Pre-stack angle gather amplitude correction method and device based on AVO forward modeling

Abstract

The invention discloses a pre-stack angle gather amplitude correction method and device based on AVO forward modeling. The method comprises the following steps: generating an AVO forward modeling gather based on logging data and wavelets of a typical well in a research area; comparing reservoir section AVO characteristics of the well-side pre-stack angle gather and the generated forward modeling gather, and determining an angle stacking range of part of angle gather data facing pre-stack inversion; and setting a template channel of pre-stack channel gather data by taking the forward modeling channel gather as a reference, and carrying out amplitude energy value correction and amplitude fitting trend correction along with an incident angle on partial angle channel gather data of a non-template channel so as to improve the quality of the partial angle channel gather. According to the method, the gather quality can be improved, and a high-quality data basis is provided for pre-stack inversion.

Description

Technical Field

[0001] This invention relates to the field of oil and gas geophysical exploration, and more specifically, to a method and apparatus for pre-stack angle gather amplitude correction based on AVO forward modeling. Background Technology

[0002] Pre-stack inversion methods based on pre-stack data can reflect the amplitude variation characteristics of field-acquired data with shot-receiver distance. They can also fully utilize shear wave information closely related to shot-receiver distance and angular information in pre-stack data. Therefore, pre-stack inversion can obtain more elastic parameters reflecting the differences between reservoirs and non-reservoir elements, such as Poisson's ratio and Young's modulus, ultimately providing richer and more accurate data for lithology and reservoir prediction. 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 seismic records. The introduction of these non-lithological, reservoir, and fluid information leads to inaccurate subsurface information inversion. Pre-stack gather optimization can eliminate (suppress) the seismic information changes caused by non-lithological and fluid information, restoring seismic information that objectively reflects lithological and fluid changes, ultimately improving the accuracy of pre-stack inversion.

[0003] Currently, to address various amplitude issues in pre-stack gathers after conventional processing, such as weak amplitude energy and uneven gather energy, research on existing technologies reveals that previous methods primarily focused on the gathers themselves. These methods involved visually observing and identifying amplitude energy problems, employing techniques like spectral balancing, inverse Q filtering, and energy compensation to correct the amplitude-energy relationship. However, these methods lack specificity and cannot effectively address the fundamental problems of pre-stack gathers through visual observation. Secondly, some researchers have optimized gathers by comparing the original gathers with AVO forward-modeled gathers, but this often takes a holistic approach, applying a single set of parameters to the entire gather without considering the quality requirements of pre-stack inversion for specific angles of gather data. Therefore, achieving optimal optimization results is difficult. Summary of the Invention

[0004] The purpose of this invention is to propose a method and apparatus for pre-stack angle gather amplitude correction based on AVO forward modeling, so as to improve gather quality and provide a high-quality data foundation for pre-stack inversion.

[0005] To achieve the above objectives, in a first aspect, the present invention proposes a pre-stack angle gather amplitude correction method based on AVO forward modeling, comprising:

[0006] Based on logging data from typical wells in the study area and wavelet-generated AVO forward set;

[0007] By comparing the reservoir AVO characteristics of pre-stack angle gathers near the well with those of the generated forward-modeled gathers, the angle stacking range of some angle gather data for pre-stack inversion is clarified.

[0008] Using forward modeling gathers as a reference, template gathers are set up for pre-stack gather data. Amplitude energy value correction and amplitude-as-incident-angle fitting trend correction are performed on some angle gather data that are not template gathers to improve the quality of some angle gathers.

[0009] Optionally, the generation of AVO forward lookup based on logging data and wavelet data from typical wells in the study area includes:

[0010] Based on the P-wave velocity and density curves of typical wells in the work area, a suitable wavelet is selected for synthetic recording and fine calibration to obtain the corresponding time-depth relationship. Then, combined with the S-wave velocity and density, the corresponding reflection coefficient is calculated based on the Zoeppritz equation, and a suitable wavelet is selected to generate AVO forward modeling gathers.

