A method, apparatus and related device for determining a seismic data migration profile

Abstract

The application discloses a method, device and related equipment for determining a seismic data migration profile, and the method comprises the following steps: screening discrete diffraction points at a preset interval in a velocity field model constructed by seismic data, and extracting a root mean square amplitude value of the screened discrete diffraction points based on a point spread function determined by the screened discrete diffraction points, so as to determine an amplitude distribution of each of the screened discrete diffraction points; performing interpolation processing on the amplitude of each of the screened discrete diffraction points based on a preset interpolation algorithm, so as to determine a global amplitude distribution of all the discrete diffraction points; determining a regularization operator based on the global amplitude distribution of all the discrete diffraction points; and performing regularization processing on a gradient field determined by the seismic data based on the regularization operator, so as to determine a migration profile corresponding to the seismic data. The point spread function is used to analyze illumination of an imaging space, and a regularization operator for the imaging space is generated to perform regularization processing, so that a least square migration objective function converges.

Description

Technical Field

[0001] This invention relates to the field of seismic data processing technology, and in particular to a method, apparatus, and related equipment for determining seismic data migration profiles. Background Technology

[0002] One of the important purposes of seismic data processing is to obtain high-quality depth domain images through depth migration. Least squares depth migration is to obtain the subsurface reflection coefficient model by iteratively solving the error between forward modeling data and observation data. The process is to find the optimal migration profile so that the seismic record synthesized by the inverse migration is closest to the real seismic record.

[0003] However, due to factors such as the complexity of the underground velocity model, uneven deployment of the observation system, insufficient illumination, uneven illumination of the migration image caused by energy dissipation during wave propagation, and amplitude processing errors in the time domain, the energy distribution of the obtained migration image (i.e., the initial reflection coefficient of the least squares migration iteration) is unreasonable. This makes the migration operator and the inverse migration operator not strictly inverse operators, thus causing the least squares migration iteration objective function to fail to converge. Summary of the Invention

[0004] The inventors discovered that traditional techniques use the dot-test method to test the offset operator and its self-adjoint operator. Only if the adjoint operator passes the test can the inversion process converge. However, the convergence speed is slow and convergence is not guaranteed to succeed.

[0005] In view of the above problems, the present invention is proposed to provide a method, apparatus and related equipment for determining seismic data migration profiles that overcomes or at least partially solves the above problems.

[0006] In a first aspect, embodiments of the present invention provide a method for determining seismic data migration profiles, characterized in that it includes:

[0007] Discrete diffraction points are selected at preset intervals in the velocity field model constructed from seismic data, and the root mean square amplitude value of the selected discrete diffraction points is extracted based on the point spread function determined by the selected discrete diffraction points to determine the amplitude distribution of each selected discrete diffraction point.

[0008] The amplitude of each discrete diffraction point selected is interpolated based on a preset interpolation algorithm to determine the global amplitude distribution of all discrete diffraction points.

[0009] Based on the global amplitude distribution of all discrete diffraction points, the regularization operator is determined.

[0010] The gradient field determined from the seismic data is regularized based on the regularization operator to determine the migration profile corresponding to the seismic data.

[0011] Optionally, before extracting the root mean square amplitude values ​​of the selected discrete diffraction points, the process may further include:

[0012] A velocity field model is constructed based on the acquired seismic data;

[0013] Based on the velocity field model, several discrete diffraction points are selected according to a preset interval;

[0014] The point spread function is determined based on a selection of discrete diffraction points.

[0015] Optionally, determining the point spread function based on a selection of discrete diffraction points may include:

[0016] The shot gather seismic data are obtained by performing offset calculations on a number of selected discrete diffraction points.

[0017] The shot gather seismic data is subjected to depth domain migration imaging to obtain the point spread function of the diffraction point.

[0018] Optionally, before constructing the velocity field model based on the acquired seismic data, the process may further include: preprocessing the acquired seismic data;

[0019] The preprocessing includes at least one of the following: static correction, noise reduction, and energy compensation.

