Gas-bearing property prediction method and device for reef-flat facies reservoir, electronic equipment and medium

Abstract

The application discloses a reef flat reservoir gas-bearing property prediction method and device, electronic equipment and medium. The method can comprise: performing optimization processing on pre-stack gathers, then performing partial angle stacking to obtain a plurality of stacks; performing single-well reservoir and non-reservoir section spectral attenuation analysis based on the plurality of stacks; performing angle optimization and spectral decomposition according to the spectral feature analysis result to obtain a time-frequency spectrum of each stack; and extracting high-frequency attenuation gradient attributes of different stacks according to the time-frequency spectrum to detect reservoir gas-bearing characteristics. The application starts from pre-stack gather data, solves the applicability problem of attenuation attributes in reef flat reservoir gas-bearing property prediction through gather optimization processing, single-well analysis, angle optimization and other means, and effectively improves the reef flat reservoir gas-bearing property prediction accuracy.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of oil and gas geophysical exploration, and more particularly, to a reef flat facies reservoir gas-bearing property prediction method, device, electronic equipment and medium. BACKGROUND

[0002] Reef flat facies carbonate rock oil and gas reservoirs are one of the important global oil and gas reservoir types. In China, large and medium-sized gas fields such as Dakouhe, Tieshanpo, Luojiazai, Puguang, Heba, Longgang and Yuanba have been discovered. The main development layer series of the gas field is the Changxing Formation-Feixianguan Formation and Jialingjiang Formation. The sedimentary environment is the carbonate platform margin, and the reservoir is a reef flat facies carbonate rock. The reef flat body is dispersedly distributed, the reservoir has strong heterogeneity, the gas-water relationship is complex, and there is no unified gas-water interface, which belongs to a reef or a beach gas reservoir. Overall, the gas-bearing property prediction of the reef flat facies reservoir is relatively difficult.

[0003] At present, there are mainly two types of methods for gas-bearing property prediction. One is the fluid factor prediction technology based on elastic parameters, that is, the fluid factor representing the gas-bearing reservoir is obtained through rock physical analysis, and then the relevant elastic parameters are obtained by inversion to calculate the fluid factor. The second is the sensitive attenuation attribute prediction technology based on seismic data, which directly starts from the seismic data to obtain the attenuation attribute representing the gas-bearing reservoir. At present, the first method is mostly used for reef flat facies reservoir gas-bearing property prediction, and the second method is mostly based on post-stack data, so the prediction accuracy is not high. A small amount of pre-stack data lacks systematic analysis and quality control process, and is greatly affected by the quality of the trace set, resulting in that the sensitive attenuation attribute prediction technology based on seismic data has low applicability in reef flat facies reservoir gas-bearing property prediction.

[0004] Therefore, there is a need to develop a reef flat facies reservoir gas-bearing property prediction method.

[0005] The information disclosed in the background section of this application is only intended to deepen the understanding of the general background of the application, and should not be regarded as acknowledging or implying in any form that the information constitutes prior art known to those skilled in the art. SUMMARY

[0006] The present application provides a reef flat facies reservoir gas-bearing property prediction method, device, electronic equipment and medium, which starts from pre-stack trace set data, solves the applicability problem of attenuation attribute in reef flat facies reservoir gas-bearing property prediction through trace set optimization processing, single well analysis, angle optimization and other means, and effectively improves the reef flat facies reservoir gas-bearing property prediction accuracy.

[0007] In a first aspect, the present application provides a reef flat facies reservoir gas-bearing property prediction method, comprising:

[0008] The pre-stack trace set is optimized and processed, and then partially stacked to obtain a plurality of stacked bodies;

[0009] Performing spectral attenuation analysis on single well reservoir and non-reservoir sections based on multiple stacks;

[0010] Performing angle optimization and spectral decomposition according to the spectral feature analysis result to obtain time-frequency spectrum of each stack;

[0011] Extracting high-frequency attenuation gradient attributes of different stacks according to the time-frequency spectrum to detect reservoir gas-bearing characteristics.

