Crack prediction method and device based on post-stack seismic orientation attribute difference

Abstract

The invention relates to a crack prediction method and device based on post-stack seismic orientation attribute difference, and the method comprises the steps: carrying out the guided filtering of original seismic data, and obtaining the filtering data; setting a plurality of azimuth angles, and respectively extracting a plurality of azimuth attribute data of the filtering data based on the plurality of azimuth angles; ellipse fitting is carried out on the multiple pieces of azimuth attribute data, and ellipse parameters are obtained; and fracture data are obtained through analysis according to the ellipse parameters. According to the method, the response characteristics of the crack can be captured from different directions, so that the distribution rule of the crack is more comprehensively described, and the crack prediction precision is remarkably improved.

Description

Technical Field

[0001] The present invention relates to the technical field of oil exploration, and particularly to a fracture prediction method and device based on the difference of post-stack seismic azimuth attributes. Background Art

[0002] There are usually two methods for fracture prediction based on seismic data. One method starts from wide-azimuth seismic gathers, and detects fractures by analyzing the differences of pre-stack reflection waves with different azimuth angles and different shot-receiver offsets, so as to obtain the density and direction of fractures; the other method starts from post-stack seismic data, and indirectly infers the existence and distribution of fractures by extracting and analyzing post-stack seismic data attributes.

[0003] The first method above can directly detect the information of underground fractures, providing direct data support for the prediction of fracture reservoirs. Its disadvantage is that there is little wide-azimuth seismic data and it cannot be carried out on a large scale; the second method predicts fractures by processing and analyzing post-stack data, reducing the requirement for data acquisition. Its advantages are simple operation and low cost, being suitable for large-scale application and promotion. However, its disadvantage is that there is no azimuth information of fractures and the calculation results are inaccurate.

[0004] In actual production research, there is little pre-stack wide-azimuth data, and fracture prediction is mostly carried out on post-stack seismic data. However, the existing post-stack methods, including post-stack attribute technologies such as coherence, curvature, ant body, and maximum likelihood, cannot meet the requirements of fine development of oilfields, and the prediction of fracture density and direction is inaccurate. Summary of the Invention

[0005] The present invention provides a fracture prediction method and device based on the difference of post-stack seismic azimuth attributes to solve the defects of the prior art.

[0006] The present invention provides a fracture prediction method based on the difference of post-stack seismic azimuth attributes, including: S1: Conduct guided filtering on the original seismic data to obtain filtered data; S2: Set multiple azimuth angles, and respectively extract multiple azimuth attribute data of the filtered data based on the multiple azimuth angles; S3: Conduct elliptical fitting on the multiple azimuth attribute data to obtain elliptical parameters; S4: Analyze and obtain fracture data according to the elliptical parameters.

[0007] According to the fracture prediction method based on the difference of post-stack seismic azimuth attributes provided by the present invention, the number of set azimuth angles in step S2 is greater than or equal to 3 and less than or equal to 6.

[0008] A fracture prediction method based on the difference in post-stack seismic azimuth attributes provided by the present invention. In step S2, the number of set azimuth angles is 3, and the set multiple azimuth angles include: The first azimuth angle, which is the 0° angle parallel to the seismic fault; The second azimuth angle, which is the 45° angle with the seismic fault; The third azimuth angle, which is the 90° angle perpendicular to the seismic fault.

[0009] A fracture prediction method based on the difference in post-stack seismic azimuth attributes provided by the present invention. The elliptical parameters in step S3 include: Elliptical flattening data, elliptical major axis data, and elliptical minor axis data.

[0010] A fracture prediction method based on the difference in post-stack seismic azimuth attributes provided by the present invention. The fracture data in step S4 includes: Fracture density data and fracture direction data.

[0011] A fracture prediction method based on the difference in post-stack seismic azimuth attributes provided by the present invention. The fracture density data is obtained by analyzing the elliptical flattening data, and the fracture direction data is obtained by analyzing the elliptical major axis data and the elliptical minor axis data.

[0012] A fracture prediction method based on the difference in post-stack seismic azimuth attributes provided by the present invention. Step S4 further includes: Drawing a fracture prediction map according to the fracture density data and the fracture direction data in the fracture data.

[0013] The second aspect of the present invention provides a fracture prediction device based on the difference in post-stack seismic azimuth attributes, including: Filtering module: used to perform directional filtering on the original seismic data to obtain filtered data; Extracting module: used to respectively extract multiple azimuth attribute data of the filtered data based on a set of multiple azimuth angles; Fitting module: used to perform elliptical fitting on multiple azimuth attribute data to obtain elliptical parameters; Analysis module: used to analyze and obtain fracture data according to the elliptical parameters.