[0020] Optionally, before performing regularization processing on the gradient field determined from the seismic data based on the regularization operator, the process may further include:

[0021] Using conventional migration profiles as reflection coefficients for seismic wave propagation in the seismic data, inverse migration processing is performed to obtain inverse migration synthetic seismic records.

[0022] The acquired seismic data is matched with the inverse-migration synthetic seismic record to determine the residuals;

[0023] The gradient field is determined based on the residual and the offset operator.

[0024] Optionally, after performing regularization processing on the gradient field determined from the seismic data based on the regularization operator, the process may further include:

[0025] The update step size is determined based on the reflection inversion method to update the reflection coefficients and determine the migration profile corresponding to the seismic data.

[0026] Optionally, the method may further include:

[0027] The inverse migration processing step, the inverse migration synthesis step, and the regularization processing step are repeated based on the updated reflection coefficients to enable the inversion to converge and determine the migration profile corresponding to the seismic data.

[0028] Optionally, the step of interpolating the amplitude of each selected discrete diffraction point based on a preset interpolation algorithm to determine the global amplitude distribution of all discrete diffraction points may include:

[0029] The amplitude of each discrete diffraction point selected is interpolated using bilinear interpolation to determine the global amplitude distribution of all discrete diffraction points based on a defined velocity field model and observation system.

[0030] Optionally, determining the regularization operator based on the global amplitude distribution of all discrete diffraction points may include:

[0031] The regularization operator is determined based on the reciprocal of the amplitude of all discrete diffraction points.

[0032] Secondly, embodiments of the present invention provide a seismic data depth domain imaging method, which may include:

[0033] The migration profile determined based on the seismic data migration profile determination method described in the first aspect is used to generate an inverse migration synthetic depth domain image.

[0034] Thirdly, embodiments of the present invention provide a device for determining seismic data migration profiles, which may include:

[0035] The extraction module is used to filter discrete diffraction points in the velocity field model constructed from seismic data at preset intervals, and extract the root mean square amplitude value of the filtered discrete diffraction points based on the point spread function determined by the filtered discrete diffraction points, so as to determine the amplitude distribution of each filtered discrete diffraction point.

[0036] An interpolation processing module is used to interpolate the amplitude of each of the selected discrete diffraction points based on a preset interpolation algorithm, so as to determine the global amplitude distribution of all discrete diffraction points.

[0037] The regularization operator determination module determines the regularization operator based on the global amplitude distribution of all discrete diffraction points;

[0038] The regularization processing module performs regularization processing on the gradient field determined from the seismic data based on the regularization operator to determine the migration profile corresponding to the seismic data.

[0039] Optionally, the device may also include:

[0040] The preprocessing module is used to preprocess the acquired seismic data;

[0041] The building block is used to construct velocity field models based on preprocessed seismic data;

[0042] The filtering module is used to filter a number of discrete diffraction points according to a preset interval based on the velocity field model.

[0043] A point spread function determination module is used to determine the point spread function based on a selected set of discrete diffraction points;

[0044] The reverse migration processing module is used to perform reverse migration processing on the seismic data by using the conventional migration profile as the reflection coefficient of the seismic wave propagation to obtain the reverse migration synthetic seismic record.

[0045] The residual determination module is used to match the acquired seismic data with the inverse-migration synthetic seismic record to determine the residuals;

[0046] The gradient field determination module is used to determine the gradient field based on the residual and the offset operator;

[0047] The update module is used to determine the update step size based on the reflection inversion method in order to update the reflection coefficients;

[0048] An iterative module is used to repeat the inverse migration processing step, the inverse migration synthesis step, and the regularization processing step based on the updated reflection coefficients, so that the inversion can converge and determine the migration profile corresponding to the seismic data.

[0049] Fourthly, embodiments of the present invention provide a seismic data depth domain imaging device, which may include:

[0050] An imaging module is used to generate a reverse-migration synthetic depth domain image based on the migration profile determined by the seismic data migration profile determination method described in the first aspect.