[0012] As a specific implementation manner of the embodiment of the present disclosure, the optimization processing includes denoising processing, time difference correction and super path processing.

[0013] As a specific implementation manner of the embodiment of the present disclosure, performing partial angle stacking includes:

[0014] Performing partial angle stacking on the optimized gather, and stacking the gather into multiple stacks according to a maximum angle range of the gather.

[0015] As a specific implementation manner of the embodiment of the present disclosure, performing spectral attenuation analysis on single well reservoir and non-reservoir sections based on multiple stacks includes:

[0016] Determining fine calibration of synthetic records of typical wells, and positioning time ranges corresponding to reservoirs and non-reservoirs on the wells;

[0017] Expanding 20 lines in the horizontal and vertical directions respectively with the well position as the center to generate a small three-dimensional around the well.

[0018] Analyzing spectral features of data in the time range based on multiple stacks, and viewing differences in spectral features of reservoir sections and non-reservoir sections of different angle stacks.

[0019] As a specific implementation manner of the embodiment of the present disclosure, the spectral decomposition includes:

[0020] Determining an optimal angle stacking range, performing spectral decomposition on each partial angle stack by using a high-precision matching pursuit algorithm to obtain time-frequency spectrum of each stack.

[0021] As a specific implementation manner of the embodiment of the present disclosure, it further includes:

[0022] By comparing and analyzing high-frequency attenuation gradient attribute features of different angle stacks, differential processing can enhance the gas-bearing prediction capability.

[0023] In a second aspect, the embodiment of the present disclosure further provides a reef flat facies reservoir gas-bearing prediction device, which includes:

[0024] A stacking module performs optimization processing on pre-stack gathers, and then performs partial angle stacking to obtain multiple stacks.

[0025] an analysis module configured to perform spectral attenuation analysis on single-well reservoir and non-reservoir sections based on the multiple stacks;

[0026] an optimization module configured to perform angle optimization and spectral decomposition according to the spectral feature analysis result, to obtain time-frequency spectra of the multiple stacks;

[0027] a detection module configured to extract high-frequency attenuation gradient attributes of different stacks according to the time-frequency spectra, and to detect reservoir gas-bearing features.

[0028] As a specific implementation manner of the embodiments of the present disclosure, the optimization processing includes denoising processing, time difference correction, and super path processing.

[0029] As a specific implementation manner of the embodiments of the present disclosure, performing partial angle stacking includes:

[0030] Performing partial angle stacking on the optimized gather, and stacking the gather into multiple stacks according to a maximum angle range of the gather.

[0031] As a specific implementation manner of the embodiments of the present disclosure, performing spectral attenuation analysis on single-well reservoir and non-reservoir sections based on the multiple stacks includes:

[0032] Determining fine calibration of synthetic records of typical wells, and locating time ranges corresponding to reservoirs and non-reservoirs on the wells;

[0033] Expanding 20 lines in each of the cross-line and in-line directions with the well as the center, to generate a small three-dimensional space around the well; analyzing spectral features of data in the time ranges based on the multiple stacks, and viewing differences in spectral features of reservoir sections and non-reservoir sections of different angle stacks.

[0034] As a specific implementation manner of the embodiments of the present disclosure, the spectral decomposition includes:

[0035] Determining an optimal angle stacking range, performing spectral decomposition on each partial angle stack by using a high-precision matching pursuit algorithm, to obtain time-frequency spectra of the multiple stacks.

[0036] As a specific implementation manner of the embodiments of the present disclosure, the method further includes:

[0037] By comparing and analyzing high-frequency attenuation gradient attribute features of different angle stacks, and performing differential processing, the gas-bearing prediction capability can be enhanced.

[0038] In a third aspect, the embodiments of the present disclosure further provide an electronic device, which includes:

[0039] a memory storing executable instructions;

[0040] A processor, which runs the executable instructions in the memory, to implement the reef flat reservoir gas-bearing property prediction method.