[0011] Optionally, the comparison of reservoir segment AVO characteristics between pre-stack angle gathers near the well and the generated forward-modeled gathers clarifies the angle stacking range of partial angle gather data for pre-stack inversion, including:

[0012] By combining the well-side angle gathers with the generated forward-modeled gathers, AVO characteristic analysis is performed on the reservoir section to clarify the AVO type and amplitude scatter distribution trend of the reservoir section. In addition, by combining the effective angle range of the pre-stack angle gathers, the angle superposition range of some angle gather data for pre-stack inversion is clarified.

[0013] Optionally, the angular overlay range of the partial angle gather data includes: the overlay range of near-angle gather data, the overlay range of mid-angle gather data, and the overlay range of far-angle gather data.

[0014] Optionally, the mid-angle gather data is set as a template gather for the pre-stack gather data;

[0015] The non-template trace partial angle gather data includes: near angle gather data and far angle gather data.

[0016] Optionally, the amplitude energy value correction of the partial angle gather data of the non-template trace includes:

[0017] The near-angle gather, intermediate-angle gather, and far-angle gather of the pre-stack angle gather are denoted as O. n O m and O f Let F be the near-angle, mid-angle, and far-angle sets of the corresponding orthogonal set. n F m and F f ;

[0018] Statistical analysis of O n O m O f F n F m F f The average amplitude energy value is denoted as . and

[0019] Choose the mid-angle gather of the pre-stack angle gather as the template gather, and let:

[0020]

[0021] in and This represents the average amplitude energy of the near-angle and far-angle gathers after the first correction of the pre-stack angle gathers.

[0022] Multiplying the near-angle and far-angle gathers from the pre-stack angle gathers before correction by the variation coefficient of the average amplitude energy, we obtain the near-angle and far-angle gathers after amplitude energy correction, i.e.:

[0023]

[0024] Among them O' n O' f These are the near-angle gather and far-angle gather after amplitude energy value correction, respectively.

[0025] Optionally, amplitude fitting trend correction is performed on a portion of the non-template trace angle gather data, including:

[0026] Based on the amplitude variation trends of near-angle, mid-angle, and far-angle gathers in the pre-stack gathers and forward modeling gathers after first correction, a second fitting was performed to obtain the following relationship:

[0027] O' n =a 1n x 2 +b 1n x+c 1n

[0028] O m =a 1m x 2 +b 1m x+c 1m

[0029] O' f =a 1f x 2 +b 1f x+c 1f

[0030] F n =a 2n x 2 +b 2n x+c 2n

[0031] F m =a 2m x 2 +b 2m x+c 2m

[0032] F f =a 2f x 2 +b 2f x+c 2f (3)

[0033] Where x is the angle, a 1n b 1n c 1n a 1m b 1m c 1m a 1f b 1f c 1f and a 2n b 2n c 2n a 2m b 2m c 2m a 2f b 2f c 2f All are constants;

[0034] From the near-angle, intermediate-angle, and far-angle gathers after one correction, the intermediate-angle gather with a higher amplitude-to-incident-angle fitting coefficient and better consistency with the forward-modeling gathers is selected as the template gather, let:

[0035]

[0036] Where a' 1n b' 1n c' 1n and a' 1f b' 1f c' 1f is a constant, and represents the coefficients of the quadratic fitting relationship between the amplitude of near-angle and far-angle gathers after pre-stack angle gather secondary correction and the incident angle.

[0037] make:

[0038] a 1n =a' 1n b 1n =b'1n ;c 1n =c' 1n

[0039] a 1f =a' 1f b 1f =b' 1f ;c 1f =c' 1f (5)

[0040] Finally, the pre-stack gather data after secondary correction was obtained.