[0051] Fifthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method for determining seismic data migration profiles as described in the first aspect, or the method for seismic data depth domain imaging as described in the second aspect.

[0052] In a sixth aspect, embodiments of the present invention provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, when the processor executes the program, it implements the method for determining seismic data migration profiles as described in the first aspect, or the method for seismic data depth domain imaging as described in the second aspect.

[0053] The beneficial effects of the above-described technical solutions provided in the embodiments of the present invention include at least the following:

[0054] This invention provides a method, apparatus, and related equipment for determining an migration profile. The method may include: filtering discrete diffraction points at preset intervals in a velocity field model constructed from seismic data; extracting the root mean square amplitude values ​​of the filtered discrete diffraction points based on a point spread function determined from the filtered discrete diffraction points to determine the amplitude distribution of each filtered discrete diffraction point; interpolating the amplitude of each filtered discrete diffraction point based on a preset interpolation algorithm to determine the global amplitude distribution of all discrete diffraction points; determining a regularization operator based on the global amplitude distribution of all discrete diffraction points; and regularizing the gradient field determined from the seismic data based on the regularization operator to determine the migration profile corresponding to the seismic data. This invention utilizes a point spread function to perform illumination analysis on the imaging space and generates a regularization operator for the imaging space. It regularizes the reflection coefficients of the least squares input and applies it to the gradient field in each iteration, ensuring that the algorithm meets the point test conditions of the forward and inverse operators and accelerating its convergence, thereby causing the least squares migration objective function to converge.

[0055] Furthermore, regularization is calculated directly on the migrated image. Compared with amplitude processing based on shot gather seismic data, the embodiments of the present invention have less computation, less storage, lower cost, and higher efficiency, and only need to be calculated once, which significantly improves the efficiency of least squares migration.

[0056] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0057] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0058] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0059] Figure 1 This is a flowchart illustrating the method for determining seismic data migration profiles provided in an embodiment of the present invention.

[0060] Figure 2 This is a flowchart illustrating a specific method for determining seismic data migration profiles provided in an embodiment of the present invention.

[0061] Figure 3 This is a schematic diagram of discrete diffraction points with equal intervals provided in an embodiment of the present invention.

[0062] Figure 4 This is a point spread function (PSF) distribution diagram of an underground diffraction point provided in an embodiment of the present invention;

[0063] Figure 5 This is a discrete diffraction point amplitude distribution diagram provided in an embodiment of the present invention;

[0064] Figure 6 This is a schematic diagram of bilinear interpolation provided in an embodiment of the present invention;

[0065] Figure 7 This is an amplitude distribution diagram of discrete diffraction points after interpolation processing, provided in an embodiment of the present invention.

[0066] Figure 8 This is a depth-domain offset image obtained based on a reflection system model, as provided in this embodiment of the invention.

[0067] Figure 9 This is a depth-domain offset image obtained based on conventional one-way wave offset provided in an embodiment of the present invention;

[0068] Figure 10 This is a depth-domain offset image obtained based on least-squares offset provided in an embodiment of the present invention;

[0069] Figure 11 This is a schematic diagram of the structure of the device for determining seismic data migration profiles provided in an embodiment of the present invention. Detailed Implementation

[0070] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0071] This invention provides a method for determining seismic data migration profiles, referring to... Figure 1 As shown, the following steps may be included:

[0072] Step S11: In the velocity field model constructed from seismic data, discrete diffraction points are selected at preset intervals, and the root mean square amplitude value of the selected discrete diffraction points is extracted based on the point spread function determined by the selected discrete diffraction points, so as to determine the amplitude distribution of each selected discrete diffraction point.

[0073] Step S12: Based on the preset interpolation algorithm, the amplitude of each selected discrete diffraction point is interpolated to determine the global amplitude distribution of all discrete diffraction points.

[0074] Step S13: Determine the regularization operator based on the global amplitude distribution of all discrete diffraction points.

[0075] Step S14: Regularize the gradient field determined by the seismic data based on the regularization operator to determine the migration profile corresponding to the seismic data.