[0041] In a fourth aspect, the embodiments of the present disclosure further provide a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the reef flat reservoir gas-bearing property prediction method.

[0042] The beneficial effects are that:

[0043] The method and device of the present application have other characteristics and advantages, which will be apparent from or set forth in the accompanying drawings and the following detailed description, which together serve to explain certain principles of the present application.

[0044] The method and device of the present application have other characteristics and advantages, which will be apparent from or set forth in the accompanying drawings and the following detailed description, which together serve to explain certain principles of the present application. BRIEF DESCRIPTION OF DRAWINGS

[0045] The above and other objects, features and advantages of the present application will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings, in which like reference characters refer to like parts throughout the figures, and in which:

[0046] Figure 1 A flow chart showing the steps of the reef flat reservoir gas-bearing property prediction method according to one embodiment of the present application is shown.

[0047] Figure 2a 、 Figure 2b 、 Figure 2c 、 Figure 2d Schematic diagrams of a raw gather, a denoised gather, a flattened gather and a super gather according to one embodiment of the present application are shown respectively.

[0048] Figure 3 A schematic diagram showing a typical well synthetic record calibration according to one embodiment of the present application is shown.

[0049] Figure 4a 、 Figure 4b 、 Figure 4cFigures respectively show schematic diagrams of gas-bearing layer segment, water-bearing layer segment and non-reservoir segment spectrum analysis according to an embodiment of the present application.

[0050] Figure 5a 、 Figure 5b 、 Figure 5c Figures respectively show schematic diagrams of low-angle stack, high-angle stack and differential processing high-frequency attenuation gradient attribute according to an embodiment of the present application.

[0051] Figure 6 Figure shows a block diagram of a reef flat facies reservoir gas-bearing property prediction device according to an embodiment of the present application.

[0052] BRIEF DESCRIPTION OF DRAWINGS

[0053] 201, stack module; 202, analysis module; 203, optimization module; 204, detection module. DETAILED DESCRIPTION

[0054] The preferred embodiments of the present application will be described in more detail below. Although the preferred embodiments of the present application are described below, it should be understood that the present application can be implemented in various forms and should not be limited by the embodiments set forth herein.

[0055] To facilitate understanding of the scheme and effects of the embodiments of the present application, six specific application examples are given below. Those skilled in the art should understand that the examples are only for facilitating understanding of the present application, and any specific details thereof are not intended to limit the present application in any way.

[0056] Example 1

[0057] Figure 1 Figure shows a flowchart of steps of a reef flat facies reservoir gas-bearing property prediction method according to an embodiment of the present application.

[0058] As shown in Figure 1 , the reef flat facies reservoir gas-bearing property prediction method comprises: step 101, performing optimization processing on pre-stack gathers, and then performing partial angle stacking to obtain a plurality of stacks; step 102, performing single-well reservoir and non-reservoir segment spectrum attenuation analysis based on the plurality of stacks; step 103, performing angle optimization and spectrum decomposition according to the spectrum feature analysis result to obtain time-frequency spectrum of each stack; and step 104, extracting high-frequency attenuation gradient attribute of different stacks according to the time-frequency spectrum to detect reservoir gas-bearing characteristics.

[0059] In one example, the optimization processing comprises denoising processing, time difference correction and super channel processing.

[0060] In one example, the partial angle stacking comprises:

[0061] Partial angle stack is performed on the optimized gather, and the gather is stacked into multiple stacks according to a maximum angle range of the gather.

[0062] In one example, the spectral attenuation analysis of the single well reservoir and non-reservoir section based on the multiple stacks includes:

[0063] The fine calibration of the synthetic record of the typical well is determined, and the time range corresponding to the reservoir and non-reservoir on the well is located;

[0064] A small three-dimensional around the well is generated by expanding 20 lines in the horizontal and vertical directions with the well as the center.