[0041] Secondly, the present invention provides an electronic device, the electronic device comprising:

[0042] At least one processor; and,

[0043] A memory communicatively connected to the at least one processor; wherein,

[0044] The memory stores instructions that can be executed by the at least one processor to enable the at least one processor to perform the pre-stack angle gather amplitude correction method based on AVO forward modeling as described in the first aspect.

[0045] Thirdly, the present invention proposes a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the pre-stack angle gather amplitude correction method based on AVO forward modeling as described in the first aspect.

[0046] Fourthly, this invention proposes a pre-stack angle gather amplitude correction device based on AVO forward modeling, comprising:

[0047] The forward gather generation module is used to generate AVO forward gathers based on logging data and wavelets from typical wells in the study area.

[0048] The AVO feature analysis module is used to compare the reservoir AVO features of pre-stack angle gathers near the well with those of the generated forward-modeled gathers, and to clarify the angle stacking range of some angle gather data for pre-stack inversion.

[0049] The gather amplitude correction module is used to set template gathers for pre-stack gather data with forward modeling gathers as a reference, and to correct the amplitude energy value and amplitude fitting trend of some angle gather data that are not template gathers, so as to improve the quality of some angle gathers.

[0050] The beneficial effects of this invention are as follows:

[0051] This invention maps the relative mean amplitude energy and AVO fitting relationship of near-angle, mid-angle, and far-angle gathers of forward modeling gathers to pre-stack gathers, respectively, and performs secondary correction on the near-angle, mid-angle, and far-angle gathers of pre-stack gathers. This can greatly reduce various problems such as weak near-angle and far-angle amplitude energy and uneven gather energy that often exist in pre-stack gathers after conventional processing, and effectively improve the consistency of near-angle, mid-angle, and far-angle gathers, thereby providing a higher quality data foundation for pre-stack inversion.

[0052] The system of the present invention has 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

[0053] The above and other objects, features and advantages of the present invention will become more apparent from the accompanying drawings, in which like reference numerals generally denote like parts.

[0054] Figure 1 The diagram illustrates the steps of a pre-stack angle gather amplitude correction method based on AVO forward modeling according to the present invention.

[0055] Figure 2a and Figure 2b These are pre-stack angle sets and forward set sets, respectively.

[0056] Figure 3a and Figure 3b The AVO feature analysis results are shown for pre-stack trace sets and forward trace sets, respectively.

[0057] Figure 4a and Figure 4b The waveforms of the data before and after correction are displayed respectively.

[0058] Figure 5a and Figure 5b These are the pre-stack inversion results for the data before and after correction, respectively. Detailed Implementation

[0059] To address the current limitations of targeted pre-stack angle gather amplitude correction processing and its failure to consider the quality requirements of some angle gather data in pre-stack inversion, this invention proposes a pre-stack angle gather amplitude correction method and apparatus based on AVO forward modeling. By comparing and analyzing the AVO characteristics of pre-stack angle gathers and forward modeling gathers, the relative amplitude energy relationships and AVO fitting relationships of near-angle, mid-angle, and far-angle gather data from forward modeling gathers are mapped to pre-stack angle gathers, respectively. The near-angle, mid-angle, and far-angle gather data of pre-stack angle gathers are then corrected to achieve gather optimization.

[0060] The invention will now be described in more detail with reference to the accompanying drawings. While preferred embodiments of the invention are shown in the drawings, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that the invention will be thorough and complete, and will fully convey the scope of the invention to those skilled in the art.

[0061] Example 1

[0062] like Figure 1 As shown, this embodiment provides a pre-stack angle gather amplitude correction method based on AVO forward modeling, including:

[0063] S1: AVO forward lookup generated based on logging data and wavelet generation from typical wells in the study area;

[0064] Specifically, this step involves selecting appropriate wavelets based on the P-wave velocity and density curves of typical wells in the work area, performing synthetic recording and fine calibration to obtain the corresponding time-depth relationship, and then calculating the corresponding reflection coefficient based on the Zoeppritz equation using the shear wave velocity and density, and selecting appropriate wavelets to generate AVO forward modeling gathers.

