Pre-stack gather optimization processing method and device, electronic equipment and medium

Abstract

The application discloses a pre-stack gather optimization processing method and device, electronic equipment and medium, wherein the processing method comprises the following steps: step 1: establishing an AVO synthetic gather based on actual logging data in a work area; step 2: comparing and analyzing the AVO feature difference between the original wellside gather and the synthetic gather, evaluating the problems existing in the original wellside gather based on the AVO feature difference, wherein the problems include noise interference, residual time difference and inconsistent near-far gather spectrum; step 3: for each problem existing in the original wellside gather, performing data optimization processing to modify and improve the original wellside gather to the synthetic gather; and step 4: performing pre-stack inversion on the data before optimization and the data after optimization respectively, and evaluating the optimization result of the original wellside gather based on the inversion result.

Description

Technical Field

[0001] This invention relates to the field of oil and gas geophysical exploration, and more specifically, to a method, apparatus, electronic device, and medium for pre-stack gather optimization processing. Background Technology

[0002] Conventional post-stack acoustic impedance inversion methods rely on post-stack data and can only obtain a single reservoir elastic parameter, namely acoustic impedance information. These methods struggle to effectively identify reservoirs in complex areas, particularly when reservoirs and non-reservoir areas are severely mixed, as acoustic impedance cannot effectively distinguish between them. Pre-stack inversion methods based on pre-stack data, however, can reflect the amplitude variation characteristics with shot-receiver distance recorded in the field acquisition. Furthermore, they can fully utilize shear wave information closely related to shot-receiver distance. Therefore, pre-stack inversion can obtain more elastic parameters reflecting the distinction between reservoirs and non-reservoir areas, such as Poisson's ratio and Young's modulus. Ultimately, this provides richer and more accurate data for reservoir prediction.

[0003] Pre-stack inversion is widely used in reservoir prediction. The accuracy and reliability of the inversion results depend on both the inversion algorithm itself and the quality of the underlying data used, i.e., the pre-stack gathers. Ideally, seismic information is a true reflection of subsurface lithology, reservoirs, and fluids. However, various factors such as acquisition and processing alter the seismic record. It is precisely the introduction of these non-lithological, non-reservoir, and non-fluid information that leads to inaccurate subsurface information inversion. Pre-stack gather optimization can eliminate (suppress) seismic anomalies caused by non-lithological and non-fluid information, restore seismic information that objectively reflects lithological and fluid changes, and ultimately improve the accuracy of pre-stack inversion.

[0004] To address various issues in pre-stack gathers after conventional processing, such as low signal-to-noise ratio, uneven phase axis (i.e., residual time difference), and inconsistent spectrum, traditional gather optimization methods often lack comprehensive basic data analysis. Problems with the original gathers are often judged solely by the gathers themselves or by simple comparison with the synthesized gathers, without in-depth analysis. Consequently, the formulation of the processing flow tends to be subjective, and there is a lack of comprehensive and effective quality control measures for the rationality of the processing results.

[0005] Therefore, we look forward to a pre-stack gather optimization method that can effectively optimize the original wellside gathers and provide high-quality data for pre-stack inversion.

[0006] The information disclosed in the background section of this invention is intended only to enhance the understanding of the general background of this invention, and should not be construed as an admission or in any way implying that such information constitutes prior art known to those skilled in the art. Summary of the Invention

[0007] The purpose of this invention is to propose a pre-stack gather optimization processing method, apparatus, electronic equipment and medium, which can effectively optimize the original wellside gathers and provide high-quality data for pre-stack inversion.

[0008] In a first aspect, embodiments of this disclosure provide a pre-stack gather optimization method, including:

[0009] Step 1: Establish AVO composite gather based on actual well logging data within the work area;

[0010] Step 2: Compare and analyze the differences in AVO characteristics between the original well-side gather and the synthesized gather, and evaluate the problems existing in the original well-side gather based on the differences in AVO characteristics. The problems include: noise interference, residual time difference, and inconsistency between near and far channel spectra.

[0011] Step 3: For each problem existing in the original well-side trace collection, perform data optimization processing to correct and improve the original well-side trace collection into the synthetic trace collection;

[0012] Step 4: Perform pre-stack inversion on the data before and after optimization, and evaluate the optimization results of the original wellside gather based on the inversion results.