[0014] The third aspect of the present invention provides a fracture prediction device based on the difference in post-stack seismic azimuth attributes, including: A memory and at least one processor, wherein instructions are stored in the memory; At least one of the processors invokes the instructions in the memory to cause a fracture prediction device based on the difference in post-stack seismic azimuth attributes to perform a fracture prediction method based on the difference in post-stack seismic azimuth attributes as described in any one of the above.

[0015] A fourth aspect of the present invention provides a computer-readable storage medium, on which instructions are stored, and when the instructions are executed by a processor, a fracture prediction method based on the difference in post-stack seismic azimuth attributes as described in any one of the above is implemented.

[0016] A fracture prediction method, device, equipment and medium based on the difference in post-stack seismic azimuth attributes provided by the present invention significantly improve the accuracy of fracture prediction through the fracture prediction method based on the difference in post-stack seismic azimuth attributes. Traditional seismic attribute analysis methods usually can only provide fracture information in a single dimension and are difficult to comprehensively reflect the development characteristics of fractures. However, by setting multiple azimuth angles and extracting the azimuth attributes of post-stack seismic data, the present invention can capture the response characteristics of fractures from different directions, thereby more comprehensively depicting the distribution law of fractures. In addition, the introduction of the ellipse fitting technology further improves the prediction accuracy. Ellipse fitting extracts ellipse parameters (flattening, major axis, minor axis) by mathematically modeling the seismic attribute data of multiple azimuth angles, and these parameters can quantify the density and direction characteristics of fractures. For example, the ellipse flattening directly reflects the development density of fractures, and the larger the flattening, the higher the fracture density; the major axis and minor axis of the ellipse indicate the main and secondary development directions of fractures. Through this quantitative analysis method, the present invention can more accurately predict the spatial distribution of fractures and provide a reliable basis for subsequent reservoir evaluation and development plan design.

[0017] The present invention has significant advantages in the ability to depict the development characteristics of fractures. Traditional methods usually rely on a single seismic attribute (such as amplitude, frequency, etc.) to describe fracture characteristics, but these attributes are often difficult to finely depict the density and direction of fractures. Through the extraction of multi-azimuth angle data, the present invention can obtain the response information of fractures from different directions, thereby more comprehensively reflecting the development characteristics of fractures. For example, by setting azimuth angles parallel, oblique and perpendicular to the seismic fault, the seismic response differences of fractures in different directions can be captured respectively. In addition, the application of the ellipse fitting technology further enhances the ability to depict fracture characteristics. The ellipse parameters can not only quantify the density and direction of fractures, but also reveal the geometric shape and spatial distribution law of fractures. For example, the direction of the major axis of the ellipse is usually consistent with the main development direction of fractures, while the minor axis direction reflects the secondary development direction of fractures. Through this multi-azimuth and multi-dimensional analysis method, the present invention can more finely depict the development characteristics of fractures and provide more comprehensive geological information for the exploration and development of fractured reservoirs.

[0018] The present invention significantly improves work efficiency and reduces exploration costs through an automated data processing and analysis process. Traditional seismic attribute analysis methods usually require a large amount of manual intervention, which is not only inefficient but also prone to introducing human errors. In contrast, the entire process of the present invention, from data filtering, attribute extraction to ellipse fitting and fracture analysis, realizes automated processing, reduces manual intervention, and improves work efficiency. For example, the guided filtering technology can automatically eliminate noise in seismic data and extract effective fracture response information; the ellipse fitting technology can automatically calculate ellipse parameters and generate fracture density and direction data. In addition, the present invention predicts fractures through seismic data, reduces the dependence on drilling and logging data, and thus reduces exploration costs. For example, in the initial stage of exploration, the fracture distribution can be quickly predicted through the method of the present invention, the drilling deployment plan can be optimized, and ineffective drilling can be reduced; in the development stage, the fracture prediction results can be used to optimize the fracturing design and improve the reservoir development efficiency. Through this efficient and low-cost analysis method, the present invention can provide strong technical support for oil and gas exploration and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0020] Figure 1 Schematic flow chart of a fracture prediction method based on post-stack seismic azimuth attribute differences provided by an embodiment of the present invention; Figure 2 Schematic structural diagram of a fracture prediction device based on post-stack seismic azimuth attribute differences provided by an embodiment of the present invention; Figure 3 Data schematic diagram of the post-stack seismic amplitude change rate of the 0-degree azimuth angle extracted from the oilfield fracture reservoir provided by an embodiment of the present invention; Figure 4 Data schematic diagram of the post-stack seismic amplitude change rate of the 45-degree azimuth angle extracted from the oilfield fracture reservoir provided by an embodiment of the present invention; Figure 5 Data schematic diagram of the post-stack seismic amplitude change rate of the 90-degree azimuth angle extracted from the oilfield fracture reservoir provided by an embodiment of the present invention; Figure 6 Data schematic diagram of the obtained planar fracture density provided by an embodiment of the present invention; Figure 7 Data schematic diagram of the obtained planar fracture direction provided by an embodiment of the present invention.