[0065] S2: Compare the reservoir section AVO characteristics of the pre-stack angle gathers near the well with the generated forward-modeled gathers to clarify the angle stacking range of some angle gather data for pre-stack inversion;

[0066] This step combines well-side angle gathers with the generated forward-modeled gathers to perform AVO characteristic analysis on the reservoir section, clarifying the AVO type and amplitude scatter distribution trend of the reservoir section. Furthermore, by combining the effective angle range of the pre-stack angle gathers, the angle stacking range of some angle gather data for pre-stack inversion is determined. The angle stacking range of some angle gather data includes: the stacking range of near-angle gather data, the stacking range of mid-angle gather data, and the stacking range of far-angle gather data.

[0067] Specifically, by combining the well-side angle gathers with the forward-modeling gathers generated in step S1, AVO characteristic analysis is performed on the reservoir section to clarify the AVO type and amplitude scatter distribution trend of the reservoir section. In addition, by combining the effective angle range of the pre-stack angle gathers, the angle superposition range of some angle (usually three) gather data for pre-stack inversion is clarified, namely the superposition range of near-angle gather data, the superposition range of mid-angle gather data, and the superposition range of far-angle gather data.

[0068] S3: Using forward modeling gathers as a reference, a template gather is set for pre-stack gather data. Amplitude energy value correction and amplitude-as-incident-angle fitting trend correction are performed on some angle gather data that are not template gathers to improve the quality of some angle gathers.

[0069] The intermediate angle gather data is set as the template gather data for pre-stack gather data; the non-template gather data includes near angle gather data and far angle gather data.

[0070] This step specifically includes:

[0071] S301: Amplitude energy value correction, as detailed below:

[0072] The near-angle gather, intermediate-angle gather, and far-angle gather of the pre-stack angle gather in step S2 are respectively denoted as O. n O m and O f Let F be the near-angle, mid-angle, and far-angle sets of the corresponding orthogonal set. n F m and F f ;

[0073] Then count O respectively n O m O f F n F m F f The average amplitude energy values ​​are denoted as constants. and

[0074] Choose the template trace for the pre-stack trace set, typically the mid-angle trace set, and let:

[0075]

[0076] in and It is also a constant, representing the average amplitude energy of the near-angle and far-angle gathers after one correction of the pre-stack angle gathers;

[0077] Then, the near-angle and far-angle gathers of the pre-stack angle gathers before correction are multiplied by the variation coefficient of the average amplitude energy to obtain the near-angle and far-angle gathers after amplitude energy value correction, i.e.:

[0078]

[0079] Among them O' n O' f These are the near-angle gather and far-angle gather after amplitude energy value correction, respectively.

[0080] Therefore, in the pre-stack gather data after one correction, the near-angle, intermediate-angle, and far-angle gathers are respectively O' n O m O' f If the near, middle, and far angles of the orthogonal set remain unchanged, is it still F? n F m F f .

[0081] Optionally, amplitude fitting trend correction is performed on a portion of the non-template trace angle gather data, including:

[0082] S302: Amplitude fitting trend correction with incident angle, as detailed below:

[0083] Next, the amplitude fitting trend is corrected as a function of the incident angle. Based on the amplitude variation trend of near-angle, mid-angle, and far-angle gathers in the pre-stack gathers and forward modeling gathers after the first correction, a second fitting is performed, and the following relationship can be obtained:

[0084] O' n =a 1n x 2 +b 1n x+c 1n

[0085] O m =a 1m x 2 +b 1m x+c 1m

[0086] O' f =a 1f x 2 +b 1f x+c 1f

[0087] F n =a 2n x 2 +b 2n x+c 2n

[0088] F m =a 2m x 2 +b 2m x+c 2m

[0089] F f =a 2f x 2 +b 2f x+c 2f (3)