[0065] The spectral features of the data in the time range are analyzed based on the multiple stacks, and the spectral feature differences between the reservoir section and the non-reservoir section of different angle stacks are viewed.

[0066] In one example, the spectral decomposition includes:

[0067] The optimal angle stack range is determined, the spectral decomposition of each partial angle stack is performed by using a high-precision matching pursuit algorithm, and the time-frequency spectrum of each stack is obtained.

[0068] In one example, it also includes:

[0069] By comparing and analyzing the high-frequency attenuation gradient attribute features of different angle stacks, differential processing is performed, which can enhance the gas-bearing prediction capability.

[0070] Specifically, in view of the problems that the post-stack attenuation attribute prediction accuracy is not high in the reef flat reservoir gas-bearing prediction, the pre-stack attenuation attribute prediction lacks a systematic analysis and quality control process, and is greatly affected by the gather quality, the pre-stack gather optimization processing is performed to improve the gather quality, spectral attenuation analysis is performed on the reservoir and non-reservoir section of different wells, the angle range is optimized and spectral decomposition is performed on the basis of the analysis, and finally the attenuation attribute changing with the angle is extracted.

[0071] Taking the pre-stack angle gather as an example, first, the gather optimization processing is performed, including denoising processing, time difference correction and super-path processing. The signal-to-noise ratio of the original gather is improved, the residual time difference of the original gather is eliminated, the amplitude anomaly problem is corrected, and the data requirements for gas-bearing prediction are met. Then, partial angle stack is performed on the optimized gather, and the gather is stacked into four stacks according to the maximum angle range of the gather.

[0072] Typical wells in the study area are selected for fine calibration of synthetic records, and the reservoirs and non-reservoirs on the well are accurately positioned in the time range. Then, taking the well position as the center, 20 lines are expanded in the horizontal and vertical directions to generate a small three-dimensional well around the well. In order to subsequent spectral analysis, in order to highlight the attenuation characteristics of the data in the three-dimensional space, the spectrum of the small three-dimensional well around the angle stack body of each part is selected for analysis, so that the spectral feature differences of the reservoir section and the non-reservoir section of different angle stack bodies are clear. On the basis of the generated stack, the spectral characteristics of the data in the range are analyzed, and the spectral feature differences of the reservoir section and the non-reservoir section of different angle stack bodies are viewed.

[0073] According to the spectral feature analysis result, the angle is optimized, and after optimization, the spectral feature differences of the reservoir section of different angle stack bodies are large, and the spectral feature differences of the non-reservoir section are small. After determining the optimal angle stacking range, a high-precision matching pursuit algorithm is used to perform spectral decomposition on each partial angle stack body to obtain the time-frequency spectrum of each stack body.

[0074] When the reservoir contains gas, the high-frequency energy attenuation in the seismic wave is greater than the low-frequency energy attenuation, therefore, the high-frequency attenuation gradient attribute of different stack bodies can be extracted to detect the gas content characteristics of the reservoir. By comparing and analyzing the high-frequency attenuation gradient attribute characteristics of different angle stack bodies, and performing differential processing, the gas content prediction capability can be enhanced.

[0075] Example 2

[0076] The application also provides a reef flat reservoir gas content prediction device, comprising:

[0077] A stacking module is used for optimizing pre-stack gathers and then performing partial angle stacking to obtain a plurality of stack bodies.

[0078] In one example, the optimization processing includes denoising processing, time difference correction and super channel processing.

[0079] In one example, the partial angle stacking includes:

[0080] The optimized gathers are subjected to partial angle stacking, and the gathers are stacked into a plurality of stack bodies according to the maximum angle range of the gathers.

[0081] Specifically, taking the pre-stack angle gather as an example, first, the gather optimization processing is performed, including denoising processing, time difference correction and super channel processing. The signal-to-noise ratio of the original gather is improved through the above processing, the residual time difference of the original gather is eliminated, the amplitude anomaly problem is corrected, and the data requirements for gas content prediction are met. Then, the optimized gathers are subjected to partial angle stacking, and the gathers are stacked into 4 stack bodies according to the maximum angle range of the gathers.