[0013] As a specific implementation of this disclosure, step 1 includes: selecting typical wells in the work area, selecting wavelet for synthetic recording calibration based on P-wave velocity and density curves, obtaining the corresponding time-depth relationship, and then calculating the corresponding reflection coefficient based on the Zoeppritz equation in combination with the S-wave velocity, and selecting the wavelet to establish the AVO synthetic gather.

[0014] As a specific implementation of this disclosure, step 2 includes: combining the original well-side gather and the synthetic gather, selecting a marker layer, performing AVO feature analysis, and analyzing and evaluating the differences between the original well-side gather and the synthetic gather from four aspects: amplitude, residual time difference, correlation, and maximum frequency, and identifying the problems existing in the original well-side gather.

[0015] As a specific implementation of this disclosure, step 3 includes: performing parameter testing based on the original well-side gather, selecting a marker layer to analyze the AVO characteristic changes of the original well-side gather and the differences with the synthetic gather as pre-stack micro-quality control; simultaneously, superimposing the well-crossing lines of each optimization process, and using the correlation between the post-stack spectrum and well-vibration calibration as post-stack macro-quality control to ensure the rationality of each optimization process.

[0016] Secondly, embodiments of this disclosure also provide an electronic device, including:

[0017] At least one processor; and,

[0018] A memory communicatively connected to the at least one processor; wherein,

[0019] The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the pre-stack gather optimization processing method described above.

[0020] Thirdly, embodiments of this disclosure also provide a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the aforementioned pre-stack gather optimization processing method.

[0021] Fourthly, this disclosure also provides a pre-stack gather optimization processing device, including: a construction module, which is used to establish an AVO synthetic gather based on actual logging data within the work area;

[0022] The analysis module is used to evaluate the problems existing in the original wellside gather based on the differences in AVO characteristics between the original wellside gather and the synthetic gather, based on the differences in AVO characteristics.

[0023] An optimization module is used to optimize each problem existing in the original well-side trace collection and correct and improve the original well-side trace collection into the synthetic trace collection.

[0024] The evaluation module is used to perform pre-stack inversion on the original data before optimization and the data after optimization, and evaluate the optimization results of the original wellside gather based on the inversion results.

[0025] As a specific implementation of this disclosure, the construction module is used to: select typical wells in the work area, select wavelets for synthetic recording and calibration based on the P-wave velocity and density curves, obtain the corresponding time-depth relationship, and then calculate the corresponding reflection coefficient based on the Zoeppritz equation in combination with the S-wave velocity, and select wavelets to establish the AVO synthetic gather.

[0026] As a specific implementation of this disclosure, the analysis module is used to: combine the original well-side gather and the synthetic gather, select a marker layer, perform AVO feature analysis, and analyze and evaluate the differences between the original well-side gather and the synthetic gather from four aspects: amplitude, residual time difference, correlation and maximum frequency, and identify the problems existing in the original well-side gather.

[0027] As a specific implementation of this disclosure, the optimization module is used to: perform parameter testing based on the well-side gather, select a marker layer to analyze the AVO characteristic changes of the original well-side gather and the differences with the synthetic gather as pre-stack micro-quality control; and simultaneously superimpose the well-crossing lines of each optimization process, and use the correlation between the post-stack spectrum and well-vibration calibration as post-stack macro-quality control to ensure the rationality of each optimization process.

[0028] The beneficial effects of this invention are as follows:

[0029] This invention establishes an AVO synthetic gather, compares and analyzes the AVO characteristics of the original well-side gather and the synthetic gather to identify the problems existing in the original well-side gather, and then formulates a targeted optimization process. Finally, the optimization results are effectively evaluated intuitively through pre-stack inversion results. This method avoids the blindness of the gather optimization process and the subjectivity of the processing parameter settings, ultimately providing high-quality data for pre-stack inversion.

[0030] This invention performs parameter testing based on the original wellside gathers, and simultaneously conducts quality control from both pre-stack microscopic and post-stack macroscopic aspects to ensure the rationality of the processing procedures and parameters. A series of quality control measures ensure the rationality of the processing.

[0031] The methods and apparatus of the present invention have other features and advantages that will be apparent from or will be set forth in detail in the accompanying drawings and following detailed description, which together serve to explain the particular principles of the invention. Attached Figure Description

[0032] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings, wherein the same reference numerals generally represent the same parts.