[0090] Where x is the angle, a 1n b 1n c 1n a 1m b 1m c 1m a 1f b 1f c 1f and a 2n b 2n c 2n a 2m b 2m c 2m a 2f b 2f c 2f All are constants;

[0091] In the near-angle, mid-angle, and far-angle gathers after one correction, the gathers with higher amplitude-to-incident-angle fitting coefficients and better consistency with forward-modeling gathers are selected as template gathers. Taking the mid-angle gather as an example, let:

[0092]

[0093] Where a' 1n b' 1n c' 1n and a' 1f b' 1f c' 1f is a constant, and represents the coefficients of the quadratic fitting relationship between the amplitude of near-angle and far-angle gathers after pre-stack angle gather secondary correction and the incident angle.

[0094] Final command:

[0095] a 1n =a' 1n b 1n =b' 1n ;c 1n =c' 1n

[0096] a 1f =a' 1fb 1f =b' 1f ;c 1f =c' 1f (5)

[0097] Finally, we can obtain the pre-stack gather data after secondary correction, which is the gather required after correction.

[0098] It should be noted that this invention focuses on the content related to gather amplitude energy correction. If the pre-stack gather still has problems such as low signal-to-noise ratio and residual time difference, further data processing is required by combining noise suppression and time difference correction methods.

[0099] This method can effectively improve the consistency of near-angle, mid-angle, and far-angle gather data, meet the quality requirements of pre-stack inversion for some angle gather data, improve the accuracy of pre-stack inversion, solve the amplitude energy problem of pre-stack angle gathers, and help improve the quality of pre-stack gathers and thus improve the inversion accuracy without reprocessing the data.

[0100] Example 2

[0101] Taking a specific set of data as an example, the pre-stack angle gather amplitude correction method based on AVO forward modeling of this invention is used to correct the data, as detailed below:

[0102] First, typical well-matrix trace sets from the study area are extracted and compared with the generated forward trace sets, such as... Figure 2a and Figure 2b As shown, the waveform characteristics of the two are quite consistent, and the effective angle range of the pre-stack gather is 3-32 degrees.

[0103] Select reservoir section ( Figure 2a and Figure 2b AVO analysis was performed at the location indicated by the blue line in the middle, and the results are as follows: Figure 3a and Figure 3b As shown in the figure, the reservoir segment exhibits Type II AVO characteristics. Based on the amplitude scatter distribution trend and combined with the effective angle range of the pre-stack gathers, the original gather data at 3-13 degrees are classified as near-angle gathers, 13-23 degrees as mid-angle gathers, and 23-32 degrees as far-angle gathers. The corresponding data ranges are... Figure 2a and Figure 2b The black, blue, and red areas in the middle remain consistent.

[0104] Based on the AVO characteristics of the gathers, the mid-angle gathers of the pre-stack gathers have the highest convergence of amplitude scatter points and the most stable amplitude energy. Therefore, the mid-angle gathers are used as template gathers, and the amplitude energy value is corrected and the amplitude fitting trend with the incident angle is corrected according to the method of this invention.

[0105] After calibration, the calibrated near-angle, mid-angle, and far-angle gathers are superimposed, and the waveform display results are as follows. Figure 4b As shown in the figure, the black line represents the near-angle gather stack, the blue line represents the mid-angle gather stack, and the red line represents the far-angle gather stack. It can be seen from the figure that the corrected data, compared to the uncorrected data (…),… Figure 4a The waveform characteristics of the near, medium, and far-angle gather stacks are significantly more consistent, and the amplitude energy of the three is more uniform. This proves that the amplitude correction method of the present invention can solve the amplitude energy problem and the AVO fitting trend problem of the gathers.