[0082] An analysis module is used for single-well reservoir and non-reservoir section spectral attenuation analysis based on the plurality of stack bodies.

[0083] In one example, the single-well reservoir and non-reservoir section spectral attenuation analysis based on multiple stacks includes:

[0084] determining the fine calibration of the synthetic record of the typical well, locating the time range corresponding to the reservoir and non-reservoir on the well;

[0085] expanding 20 lines in the horizontal and vertical directions respectively with the well location as the center to generate a small three-dimensional around the well;

[0086] analyzing the spectral characteristics of the data in the time range based on multiple stacks, and viewing the spectral characteristic differences of the reservoir section and the non-reservoir section of different angle stacks.

[0087] Specifically, the fine calibration of the synthetic record of the typical well in the study area is selected, and the time range corresponding to the reservoir and non-reservoir on the well is accurately located. Then, the small three-dimensional around the well is generated by expanding 20 lines in the horizontal and vertical directions respectively with the well location as the center. In order to highlight the attenuation characteristics of the data in the three-dimensional space for subsequent spectral analysis, the spectrum of the small three-dimensional around the well of each part angle stack is selected for analysis, so as to clearly determine the spectral characteristic differences of the reservoir section and the non-reservoir section of different angle stacks. The spectral characteristics of the data in the generated stack are analyzed, and the spectral characteristic differences of the reservoir section and the non-reservoir section of different angle stacks are viewed.

[0088] The optimization module performs angle optimization and spectral decomposition according to the spectral characteristic analysis result to obtain the time-frequency spectrum of each stack;

[0089] In one example, the spectral decomposition includes:

[0090] determining the best angle stack range, and performing spectral decomposition on each angle stack by using a high-precision matching pursuit algorithm to obtain the time-frequency spectrum of each stack.

[0091] Specifically, the angle optimization is performed according to the spectral characteristic analysis result, and after optimization, the spectral characteristic differences of the reservoir section of different angle stacks are large, and the spectral characteristic differences of the non-reservoir section are small. After determining the best angle stack range, the spectral decomposition is performed on each angle stack by using a high-precision matching pursuit algorithm to obtain the time-frequency spectrum of each stack.

[0092] The detection module extracts the high-frequency attenuation gradient attribute of different stacks according to the time-frequency spectrum to detect the gas-bearing characteristics of the reservoir.

[0093] Specifically, when the reservoir contains gas, the high-frequency energy attenuation in the seismic wave is larger than the low-frequency energy attenuation, therefore, the high-frequency attenuation gradient attribute of different stacks can be extracted to detect the gas-bearing characteristics of the reservoir. By comparing and analyzing the high-frequency attenuation gradient attribute characteristics of different angle stacks, and performing differential processing, the gas-bearing prediction ability can be enhanced.

[0094] Example 3

[0095] Taking the data of a certain actual gas field as an example, the reservoir in the study area is a typical reef-flat carbonate rock, and the studied strata are the first and second members of the Feixianguan Formation.

[0096] Figure 2a 、 Figure 2b 、 Figure 2c 、 Figure 2d Schematic diagrams of an original gather, a denoised gather, a flattened gather, and a super gather according to an embodiment of the present invention are respectively shown.

[0097] Figure 3 A schematic diagram of typical well synthetic log calibration according to an embodiment of the present invention is shown.

[0098] Figure 4a 、 Figure 4b 、 Figure 4c Schematic diagrams of spectrum analysis of a gas-bearing layer segment, a water-bearing layer segment, and a non-reservoir segment according to an embodiment of the present invention are respectively shown.

[0099] Figure 5a 、 Figure 5b 、 Figure 5c Schematic diagrams of a small-angle superposition body, a large-angle superposition body, and differential processing of high-frequency attenuation gradient properties according to an embodiment of the present invention are respectively shown.