[0021] Reference numerals: 100, filtering module; 200, extraction module; 300, fitting module; 400, analysis module. Detailed implementation manners

[0022] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the present invention. Obviously, the described embodiments are some but not all of the embodiments of the present invention, and they should not be construed as limiting the present invention. Based on the embodiments in the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention. In the description of the present invention, it should be understood that the terms used are only for the purpose of description and cannot be construed as indicating or implying relative importance.

[0023] The embodiments of the present invention will be described below in conjunction with the drawings.

[0024] As Figure 1 shown, the present invention provides a fracture prediction method based on the difference in post-stack seismic azimuth attributes, including: S1: Perform guided filtering on the original seismic data to obtain filtered data.

[0025] The purpose of step S1 is to improve the quality of the original seismic data. Guided filtering can be implemented by software or hardware. It can retain important edge information while smoothing the image. In seismic data processing, guided filtering can effectively suppress random noise while retaining linear structural features such as faults and fractures. Through this preprocessing, the signal-to-noise ratio and accuracy of subsequent analysis can be improved.

[0026] Specifically, performing structural guided filtering on the seismic data can smooth the continuous regions parallel to the seismic event axis, improve the signal-to-noise ratio, and not smooth the information perpendicular to the seismic event axis direction, such as fractures and lithologic boundaries. While improving the signal-to-noise ratio, small-scale structural information is retained, and the fracture prediction accuracy is improved.

[0027] S2: Set multiple azimuth angles, and extract multiple azimuth attribute data of the filtered data based on the multiple azimuth angles respectively.

[0028] The purpose of step S2 is to extract the azimuth attributes of seismic data according to specific azimuth angles. The azimuth angle refers to the angle relative to the seismic fault or the main tectonic direction. The azimuth attribute reflects the characteristic differences shown by seismic waves when propagating in different directions. In a formation containing directional fractures, seismic waves will show different characteristics when propagating in different directions, and these differences can be identified and quantified through azimuth attribute analysis.

[0029] Further, the method for extracting post-stack azimuth seismic attribute data in step S2 is as follows: The post-stack seismic data contains the response information of fractures. Conventional attributes such as coherence, curvature, amplitude, and frequency are not sufficient to finely describe the development density and direction of fractures. The post-stack azimuth seismic attributes can finely depict the fracture density and indicate the development direction of fractures. Along the selected azimuth direction, the corresponding post-stack azimuth seismic attributes are extracted, not limited to various extraction methods, to obtain the post-stack azimuth seismic attribute data volume.

[0030] Among them, the number of azimuths set in step S2 is greater than or equal to 3 and less than or equal to 6.

[0031] Among them, the number of azimuths set in step S2 is 3, and the set multiple azimuths include: The first azimuth, and the first azimuth is the 0° angle parallel to the seismic fault; The second azimuth, and the second azimuth is the 45° angle with the seismic fault; The third azimuth, and the third azimuth is the 90° angle perpendicular to the seismic fault.

[0032] According to the regional fault development characteristics and seismic structure interpretation, the present invention selects three azimuths, and the selection principle is: the first azimuth is the azimuth parallel to the main fault, the second azimuth is the first azimuth plus 45 degrees, and the third azimuth is the first azimuth plus 90 degrees.

[0033] Specifically, the physical meanings of the selected three specific angles are: the 0° direction (parallel to the fault) captures the characteristics of seismic waves propagating along the fracture strike; the 90° direction (perpendicular to the fault) captures the characteristics of seismic waves propagating perpendicular to the fracture strike; the 45° direction provides an intermediate state, increasing the constraint information and helping to improve the accuracy of subsequent ellipse fitting.