[0033] Figure 1 A flowchart illustrating the steps of a pre-stack gather optimization method according to an embodiment of the present invention is shown.

[0034] Figure 2a The original well-side gather and the synthetic gather are shown according to an embodiment of the present invention.

[0035] Figure 2b A comparison of AVO features of the original well-side gather and the synthetic gather according to an embodiment of the present invention is shown.

[0036] Figure 3a A gather optimization process according to an embodiment of the present invention is shown.

[0037] Figure 3b Pre-stack micro-quality control according to an embodiment of the present invention is shown.

[0038] Figure 4a Post-stack spectral analysis according to an embodiment of the present invention is illustrated.

[0039] Figure 4b A macroscopic quality control of well-seismic calibration correlation according to an embodiment of the present invention is shown.

[0040] Figure 5a A comparison of pre-stack inversion results according to an embodiment of the present invention is shown.

[0041] Figure 5b The quality control and correlation comparison of well bypass inversion results according to an embodiment of the present invention are shown. Detailed Implementation

[0042] Preferred embodiments of the invention will now be described in more detail. While preferred embodiments of the invention are described below, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0043] One embodiment of the present invention provides a pre-stack gather optimization method. The core of the pre-stack gather optimization method based on AVO feature analysis is to start from actual logging data, establish an AVO synthetic gather, compare and analyze the AVO features of the original gather and the synthetic gather to evaluate the problems existing in the original gather, then formulate a targeted optimization process to correct and improve the original gather to the synthetic gather, and control the rationality of the quality control from both pre-stack and post-stack aspects. Finally, the effectiveness of the gather optimization is verified by the pre-stack inversion results.

[0044] Specifically, the method includes:

[0045] Step 1: Establish AVO composite gather based on actual well logging data within the work area;

[0046] Step 2: Compare and analyze the differences in AVO characteristics between the original well-side gather and the synthesized gather, and evaluate the problems existing in the original well-side gather based on the differences in AVO characteristics. The problems include: noise interference, residual time difference, and inconsistency between near and far channel spectra.

[0047] Step 3: For each problem existing in the original well-side trace collection, perform data optimization processing to correct and improve the original well-side trace collection into the synthetic trace collection;

[0048] Step 4: Perform pre-stack inversion on the data before and after optimization, and evaluate the optimization results of the original wellside gather based on the inversion results.

[0049] In one example, step 1 includes: selecting typical wells in the work area, selecting wavelet for synthetic recording calibration based on P-wave velocity and density curves, obtaining the corresponding time-depth relationship, and then calculating the corresponding reflection coefficient based on the Zoeppritz equation using S-wave velocity, and selecting wavelet to establish the AVO synthetic gather.

[0050] In one example, step 2 includes: combining the original well-side gather and the synthetic gather, selecting a marker layer, performing AVO feature analysis, and analyzing and evaluating the differences between the original well-side gather and the synthetic gather from four aspects: amplitude, residual time difference, correlation, and maximum frequency, to identify the problems existing in the original well-side gather.

[0051] In one example, step 3 includes: performing parameter testing based on the original well-side gather, selecting a marker layer to analyze the changes in AVO characteristics of the original well-side gather and the differences between it and the synthetic gather as pre-stack micro-quality control; and simultaneously superimposing the well-crossing lines of each optimization process, using the correlation between the post-stack spectrum and well-seismic calibration as post-stack macro-quality control to ensure the rationality of each optimization process.

[0052] The specific implementation steps in one example are as follows:

[0053] (1) Establish AVO synthetic gather. Select typical wells in the work area, select wavelets for synthetic recording and calibration based on P-wave velocity and density curves, obtain the corresponding time-depth relationship, and then calculate the corresponding reflection coefficient based on the Zoeppritz equation in combination with the S-wave velocity. Then select a suitable wavelet to establish AVO synthetic gather.

[0054] (2) Comparative analysis of AVO characteristics between the original well-side gather and the synthetic gather. By combining the original well-side gather and the AVO synthetic gather obtained in step (1), a marker layer is selected and AVO characteristic analysis is performed. The differences between the original gather and the synthetic gather are analyzed and evaluated from four aspects: amplitude, residual time difference, correlation and maximum frequency. The problems existing in the original gather are identified, and preparations are made for formulating a suitable processing procedure.