[0100] First, the original gathers are optimized, and the optimization process includes denoising, flattening and super-gathering. Figures 2a-2d This is a comparison of the original wellside gather, denoised gather, flattened gather and super gather of a typical well in the study area. It can be seen from the figure that the quality of the gather is significantly improved after optimization processing. Not only is the signal-to-noise ratio improved, the residual time difference is basically eliminated, the amplitude energy is more focused, and the consistency of the phase axis is better, which meets the data needs of subsequent work. After the optimization process is completed, the optimized gather is partially angle stacked. According to the maximum angle of the gather (24 degrees), the partial angle stacking range is determined to be 1-6 degrees, 7-12 degrees, 13-18 degrees, and 19-24 degrees, and 4 partial angle stacking bodies are obtained. Then, typical wells in the study area are selected for fine calibration of synthetic records. The calibration results are shown as follows. Figure 3 As shown. Based on the logging interpretation results, the time range of the gas-bearing layer section, water-bearing layer section and non-reservoir section on the well is located, and 2620-2650ms is selected as the analysis window for the gas-bearing layer section, 2660-2690ms is selected as the analysis window for the water-bearing layer section, and 2720-2750ms is selected as the analysis window for the non-reservoir section. With the well location as the center, 20 lines are expanded in both the horizontal and vertical survey lines to generate a small three-dimensional well perimeter. The spectrum analysis of the previous four partial angle stacks is performed, as shown in the figure. Figures 4a-4cThe figure shows that the spectrum difference of the gas-bearing layer section in different angle stacks is the largest, the water-bearing layer section is smaller, and the non-reservoir section is basically without difference. Therefore, it is illustrated that the attenuation characteristics of different angle stacks are obviously different, and the angle stack range is reasonably divided, and it is not necessary to perform angle optimization. Next, the high-precision matching pursuit algorithm is used to perform spectrum decomposition on the four partial angle stacks, to obtain the time-frequency spectrum of each stack, and then further extract the high-frequency attenuation gradient attribute. Figure 5a The high-frequency attenuation gradient attribute of the small angle (1-6 degrees) stack, Figure 5b The high-frequency attenuation gradient attribute of the large angle (19-24 degrees) stack, and it can be seen from the circled part in the figure that the gas-bearing reservoir is attenuated more strongly at the large angle than at the small angle, and the non-reservoir and water layer have small difference, which is consistent with the well characteristics. Finally, the high-frequency attenuation gradient attributes of the small angle and the large angle stacks are differentially processed, and the result is as shown in Figure 5c The attenuation gradient attribute result of the circled part is more consistent with the well, and the gas-bearing prediction accuracy is further improved.

[0101] Through the application of the method, the original gather is effectively optimized and processed, the gather quality is improved, the well is analyzed, the partial angle stack range of the gather is determined, the attenuation attribute varying with the angle is extracted on the basis of the spectrum decomposition, and the gas-bearing prediction accuracy of the reef and beach facies reservoir is improved.

[0102] The main purpose of the present application is to solve the problems that the post-stack attenuation attribute has low accuracy in the gas-bearing prediction of the reef and beach facies reservoir, and the pre-stack attenuation attribute is greatly affected by the gather quality and lacks systematic analysis and quality control. The gas-bearing prediction effect of the present application is obvious, the quality control analysis means is comprehensive and reasonable, and the present application can be popularized and applied in different reef and beach facies reservoir areas.

[0103] Example 4

[0104] Figure 6 A block diagram of a reef and beach facies reservoir gas-bearing prediction device according to an embodiment of the present application is shown.

[0105] As shown in Figure 6 The reef and beach facies reservoir gas-bearing prediction device comprises:

[0106] The stack module 201 performs optimization processing on the pre-stack gather, and then performs partial angle stacking to obtain a plurality of stacks;

[0107] The analysis module 202 performs single-well reservoir and non-reservoir section spectrum attenuation analysis based on the plurality of stacks;

[0108] The optimization module 203 performs angle optimization and spectrum decomposition according to the spectrum characteristic analysis result, to obtain the time-frequency spectrum of each stack.