[0076] The method provided in this embodiment of the invention utilizes a point spread function to perform illumination analysis on the imaging space and generates a regularization operator for the imaging space. This regularization process is applied to the reflection coefficients of the least squares input, and the gradient field is applied to each iteration. This ensures that the algorithm satisfies the point test conditions of the forward and inverse operators, accelerating its convergence and thus leading to the convergence of the least squares migration objective function. Furthermore, the regularization is calculated directly on the migrated image. Compared to amplitude processing based on shot gather seismic data, this embodiment of the invention requires less computation, less storage, lower cost, and higher efficiency, and only needs to be calculated once, significantly improving the efficiency of least squares migration.

[0077] In one specific embodiment, refer to Figure 2 As shown, the method for determining the aforementioned seismic data migration profile may specifically include the following steps:

[0078] Step S201: Preprocess the acquired seismic data.

[0079] The preprocessing described in this step may include at least one of the following: static correction, denoising, and energy compensation. Preprocessing the acquired seismic data facilitates subsequent data applications. In this embodiment of the invention, two-dimensional Marmousi seismic data can be used for processing to determine its offset profile.

[0080] Step S202: Construct a velocity field model based on the preprocessed seismic data.

[0081] In this step, a reasonable velocity field model is established, and then a depth domain offset image is obtained through depth domain offset imaging processing, followed by least squares offset processing.

[0082]

[0083] Where L is the inverse offset operator, L * Here, d is the migration operator, m is the reflection coefficient model, and d is the seismic data. The left side of the formula represents the dot product of the seismic data obtained from the inverse migration and the input seismic data, while the right side represents the dot product of the reflection coefficient and the migrated image. The point tests of the algorithm's forward and inverse operators are valid and are necessary conditions for the convergence of the least squares objective function.

[0084] Step S203: Based on the velocity field model, select several discrete diffraction points according to the preset interval.

[0085] In this step, the preset interval can be 40 points at equal intervals to select some discrete diffraction points, which are regarded as the reflection coefficient of seismic wave propagation (the value of the location outside the discrete points is set to 0), for example, referring to Figure 3 As shown, 40 points selected by equal grid intervals are used as discrete diffraction points.

[0086] Step S204: Determine the point spread function based on the selected discrete diffraction points.

[0087] Specifically, this step may include the following steps: obtaining shot gather seismic data by performing migration operations on several selected discrete diffraction points: The shot gather seismic data was subjected to depth-domain migration imaging to obtain the point spread function (PSF) of the diffraction points: Reference Figure 4 The figure shown is a point spread function (PSF) distribution diagram of an underground diffraction point provided in an embodiment of the present invention.

[0088] Step S205: Extract the root mean square amplitude value of the discrete diffraction points selected in step S203 based on the point spread function determined in step S204, so as to determine the amplitude distribution of each selected discrete diffraction point.

[0089] In this step, the above root mean square amplitude value is extracted. (Where i and j represent the spatial positions of the selected points (i, j), and N represents the total number of points selected.) The amplitude distribution of the diffraction points is calculated based on the root mean square amplitude value. In this embodiment, diffraction points within an 8-neighborhood or a 24-neighborhood can be used. (Refer to...) Figure 5 The figure shown is a distribution diagram of the amplitude of discrete diffraction points.

[0090] Step S206: Based on the preset interpolation algorithm, the amplitude of each selected discrete diffraction point is interpolated to determine the global amplitude distribution of all discrete diffraction points.

[0091] Specifically, the amplitude of each selected discrete diffraction point is interpolated based on bilinear interpolation to determine the global amplitude distribution of all discrete diffraction points under a defined velocity field model and observation system.

[0092] The above double interpolation formula in this embodiment can be:

[0093]

[0094] Among them, reference Figure 6 The diagram shown illustrates bilinear interpolation, f(Q) 11 f(Q) 21 f(Q) 12 f(Q) 22 () represents the point values ​​of the four surrounding points. (Refer to...)Figure 7 The figure shown is an amplitude distribution diagram of discrete diffraction points after interpolation.