[0055] (3) Formulate an optimized processing flow. Based on the problems identified in the original gathers in step (2), formulate a suitable optimized processing flow. Perform parameter testing based on the well-side gathers, and select marker layers to analyze the changes in AVO characteristics of the original gathers and their differences from the AVO-synthesized gathers as pre-stack micro-quality control. Simultaneously, overlay the well-crossing lines of each processing step, and use the correlation between the post-stack spectrum and well-seismic calibration as post-stack macro-quality control. Ensure the rationality of each processing step.

[0056] (4) Evaluation of gather optimization results. The ultimate goal of gather optimization is to provide a high-quality data foundation for pre-stack inversion, thereby effectively improving the accuracy and reliability of pre-stack inversion. Therefore, pre-stack inversion is performed using the original data and the optimized data respectively, and the gather optimization results are evaluated based on the inversion results.

[0057] This disclosure also provides an electronic device, which includes:

[0058] At least one processor; and,

[0059] A memory that is communicatively connected to at least one processor; wherein,

[0060] The memory stores instructions that can be executed by at least one processor, which enables the at least one processor to perform the pre-stack gather optimization processing method described above.

[0061] This disclosure also provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the pre-stack gather optimization processing method described above.

[0062] This disclosure also provides a pre-stack gather optimization processing apparatus, including:

[0063] The construction module is used to establish AVO synthetic gathers based on actual logging data within the work area;

[0064] The analysis module is used to evaluate the problems existing in the original wellside gather based on the differences in AVO characteristics between the original wellside gather and the synthetic gather, based on the differences in AVO characteristics.

[0065] An optimization module is used to optimize each problem existing in the original well-side trace collection and correct and improve the original well-side trace collection into the synthetic trace collection.

[0066] The evaluation module is used to perform pre-stack inversion on the original data before optimization and the data after optimization, and evaluate the optimization results of the original wellside gather based on the inversion results.

[0067] In one example, the building module is used to: select typical wells in the work area, select wavelets for synthetic recording and fine calibration based on P-wave velocity and density curves, obtain the corresponding time-depth relationship, and then calculate the corresponding reflection coefficient based on the Zoeppritz equation using S-wave velocity, and select wavelets to establish the AVO synthetic gather.

[0068] In one example, the analysis module is used to: combine the original well-side gather and the synthetic gather, select a marker layer, perform AVO feature analysis, and analyze and evaluate the differences between the original well-side gather and the synthetic gather from four aspects: amplitude, residual time difference, correlation, and maximum frequency, and identify the problems existing in the original well-side gather.

[0069] In one example, the optimization module is used to: perform parameter testing based on the well-side gather, select a marker layer to analyze the changes in AVO characteristics of the original well-side gather and the differences between it and the synthetic gather as pre-stack micro-quality control; at the same time, the well-crossing lines of each optimization process are superimposed, and the correlation between the post-stack spectrum and well-seismic calibration is used as post-stack macro-quality control to ensure the rationality of each optimization process.

[0070] This invention establishes an AVO synthetic gather, compares and analyzes the AVO characteristics of the original well-side gather and the synthetic gather to identify the problems existing in the original well-side gather, and then formulates a targeted optimization process. Finally, the optimization results are effectively evaluated intuitively through pre-stack inversion results. This method avoids the blindness of the gather optimization process and the subjectivity of the processing parameter settings, ultimately providing high-quality data for pre-stack inversion.

[0071] This invention performs parameter testing based on the original wellside gathers, and simultaneously conducts quality control from both pre-stack microscopic and post-stack macroscopic aspects to ensure the rationality of the processing procedures and parameters. A series of quality control measures ensure the rationality of the processing.

[0072] To facilitate understanding of the solutions and effects of the embodiments of the present invention, three specific application examples are given below. Those skilled in the art should understand that these examples are merely for the purpose of understanding the present invention, and any specific details therein are not intended to limit the present invention in any way.

[0073] Example 1

[0074] Figure 1 A flowchart illustrating the steps of a pre-stack gather optimization method according to an embodiment of the present invention is shown.