[0109] The detection module 204 extracts high-frequency attenuation gradient attributes of different stacks according to the time-frequency spectrum, and detects the gas-bearing characteristics of the reservoir.

[0110] As a specific implementation manner of the embodiment of the present disclosure, the optimization processing includes denoising processing, time difference correction, and super path processing.

[0111] As a specific implementation manner of the embodiment of the present disclosure, the partial angle stacking includes:

[0112] The optimized gathers are subjected to partial angle stacking, and the gathers are stacked into multiple stacks according to a maximum angle range of the gathers.

[0113] As a specific implementation manner of the embodiment of the present disclosure, the single-well reservoir and non-reservoir section spectral attenuation analysis based on the multiple stacks includes:

[0114] The fine calibration of the synthetic record of the typical well is determined, and the time range corresponding to the reservoir and non-reservoir on the well is located;

[0115] A small three-dimensional around the well is generated by expanding 20 lines of each profile in the horizontal and vertical directions with the well position as the center.

[0116] The spectral features of the data in the time range are analyzed based on the multiple stacks, and the differences in the spectral features of the reservoir sections and non-reservoir sections of different angle stacks are viewed.

[0117] As a specific implementation manner of the embodiment of the present disclosure, the spectral decomposition includes:

[0118] The optimal angle stacking range is determined, the spectral decomposition of each partial angle stack is performed by using a high-precision matching pursuit algorithm, and the time-frequency spectrum of each stack is obtained.

[0119] As a specific implementation manner of the embodiment of the present disclosure, the method further includes:

[0120] By comparing and analyzing the high-frequency attenuation gradient attribute features of different angle stacks, the differentiation processing can enhance the gas-bearing prediction capability.

[0121] Example 5

[0122] The present disclosure provides an electronic device, which includes a memory storing executable instructions, and a processor running the executable instructions in the memory to implement the reef flat facies reservoir gas-bearing prediction method.

[0123] The electronic device according to the embodiment of the present disclosure includes a memory and a processor.

[0124] The memory is configured to store non-transitory computer readable instructions. Specifically, the memory can include one or more computer program products that can include various forms of computer readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory, for example, can include random access memory (RAM), cache memory, and / or the like. The non-volatile memory, for example, can include read only memory (ROM), hard disk, flash memory, and / or the like.

[0125] The processor can be a central processing unit (CPU) or other form of processing unit that has data processing and / or instruction execution capabilities, and can control other components in the electronic device to perform desired functions. In one embodiment of the present disclosure, the processor is configured to execute the computer readable instructions stored in the memory.

[0126] Those skilled in the art will understand that, in order to solve the technical problem of how to obtain a good user experience effect, the present embodiment can also include well-known structures such as a communication bus, an interface, and the like, which should also be included in the protection scope of the present disclosure.

[0127] Detailed descriptions of the present embodiment can refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here.

[0128] Example 6

[0129] The present disclosure provides a computer readable storage medium storing a computer program, which, when executed by a processor, implements the reef flat reservoir gas-bearing property prediction method.

[0130] The computer readable storage medium according to the embodiments of the present disclosure has non-transitory computer readable instructions stored thereon. When the non-transitory computer readable instructions are run by a processor, all or part of the steps of the method of the embodiments of the present disclosure are executed.

[0131] The computer readable storage medium described above includes, but is not limited to, optical storage media (such as CD-ROM and DVD), magneto-optical storage media (such as MO), magnetic storage media (such as magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (such as memory card), and media with built-in ROM (such as ROM cartridge).

[0132] Those skilled in the art will understand that the purpose of the above description of the embodiments of the present disclosure is only to exemplarily illustrate the beneficial effects of the embodiments of the present disclosure, and is not intended to limit the embodiments of the present disclosure to any examples given.