[0106] Finally, pre-stack inversion was performed based on the near-angle, mid-angle, and far-angle gather data before and after correction. The inversion results are as follows: Figure 5a and Figure 5b As shown. From Figure 5b As can be seen, the accuracy of the pre-stack inversion results (VP / VS) based on the corrected data is significantly higher than that of the inversion results based on the uncorrected data. Figure 5a The corrected inversion results not only have a higher degree of agreement with the well data, but also a higher signal-to-noise ratio and better lateral continuity. Furthermore, the provenance direction in the study area is from well4 to well1, meaning that well4 is closest to the provenance. Therefore, the sand bodies near well4 should be more continuous, and the pre-stack inversion results based on the corrected data are more consistent with this geological understanding.

[0107] The above examples demonstrate that this method can effectively solve the amplitude energy problem of pre-stack gathers, meet the quality requirements of pre-stack inversion for some angle gather data, and thus improve inversion accuracy.

[0108] Example 3

[0109] This embodiment provides a pre-stack angle gather amplitude correction device based on AVO forward modeling, including:

[0110] The forward gather generation module is used to generate AVO forward gathers based on logging data and wavelets from typical wells in the study area.

[0111] The AVO feature analysis module is used to compare the reservoir AVO features of pre-stack angle gathers near the well with those of the generated forward-modeled gathers, and to clarify the angle stacking range of some angle gather data for pre-stack inversion.

[0112] The gather amplitude correction module is used to set template gathers for pre-stack gather data with forward modeling gathers as a reference, and to correct the amplitude energy value and amplitude fitting trend of some angle gather data that are not template gathers, so as to improve the quality of some angle gathers.

[0113] The specific functions of each module in this embodiment are as described in Embodiment 1, and will not be repeated here.

[0114] Example 4

[0115] This embodiment provides an electronic device, the electronic device comprising:

[0116] At least one processor; and,

[0117] A memory communicatively connected to the at least one processor; wherein,

[0118] 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 angle gather amplitude correction method based on AVO forward modeling as described in the above embodiments.

[0119] An electronic device according to embodiments of the present disclosure includes a memory and a processor. The 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.

[0120] 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.

[0121] 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.

[0122] For a detailed description of this embodiment, please refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here.

[0123] Example 5

[0124] This embodiment provides a non-transitory computer-readable storage medium that stores computer instructions for causing a computer to execute the pre-stack angle gather amplitude correction method based on AVO forward modeling described in the above embodiment.

[0125] 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.

[0126] 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).

[0127] 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 angle gather amplitude correction based on AVO forward modeling, characterized in that, include: Based on logging data from typical wells in the study area and wavelet-generated AVO forward set; By comparing the reservoir AVO characteristics of pre-stack angle gathers near the well with those of the generated forward-modeled gathers, the angle stacking range of some angle gather data for pre-stack inversion is clarified. Using forward modeling gathers as a reference, template gathers are set up for pre-stack gather data. Amplitude energy value correction and amplitude-as-incident-angle fitting trend correction are performed on some angle gather data that are not template gathers to improve the quality of some angle gathers.

2. The method according to claim 1, characterized in that, The well logging data and wavelet-generated AVO forward lookup based on typical wells in the study area include: Based on the P-wave velocity and density curves of typical wells in the work area, a suitable wavelet is selected for synthetic recording and fine calibration to obtain the corresponding time-depth relationship. Then, combined with the S-wave velocity and density, the corresponding reflection coefficient is calculated based on the Zoeppritz equation, and a suitable wavelet is selected to generate AVO forward modeling gathers.

3. The method according to claim 1, characterized in that, The comparison of reservoir interval AVO characteristics between pre-stack angle gathers near the well and the generated forward-modeled gathers clarifies the angle stacking range of some angle gather data for pre-stack inversion, including: By combining the well-side angle gathers with the generated forward-modeled gathers, AVO characteristic analysis is performed on the reservoir section to clarify the AVO type and amplitude scatter distribution trend of the reservoir section. In addition, by combining the effective angle range of the pre-stack angle gathers, the angle superposition range of some angle gather data for pre-stack inversion is clarified.