[0095] Step S207: Determine the regularization operator based on the global amplitude distribution of all discrete diffraction points.

[0096] Specifically, the regularization operator is determined based on the reciprocal of the amplitude of all discrete diffraction points.

[0097] Step S208: Using the conventional migration profile as the reflection coefficient of seismic wave propagation in the seismic data, perform inverse migration processing to obtain the inverse migration synthetic seismic record.

[0098] Step S209: Match the acquired seismic data with the inverse migration synthetic seismic record to determine the residuals.

[0099] Step S210: Determine the gradient field based on the residual and the offset operator.

[0100] The gradient field described above represents the update direction of the inversion.

[0101] Step S211: Regularize the gradient field determined from the seismic data based on the regularization operator.

[0102] The gradient field in step S210 is regularized using the regularization operator obtained in step S207.

[0103] Step S212: Determine the update step size based on the reflection inversion method to update the reflection coefficient.

[0104] This step uses an inversion method to determine the update step size and updates the reflection coefficient.

[0105] Step S213: Repeat the inverse migration processing step, inverse migration synthesis step, and regularization processing step based on the updated reflection coefficients to make the inversion converge and determine the migration profile corresponding to the seismic data.

[0106] This step involves repeating steps S208 to S212 until convergence.

[0107] The method provided in this embodiment of the invention satisfies the point test conditions of the forward and inverse operators of the least squares iteration algorithm, enabling the least squares objective function to converge. Furthermore, regularization is calculated directly on the offset image. Compared to amplitude processing based on shot gather data, this embodiment of the invention requires less computation, less storage, lower cost, and higher efficiency, and only needs to be calculated once.

[0108] Reference Figure 8 The Marmousi model shown is based on a depth-domain offset image obtained from a reflection system model. Figure 9The image shown is a depth-domain migration image obtained based on conventional one-way wave migration, and Figure 10 The depth domain migration image shown is based on least squares migration. It can be seen that the resolution of the least squares migration image is significantly higher than that of the one-way wave migration image.

[0109] Therefore, the gradient regularization method that enables the least squares migration objective function to converge directly regularizes its amplitude on the migration image. This method has low computational cost, is easy to implement, and only needs to be implemented once before the least squares migration begins, which significantly improves the efficiency of least squares migration.

[0110] Based on the same inventive concept, this invention provides a device for determining seismic data migration profiles, referring to... Figure 11 As shown, the device may include: an extraction module 111, an interpolation processing module 112, a regularization operator determination module 113, and a regularization processing module 114, and its working principle is as follows:

[0111] The extraction module 111 is used to filter discrete diffraction points in the velocity field model constructed from seismic data at preset intervals, and extract the root mean square amplitude value of the filtered discrete diffraction points based on the point spread function determined by the filtered discrete diffraction points, so as to determine the amplitude distribution of each filtered discrete diffraction point.

[0112] The interpolation processing module 112 is used to interpolate the amplitude of each selected discrete diffraction point based on a preset interpolation algorithm in order to determine the global amplitude distribution of all discrete diffraction points.

[0113] The regularization operator determination module 113 determines the regularization operator based on the global amplitude distribution of all discrete diffraction points;

[0114] The regularization processing module 114 performs regularization processing on the gradient field determined by the seismic data based on the regularization operator in order to determine the migration profile corresponding to the seismic data.

[0115] In an optional embodiment, the above-mentioned apparatus may further include: a preprocessing module 115, a construction module 116, a screening module 117, a point spread function determination module 118, an inverse offset processing module 119, a residual determination module 120, a gradient field determination module 121, an update module 122, and an iteration module 123, the working principle of which is as follows:

[0116] The preprocessing module 115 is used to preprocess the acquired seismic data;

[0117] Module 116 is used to construct a velocity field model based on preprocessed seismic data;

[0118] The filtering module 117 is used to filter a number of discrete diffraction points based on the velocity field model and according to a preset interval.