[0034] Usually, the algorithms for calculating post-stack seismic attributes such as coherence volume, amplitude, and frequency calculate the change in the total amplitude or total frequency of seismic data, which is a comprehensive response and cannot well reflect the development information of fractures, and the development direction of fractures at each point cannot be obtained. The post-stack azimuth seismic attributes calculate the changes in coherence, amplitude, and frequency in different azimuths. In the direction perpendicular to the fracture, the gradients of amplitude, frequency, etc. become larger, and in the direction parallel to the fracture, the gradients become smaller, improving the fracture recognition accuracy. Therefore, in step S2 of the present invention, three azimuth attribute data of the filtered data after guided filtering of the original seismic data are extracted along the set 3 azimuths.

[0035] In a specific embodiment, the present invention extracts the post-stack seismic amplitude change rate seismic attribute according to the selected first azimuth, second azimuth, and third azimuth to obtain the azimuth attribute data data1 of the first azimuth, such as Figure 3As shown, the azimuth attribute data data2 of the second azimuth angle, such as Figure 4 As shown, the azimuth attribute data data3 of the third azimuth angle, such as Figure 4 As shown.

[0036] S3: Perform elliptical fitting on multiple azimuth attribute data to obtain elliptical parameters.

[0037] Furthermore, the elliptical fitting in step S3 is a process of fitting the attribute data points measured at different azimuth angles to an elliptical model. In a medium containing directional fractures, the distribution of azimuth attributes usually exhibits an elliptical characteristic. Through elliptical fitting, the complex azimuth attribute differences can be transformed into intuitive elliptical geometric parameters, facilitating subsequent analysis.

[0038] Among them, the elliptical parameters in step S3 include: elliptical flattening data, elliptical major axis data, and elliptical minor axis data.

[0039] Specifically, in step S3, using the elliptical fitting method, perform elliptical fitting on the three post-stack azimuth seismic amplitude change rate attributes obtained in step S2. By performing elliptical fitting on the post-stack azimuth seismic amplitude change rate attributes, the elliptical flattening data, elliptical major axis data, and minor axis data of the ellipse are obtained; the principle of elliptical simulation is mainly based on azimuthal anisotropy. The presence of fractures will cause differences in the response characteristics and attributes of seismic data in different azimuths. By fitting the elliptical trajectories of seismic attributes (such as amplitude, frequency, etc.), the strike and development degree of fractures can be inferred.

[0040] S4: Analyze the obtained fracture data based on the elliptical parameters.

[0041] In step S4, based on the elliptical flattening data, major axis direction data, and minor axis direction data in step S3, combined with logging, drilling, and geological data for fracture density and direction analysis, the fracture density and direction of the final fracture reservoir can be obtained.

[0042] Among them, the fracture data in step S4 includes: fracture density data and fracture direction data.

[0043] Among them, the fracture density data is obtained by analyzing the elliptical flattening data, and the fracture direction data is obtained by analyzing the elliptical major axis data and the elliptical minor axis data.

[0044] The specific correspondence between fracture parameters and elliptical parameters is that the larger the elliptical flattening, the higher the fracture density. The directions of the elliptical major axis and minor axis are directly related to the strike of the fractures. Generally, the direction of the elliptical major axis is perpendicular to the main direction of the fractures.

[0045] Furthermore, the flatness data of the ellipse can indirectly indicate the degree of crack development. In this embodiment, after analogy and correction with other data in the actual work area, the crack density data is obtained as Figure 6 shown. By analyzing the major axis data and minor axis data of the ellipse, the direction with a small change rate of post-stack azimuth seismic amplitude is the crack trend. In this embodiment, the crack direction data is obtained as Figure 7 shown.

[0046] Among them, step S4 further includes: Drawing a crack prediction map according to the crack density data and crack direction data in the crack data.

[0047] Furthermore, the present invention also visualizes the calculated crack parameters to generate a crack distribution prediction map, intuitively showing the spatial distribution characteristics of cracks in the study area. The obtained prediction map may include: a crack density distribution map: using a color scale to represent the crack density at different positions; a crack direction distribution map: using line segments or arrows to represent the crack directions at different positions; a composite attribute map: superimposing and displaying the density and direction information.

[0048] As Figure 2 shown, the present invention also provides a crack prediction device based on post-stack seismic azimuth attribute differences, including: Filtering module 100: configured to perform steerable filtering on the original seismic data to obtain filtered data.

[0049] Preferably, the filtering module is configured as a steerable filter to implement steerable filtering of the original seismic data from the hardware side.

[0050] Extraction module 200: configured to extract multiple azimuth attribute data of the filtered data respectively based on a set of multiple azimuth angles.

[0051] Fitting module 300: configured to perform ellipse fitting on the multiple azimuth attribute data to obtain ellipse parameters.