4. The method according to claim 3, characterized in that, The angular overlay range of the partial angle gather data includes: the overlay range of near-angle gather data, the overlay range of medium-angle gather data, and the overlay range of far-angle gather data.

5. The method according to claim 4, characterized in that, The mid-angle gather data is set as the template gather for the pre-stack gather data; The non-template trace partial angle gather data includes: near angle gather data and far angle gather data.

6. The method according to claim 5, characterized in that, The amplitude energy value correction for the partial angle gather data of non-template traces includes: The near-angle gather, intermediate-angle gather, and far-angle gather of the pre-stack angle gather are denoted as O. n O m and O f Let F be the near-angle, mid-angle, and far-angle sets of the corresponding orthogonal set. n F m and F f ; Statistical analysis of O n O m O f F n F m F f The average amplitude energy value is denoted as . and Choose the mid-angle gather of the pre-stack angle gather as the template gather, and let: in and This represents the average amplitude energy of the near-angle and far-angle gathers after the first correction of the pre-stack angle gathers. Multiplying the near-angle and far-angle gathers from the pre-stack angle gathers before correction by the variation coefficient of the average amplitude energy, we obtain the near-angle and far-angle gathers after amplitude energy correction, i.e.: Among them O' n O' f These are the near-angle gather and far-angle gather after amplitude energy value correction, respectively.

7. The method according to claim 6, characterized in that, Amplitude fitting trend correction is performed on partial angle gather data of non-template traces, including: Based on the amplitude variation trends of near-angle, mid-angle, and far-angle gathers in the pre-stack gathers and forward modeling gathers after first correction, a second fitting was performed to obtain the following relationship: O' n =a 1n x 2 +b 1n x+c 1n O m =a 1m x 2 +b 1m x+c 1m O' f =a 1f x 2 +b 1f x+c 1f F n =a 2n x 2 +b 2n x+c 2n F m =a 2m x 2 +b 2m x+c 2m F f =a 2f x 2 +b 2f x+c 2f (3) Where x is the angle, a 1n b 1n c 1n a 1m b 1m c 1m a 1f b 1f c 1f and a 2n b 2n c 2n a 2m b 2m c 2m a 2f b 2f c 2f All are constants; From the near-angle, intermediate-angle, and far-angle gathers after one correction, the intermediate-angle gather with a higher amplitude-to-incident-angle fitting coefficient and better consistency with the forward-modeling gathers is selected as the template gather, let: Where a' 1n b' 1n c' 1n and a' 1f b' 1f c' 1f is a constant, and represents the coefficients of the quadratic fitting relationship between the amplitude of near-angle and far-angle gathers after pre-stack angle gather secondary correction and the incident angle. make: a 1n =a' 1n ;b 1n =b' 1n ;c 1n =c' 1n a 1f =a' 1f ;b 1f =b' 1f ;c 1f =c' 1f (5) Finally, the pre-stack gather data after secondary correction was obtained.

8. 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 angle gather amplitude correction method based on AVO forward modeling as described in any one of claims 1-7.

9. A non-transitory computer-readable storage medium, characterized in that, The non-transitory computer-readable storage medium stores computer instructions for causing a computer to perform the pre-stack angle gather amplitude correction method based on AVO forward modeling as described in any one of claims 1-7.

10. A pre-stack angle gather amplitude correction device based on AVO forward modeling, characterized in that, include: The forward gather generation module is used to generate AVO forward gathers based on logging data and wavelets from typical wells in the study area. The AVO feature analysis module is used to compare the reservoir AVO features of pre-stack angle gathers near the well with those of the generated forward-modeled gathers, and to clarify the angle stacking range of some angle gather data for pre-stack inversion. The gather amplitude correction module is used to set template gathers for pre-stack gather data with forward modeling gathers as a reference, and to correct the amplitude energy value and amplitude fitting trend of some angle gather data that are not template gathers, so as to improve the quality of some angle gathers.

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