[0119] The point spread function determination module 118 is used to determine the point spread function based on a selection of discrete diffraction points;

[0120] The reverse migration processing module 119 is used to perform reverse migration processing on the conventional migration profile as the reflection coefficient of seismic wave propagation in the seismic data to obtain the reverse migration synthetic seismic record.

[0121] The residual determination module 120 is used to match the acquired seismic data with the inverse migration synthetic seismic record in order to determine the residuals;

[0122] The gradient field determination module 121 is used to determine the gradient field based on the residual and the offset operator;

[0123] The update module 122 is used to determine the update step size based on the reflection inversion method in order to update the reflection coefficient;

[0124] The iterative module 123 is used to repeat the inverse migration processing step, the inverse migration synthesis step, and the regularization processing step based on the updated reflection coefficients, so that the inversion can converge and determine the migration profile corresponding to the seismic data.

[0125] Based on the same inventive concept, this embodiment of the invention also provides a method for seismic data depth domain imaging, which may include: performing inverse migration to synthesize a depth domain image based on the migration profile determined by the above-mentioned method for determining seismic data migration profiles.

[0126] Based on the same inventive concept, this embodiment of the invention also provides a seismic data depth domain imaging device, which may include: an imaging module, which is used to perform inverse migration synthesis of a depth domain image based on the migration profile determined by the above-described method for determining seismic data migration profiles.

[0127] Based on the same inventive concept, this embodiment of the invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-mentioned method for determining seismic data migration profiles or the above-mentioned method for seismic data depth domain imaging.

[0128] Based on the same inventive concept, this embodiment of the invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the above-mentioned method for determining the migration profile of seismic data, or implements the above-mentioned method for depth domain imaging of seismic data.

[0129] This invention proposes a gradient field regularization method. It utilizes a point spread function to perform illumination analysis on the imaging space and generates a regularization operator for the imaging space. The reflection coefficients of the least squares input are pre-regularized, and the gradient field is applied to each iteration. This ensures the algorithm satisfies the point test conditions of the forward and inverse operators, accelerating its convergence and ultimately leading to the convergence of the least squares offset objective function.

[0130] The principles by which the above-mentioned devices, media, and related equipment in the embodiments of the present invention solve the problem are similar to those of the aforementioned methods. Therefore, their implementation can refer to the implementation of the aforementioned methods, and repeated details will not be repeated.

[0131] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0132] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0133] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0134] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxesFigure 1 The steps of the function specified in one or more boxes.

[0135] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for determining seismic data migration profiles, characterized in that, include: Discrete diffraction points are selected at preset intervals in the velocity field model constructed from seismic data, and the root mean square amplitude value of the selected discrete diffraction points is extracted based on the point spread function determined by the selected discrete diffraction points to determine the amplitude distribution of each selected discrete diffraction point. The amplitude of each discrete diffraction point selected is interpolated based on a preset interpolation algorithm to determine the global amplitude distribution of all discrete diffraction points. Based on the global amplitude distribution of all discrete diffraction points, the regularization operator is determined. The gradient field determined from the seismic data is regularized based on the regularization operator to determine the migration profile corresponding to the seismic data.

2. The method according to claim 1, characterized in that, Before extracting the root mean square amplitude values ​​of the selected discrete diffraction points, the method further includes: A velocity field model is constructed based on the acquired seismic data; Based on the velocity field model, several discrete diffraction points are selected according to a preset interval; The point spread function is determined based on a selection of discrete diffraction points.

3. The method according to claim 2, characterized in that, The determination of the point spread function based on a selection of discrete diffraction points includes: The shot gather seismic data are obtained by performing offset calculations on a number of selected discrete diffraction points. The shot gather seismic data is subjected to depth domain migration imaging to obtain the point spread function of the diffraction point.

4. The method according to claim 2, characterized in that, Before constructing the velocity field model based on the acquired seismic data, the process also includes: preprocessing the acquired seismic data; The preprocessing includes at least one of the following: static correction, noise reduction, and energy compensation.

