FK transform attribute, and ant body attribute into low-frequency and high-frequency components using wavelet transform technology. The decomposed low-frequency and high-frequency components are fused according to the fusion rules, and the fusion result of the three attributes is obtained by wavelet inverse transform, which serves as the comprehensive prediction result of multi-scale fracture zone in oilfield buried hill. Among them, the fusion rule design method for multiple low-frequency components adopts the design of low-frequency subband fusion rules based on the Laplace energy formula, and the low-frequency subband fusion rules can be expressed as: ； In the formula, This represents the fusion result of the low-frequency subband coefficients at sample point (i, j). This represents the sum of the Laplace energies of the k-th attribute. This represents the low-frequency subband coefficient of the k-th attribute at sample point (i, j); The method for designing fusion rules for multiple high-frequency components employs a formula for calculating the fusion weights of high-frequency subbands based on the root mean square energy configuration of attribute-based high-frequency subband coefficients. These high-frequency subband fusion rules can be expressed as follows: ； ； ； In the formula, , and These represent the high-frequency subband fusion results at sample point (i, j) in the horizontal, vertical, and diagonal directions, respectively. This represents the high-frequency subband fusion weight of the k-th attribute at sample point (i, j) along a specific direction n; Let be the high-frequency subband coefficient of the k-th attribute at sample point (i, j) along a specific direction n; n represents one of the three directions: horizontal (h), vertical (v), or diagonal (d).

3. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method of claim 1.

4. 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, it implements the steps of the method of claim 1.

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