[0075] like Figure 1As shown, the pre-stack gather optimization method includes: Step 1, establishing an AVO synthetic gather based on actual logging data within the work area; Step 2, comparing and analyzing the differences in AVO characteristics between the original well-side gather and the synthetic gather, and evaluating the problems existing in the original well-side gather based on the differences in AVO characteristics, including: noise interference, residual time difference, and inconsistency between near and far channel spectra; Step 3, performing data optimization processing for each problem existing in the original well-side gather, correcting and improving the original well-side gather towards the synthetic gather; Step 4, performing pre-stack inversion on the data before optimization and the data after optimization respectively, and evaluating the optimization results of the original well-side gather based on the inversion results.

[0076] refer to Figures 2a to 5b Taking actual data from a certain region as an example, we first conduct data quality analysis on the original pre-stack gathers. Figure 2a The figures show the original wellside gather (left side) and the AVO composite gather (right side) of a typical well within the work area. Figure 2b The AVO features are for a selected marker layer. The AVO features show that the amplitude trends of the original well-side gather and the synthetic gather are consistent. Therefore, subsequent processing does not require extensive amplitude modification; the main tasks are denoising and fitting to bring the amplitude scatter points closer to the trend line. The original well-side gather has a certain residual time difference, which needs to be corrected. The distant channels of the original well-side gather have interference, resulting in low correlation and maximum frequency. Spectral consistency correction is needed to improve the spectrum of the distant channels, making them closer to the AVO features of the synthetic gather.

[0077] By comparing and analyzing the AVO characteristics of the original well-side gather and the synthetic gather, an optimization process was proposed after identifying the problems existing in the original well-side gather. Figure 3a The results of well-side gathers for a typical well at different processing stages are shown from left to right: original gather, gather after denoising, gather after flattening, gather after spectral balancing, and synthesized gather. Figure 3b These are the AVO features of the same marker layer at different processing stages. The original gather is first denoised to improve its signal-to-noise ratio (SNR); then residual time difference correction is performed to flatten the gather; finally, spectral consistency correction is performed to refine the near- and far-channel spectra. Parameter testing at each processing step considers both the gather itself and the AVO features. Optimized processing significantly improves the gather's SNR and near- and far-channel energy, while the trend of the amplitude scatter plot fitting curve remains unchanged and is closer to that of the synthesized gather. The residual time difference fitting curve coincides with that of the synthesized gather, both being 0. Figure 4aTo perform spectral analysis on typical well overlay data from different processing stages, the following data was collected: (a) original gather overlay spectrum; (b) denoised gather overlay spectrum; (c) flattened gather overlay spectrum; and (d) spectrally balanced gather overlay spectrum. The main focus was on whether the bandwidth before and after the overlay quality control processing was essentially consistent, with no significant low-frequency or high-frequency loss. In the example, the bandwidth of the original gather overlay spectrum was 27 Hz, and the bandwidth of the optimized gather overlay spectrum was 28 Hz, with no low- or high-frequency loss observed, ensuring the rationality of the processing. Figure 4b Well-seismic calibration was performed on both the original and optimized stacked data using the same time depth and wavelet. (a) shows the post-stack profile of the original stack; (b) shows the well-seismic matching of the original stack; (c) shows the post-stack profile of the optimized stack; and (d) shows the well-seismic matching of the optimized stack. Comparison of the target layer correlation shows that the well-seismic correlation of the stacked data after stack optimization is significantly improved. Through preliminary stack optimization and AVO feature quality control, the original stack was effectively corrected and improved towards the synthetic stack, enhancing its quality. Finally, the results of the inversion were used for evaluation and verification. Figure 5a For the comparison of pre-stack inversion results, (a) is the impedance well profile of the original gather inversion, and (b) is the impedance well profile of the optimized gather inversion. The comparison shows that the optimized gather inversion results have higher resolution and better agreement with the well information. Figure 5b The comparison shows the well bypass inversion results before and after the corresponding gather optimization. The blue curve represents the actual logging impedance filtering result, and the red curve represents the inverted impedance result. The correlation between the pre-stack inversion impedance result and the logging impedance filtering result of the optimized gather is significantly improved. This method effectively optimizes the original gather, providing a high-quality data foundation for pre-stack inversion.

[0078] Example 2

[0079] This disclosure also provides an electronic device, which includes:

[0080] At least one processor; and,

[0081] A memory that is communicatively connected to at least one processor; wherein,

[0082] The memory stores instructions that can be executed by at least one processor, which enables the at least one processor to perform the pre-stack gather optimization processing method described above.

[0083] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0084] This memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0085] The processor may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of this disclosure, the processor is used to execute computer-readable instructions stored in the memory.