5. The method according to claim 1, characterized in that, Before performing regularization processing on the gradient field determined from the seismic data based on the regularization operator, the method further includes: Using conventional migration profiles as reflection coefficients for seismic wave propagation in the seismic data, inverse migration processing is performed to obtain inverse migration synthetic seismic records. The acquired seismic data is matched with the inverse-migration synthetic seismic record to determine the residuals; The gradient field is determined based on the residual and the offset operator.

6. The method according to claim 1, characterized in that, After performing regularization processing on the gradient field determined from the seismic data based on the regularization operator, the process further includes: The update step size is determined based on the reflection inversion method to update the reflection coefficients and determine the migration profile corresponding to the seismic data.

7. The method according to claim 6, characterized in that, Also includes: The inverse migration processing step, the inverse migration synthesis step, and the regularization processing step are repeated based on the updated reflection coefficients to enable the inversion to converge and determine the migration profile corresponding to the seismic data.

8. The method according to any one of claims 1 to 7, characterized in that, The amplitude of each selected discrete diffraction point is interpolated using a preset interpolation algorithm to determine the global amplitude distribution of all discrete diffraction points, including: The amplitude of each discrete diffraction point selected is interpolated using bilinear interpolation to determine the global amplitude distribution of all discrete diffraction points based on a defined velocity field model and observation system.

9. The method according to any one of claims 1 to 7, characterized in that, The determination of the regularization operator based on the global amplitude distribution of all discrete diffraction points includes: The regularization operator is determined based on the reciprocal of the amplitude of all discrete diffraction points.

10. A method for depth domain imaging of seismic data, characterized in that, include: Based on the migration profile determined by the method for determining seismic data migration profiles according to any one of claims 1 to 9, an inverse migration synthesis depth domain image is generated.

11. A device for determining seismic data migration profiles, characterized in that, include: The extraction module is used to filter discrete diffraction points in the velocity field model constructed from seismic data at preset intervals, and extract the root mean square amplitude value of the filtered discrete diffraction points based on the point spread function determined by the filtered discrete diffraction points, so as to determine the amplitude distribution of each filtered discrete diffraction point. An interpolation processing module is used to interpolate the amplitude of each of the selected discrete diffraction points based on a preset interpolation algorithm, so as to determine the global amplitude distribution of all discrete diffraction points. The regularization operator determination module determines the regularization operator based on the global amplitude distribution of all discrete diffraction points; The regularization processing module performs regularization processing on the gradient field determined by the seismic data based on the regularization operator to determine the migration profile corresponding to the seismic data.

12. The apparatus according to claim 11, characterized in that, Also includes: The preprocessing module is used to preprocess the acquired seismic data; The building block is used to construct velocity field models based on preprocessed seismic data; The filtering module is used to filter a number of discrete diffraction points according to a preset interval based on the velocity field model. A point spread function determination module is used to determine the point spread function based on a selected set of discrete diffraction points; The reverse migration processing module is used to perform reverse migration processing on the seismic data by using the conventional migration profile as the reflection coefficient of the seismic wave propagation, so as to obtain the reverse migration synthetic seismic record. The residual determination module is used to match the acquired seismic data with the inverse-migration synthetic seismic record to determine the residuals; The gradient field determination module is used to determine the gradient field based on the residual and the offset operator; The update module is used to determine the update step size based on the reflection inversion method in order to update the reflection coefficients; An iterative module is used to repeat the inverse migration processing step, the inverse migration synthesis step, and the regularization processing step based on the updated reflection coefficients, so that the inversion can converge and determine the migration profile corresponding to the seismic data.

13. A seismic data depth domain imaging device, characterized in that, include: An imaging module is used to generate an inverse-migration synthetic depth domain image based on the migration profile determined by the method for determining seismic data migration profiles according to any one of claims 1 to 9.

14. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the program implements the method for determining seismic data migration profiles as described in any one of claims 1 to 9, or the method for seismic data depth domain imaging as described in claim 10.

15. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the method for determining seismic data migration profiles as described in any one of claims 1 to 9, or the method for seismic data depth domain imaging as described in claim 10.

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