[0052] Analysis module 400: configured to analyze and obtain crack data according to the ellipse parameters.

[0053] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed to multiple network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art can understand and implement it without creative efforts.

[0054] The present invention also provides a crack prediction device based on post-stack seismic azimuth attribute differences, including: A memory and at least one processor, with instructions stored in the memory; At least one of the processors invokes the instructions in the memory to cause a crack prediction device based on post-stack seismic azimuth attribute differences to execute a crack prediction method based on post-stack seismic azimuth attribute differences as described in any one of the above.

[0055] The present invention also provides a computer-readable storage medium, with instructions stored on the computer-readable storage medium, and when the instructions are executed by a processor, a crack prediction method based on post-stack seismic azimuth attribute differences as described in any one of the above is implemented.

[0056] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course also by hardware. Based on such an understanding, the essence of the above technical solutions, or the part that contributes to the prior art, can be embodied in the form of a software product, and this computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disc, etc., including several instructions to cause a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0057] The present invention provides a crack prediction method and device based on post-stack seismic azimuth attribute differences. By setting multiple azimuth angles and extracting the azimuth attributes of post-stack seismic data, the azimuth characteristics of cracks can be captured more comprehensively, and the ellipse fitting method is used to extract ellipse parameters, which can more accurately quantify the density and direction of cracks, thereby improving the accuracy of crack prediction. By quantitatively analyzing the crack density and direction through ellipse parameters, a reliable basis can be provided for subsequent reservoir evaluation and development plan design. The present invention can not only provide a scientific basis for the exploration and development of fractured reservoirs, but also significantly reduce the exploration cost, and has important practical application value.

[0058] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features; and these modifications or replacements 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 fracture prediction method based on post-stack seismic azimuth attribute differences, characterized in that: include: S1: Perform guided filtering on the original seismic data to obtain filtered data; S2: setting a plurality of azimuth angles, and extracting a plurality of azimuth attribute data of the filtered data respectively based on the plurality of azimuth angles; S3: performing ellipse fitting on multiple orientation attribute data to obtain ellipse parameters; S4: Obtain crack data according to the ellipse parameter analysis.

2. A fracture prediction method based on post-stack seismic azimuth attribute differences according to claim 1, characterized in that: The number of azimuth angle settings in step S2 is greater than or equal to 3 and less than or equal to 6.

3. A fracture prediction method based on post-stack seismic azimuth attribute differences according to claim 2, characterized in that: The number of azimuth angles set in step S2 is 3, and the set multiple azimuth angles include: a first azimuth angle, wherein the first azimuth angle is an angle of 0° parallel to the earthquake fault; a second azimuth angle, wherein the second azimuth angle is 45° to the earthquake fault; The third azimuth angle is a 90° angle perpendicular to the earthquake fault.

4. The fracture prediction method based on post-stack seismic azimuth attribute difference according to claim 1, characterized in that: The ellipse parameters in step S3 include: Ellipse flattening data, ellipse major axis data, ellipse minor axis data.

5. A fracture prediction method based on post-stack seismic azimuth attribute differences according to claim 4, characterized in that: The crack data in step S4 includes: Crack density data, crack direction data.

6. A fracture prediction method based on post-stack seismic azimuth attribute differences according to claim 5, characterized in that: The crack density data is obtained by analyzing the ellipse flattening data, and the crack direction data is obtained by analyzing the ellipse major axis data and the ellipse minor axis data.

7. The fracture prediction method based on post-stack seismic azimuth attribute difference according to claim 1, characterized in that: Step S4 also includes: A crack prediction map is drawn based on the crack density data and the crack direction data in the crack data.

8. A fracture prediction device based on post-stack seismic azimuth attribute differences, characterized in that: include: Filter module: used to perform guided filtering on the original seismic data to obtain filtered data; Extraction module: used for respectively extracting multiple azimuth attribute data of the filtering data based on multiple set azimuth angles; Fitting module: used to perform ellipse fitting on multiple orientation attribute data to obtain ellipse parameters; Analysis module: used for obtaining crack data according to the ellipse parameter analysis.

9. A fracture prediction device based on post-stack seismic azimuth attribute differences, characterized in that: include: A memory and at least one processor, wherein instructions are stored in the memory; At least one of the processors calls the instructions in the memory to enable a fracture prediction device based on post-stack seismic azimuth attribute differences to execute a fracture prediction method based on post-stack seismic azimuth attribute differences as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, and when the instructions are executed by the processor, a fracture prediction method based on post-stack seismic azimuthal attribute differences as described in any one of claims 1 to 7 is implemented.

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