[0086] Those skilled in the art will understand that, in order to solve the technical problem of how to achieve a good user experience, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included within the protection scope of this disclosure.

[0087] This disclosure also provides a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the pre-stack gather optimization processing method described above.

[0088] Example 3

[0089] This disclosure provides a non-transitory computer-readable storage medium that stores computer instructions for causing a computer to execute the pre-stack gather optimization processing method described above.

[0090] A computer-readable storage medium according to embodiments of the present disclosure stores non-transitory computer-readable instructions. When these non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the methods described in the foregoing embodiments of the present disclosure are performed.

[0091] The aforementioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or portable hard drive), media with built-in rewritable non-volatile memory (e.g., memory card), and media with built-in ROM (e.g., ROM cartridge).

[0092] Those skilled in the art should understand that the above description of the embodiments of the present invention is only intended to illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any of the examples given.

[0093] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for pre-stack gather optimization, characterized in that, include: Step 1: Establish AVO composite gather based on actual well logging data within the work area; Step 2: Combining the original well-side gather and the synthesized gather, select a marker layer and perform AVO feature analysis. Analyze and evaluate the differences between the original well-side gather and the synthesized gather from four aspects: amplitude, residual time difference, correlation, and maximum frequency. Identify the problems existing in the original well-side gather, including: noise interference, residual time difference, and inconsistency between near and far channel spectra. Step 3: For each problem existing in the original well-side gather, data optimization processing is performed to correct and improve the original well-side gather into the synthetic gather; wherein, based on the original well-side gather, parameter testing is performed, and marker layer analysis is selected to analyze the changes in AVO characteristics of the original well-side gather and the differences with the synthetic gather as pre-stack micro-quality control; at the same time, the well crossing lines of each optimization process are superimposed, and the correlation between the post-stack spectrum and well-vibration calibration is used as post-stack macro-quality control to ensure the rationality of each optimization process; Step 4: Perform pre-stack inversion on the data before and after optimization, and evaluate the optimization results of the original wellside gather based on the inversion results.

2. The pre-stack gather optimization method according to claim 1, characterized in that, Step 1 includes: selecting typical wells in the work area, selecting wavelet for synthetic recording calibration based on P-wave velocity and density curves, obtaining the corresponding time-depth relationship, and then calculating the corresponding reflection coefficient based on the Zoeppritz equation using the shear wave velocity, and selecting the wavelet to establish the AVO synthetic gather.

3. An electronic device, characterized in that, The electronic device includes: At least one processor; and, A memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, which, when executed by the at least one processor, enables the at least one processor to perform the pre-stack gather optimization processing method according to any one of claims 1-2.

4. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions for causing the computer to execute the pre-stack gather optimization processing method as described in any one of claims 1-2.

5. A pre-stack gather optimization processing device, characterized in that, include: The construction module is used to establish AVO synthetic gathers based on actual logging data within the work area; The analysis module combines the original well-side gather and the synthetic gather, selects a marker layer, performs AVO feature analysis, and analyzes and evaluates the differences between the original well-side gather and the synthetic gather from four aspects: amplitude, residual time difference, correlation, and maximum frequency. It identifies the problems existing in the original well-side gather, including: noise interference, residual time difference, and inconsistency between near and far channel spectra. The optimization module is used to optimize each problem existing in the original well-side gather, correcting and improving the original well-side gather into the synthetic gather. Specifically, it performs parameter testing based on the original well-side gather, selects a marker layer to analyze the changes in the AVO characteristics of the original well-side gather and the differences between it and the synthetic gather as pre-stack micro-quality control; simultaneously, it overlays the well-crossing lines of each optimization step, and uses the correlation between the post-stack spectrum and well-seismic calibration as post-stack macro-quality control to ensure the rationality of each optimization step. The evaluation module is used to perform pre-stack inversion on the original data before optimization and the data after optimization, and evaluate the optimization results of the original wellside gather based on the inversion results.

6. The pre-stack gather optimization processing apparatus according to claim 5, characterized in that, The construction module is used to: select typical wells in the work area, select wavelets for synthetic recording and calibration based on P-wave velocity and density curves, obtain the corresponding time-depth relationship, and then calculate the corresponding reflection coefficient based on the Zoeppritz equation in combination with the S-wave velocity, and select wavelets to establish the AVO synthetic gather.

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