[0133] Having described various embodiments of the application, it is to be understood that the above description is meant to be illustrative only, and that many modifications and variations of the embodiments are possible without departing from the scope and spirit of the described embodiments. Many modifications and variations of the described embodiments are possible in light of the above teachings. It is, therefore, to be understood that within the scope of the appended claims and their equivalents, the described embodiments can be practiced otherwise than as specifically described.

Claims

1. A method for predicting gas content in reef-flat reservoirs, characterized in that: include: Optimize the pre-stack gathers and then perform partial angle stacking to obtain multiple stacked volumes; Conduct spectrum attenuation analysis of single-well reservoir and non-reservoir segments based on multiple stacks; According to the results of spectrum feature analysis, angle optimization and spectrum decomposition are performed to obtain the time-frequency spectrum of each superposition body; The high-frequency attenuation gradient attributes of different superposition bodies are extracted according to the time-frequency spectrum to detect the gas-bearing characteristics of the reservoir.

2. The method for predicting gas content of reef-flat reservoir according to claim 1, wherein: The optimization process includes denoising, time difference correction and super channel processing.

3. The method for predicting gas content of reef-flat reservoir according to claim 1, wherein: Performing partial angle overlays includes: Partial angle stacking is performed on the optimized gathers, and they are stacked into multiple stacking bodies according to the maximum angle range of the gathers.

4. The method for predicting gas content of reef-flat reservoir according to claim 1, wherein: Spectral attenuation analysis of single-well reservoir and non-reservoir segments based on multiple stacks includes: Identify typical wells for fine calibration of synthetic records and locate the time range corresponding to the reservoir and non-reservoir layers above the wells; With the well location as the center, the horizontal and vertical survey lines are expanded by 20 lines each to generate a small three-dimensional image around the well; The frequency spectrum characteristics of the data within the time range are analyzed based on multiple stacks to check the differences in frequency spectrum characteristics between reservoir segments and non-reservoir segments of stacks at different angles.

5. The method for predicting gas content of reef-flat reservoir according to claim 1, wherein: The spectrum decomposition includes: The optimal angle stacking range is determined, and a high-precision matching pursuit algorithm is used to perform spectrum decomposition on each angle stacking body to obtain the time-frequency spectrum of each stacking body.

6. The method for predicting gas content of reef-flat reservoir according to claim 1, wherein: Also includes: By comparing and analyzing the high-frequency attenuation gradient attribute characteristics of stacked bodies at different angles and performing differentiated processing, the ability to predict gas content can be enhanced.

7. A device for predicting gas content of reef-flat reservoirs, characterized in that: include: The stacking module optimizes the pre-stack gathers and performs partial angle stacking to obtain multiple stacked volumes. Analysis module, which performs spectrum attenuation analysis of single well reservoir and non-reservoir segments based on multiple superposition volumes; The optimization module performs angle optimization and spectrum decomposition based on the results of spectrum feature analysis to obtain the time-frequency spectrum of each superposition body; The detection module extracts high-frequency attenuation gradient properties of different superposition bodies according to the time-frequency spectrum and detects gas-bearing characteristics of the reservoir.

8. The gas-bearing property prediction device for reef-flat reservoir according to claim 7, wherein: Spectral attenuation analysis of single-well reservoir and non-reservoir segments based on multiple stacks includes: Identify typical wells for fine calibration of synthetic records and locate the time range corresponding to the reservoir and non-reservoir layers above the wells; With the well location as the center, the horizontal and vertical survey lines are expanded by 20 lines each to generate a small three-dimensional image around the well; The frequency spectrum characteristics of the data within the time range are analyzed based on multiple stacks to check the differences in frequency spectrum characteristics between reservoir segments and non-reservoir segments of stacks at different angles.

9. An electronic device, characterized in that: The electronic device comprises: a memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement the gas-bearing property prediction method of the reef-flat facies reservoir according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method for predicting the gas content of a reef-flat facies reservoir according to any one of claims 1 to 6.

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