Regularized seismic data volume determination method and device, equipment and medium
By setting interpolated seismic channels in the seismic data body and performing data block interpolation processing, the problems of insufficient sampling density and irregular data distribution are solved, and higher three-dimensional data prediction accuracy and regular data reliability are achieved.
Patent Information
- Application Number
- CN202311672893.X
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-12-07
- Publication Date
- 2025-06-10
AI Technical Summary
When processing economic three-dimensional seismic data, the prior art is limited by insufficient sampling density and irregular data distribution, resulting in poor seismic data processing results, and the existing interpolation methods have problems such as large calculation volume and poor practicality.
By obtaining the seismic data body after the target area is superimposed, multiple blank seismic channels are set equally apart in the data body as interpolated seismic channels, select data blocks of preset size and determine the interpolated data, and finally fuse the interpolated data with the original seismic data body to form a regular seismic data body.
It improves the accuracy of three-dimensional data prediction, enhances the reliability of regularized data, prevents false frequency phenomena, and significantly improves the steep inclination effect of complex exploration areas.
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Figure CN120122147A_ABST
Abstract
Description
Technical Field
[0001] The present invention belongs to the technical field of geophysical exploration, and particularly relates to a method, device, equipment and medium for determining a regularized seismic data volume. Background Art
[0002] In the acquisition of economic three-dimensional seismic data, insufficient sampling density and irregular acquisition systems can cause many problems, which often seriously affect the final effect of seismic data processing. Whether it is land data or marine data, seismic acquisition is affected by various factors such as terrain and environment, and problems such as insufficient spatial sampling density, bad channels, and irregular data distribution are common. These problems cause serious interference to data processing and affect the seismic data processing effect and geological interpretation direction.
[0003] In response to these problems, scholars at home and abroad have proposed methods for seismic trace interpolation and encryption, which are currently widely used in actual seismic data. Seismic trace interpolation can be used to increase the spatial sampling rate, prevent the occurrence of migration dispersion, and improve the signal-to-noise ratio. After seismic trace interpolation, the data volume doubles, and geophysical information such as velocity, amplitude, and frequency becomes more abundant. Seismic trace interpolation can basically achieve the geological effect of dense field sampling. Since seismic trace interpolation overcomes spatial aliasing, its geophysical information more truly reflects the geophysical characteristics of underground geological bodies, which is more conducive to structural interpretation and seismic stratigraphy research.
[0004] Scholars at home and abroad have proposed various regularization methods for irregularly acquired data. The T-X prediction error filtering interpolation method proposed by Claerbout and the anti-aliasing F-K domain seismic trace interpolation method (UFKI) proposed by Gulunay have become commonly used seismic trace interpolation methods, but these methods all have their own problems. Among them, although the Sinc seismic trace interpolation method is fast and easy to implement when performing seismic trace interpolation, it cannot correctly interpolate seismic traces with spatial aliasing. Although the F-X domain seismic trace interpolation method of Spitz and the T-X domain prediction error filtering interpolation method of Claerbout can correctly interpolate seismic traces with spatial aliasing, their computational complexity is extremely large, greatly reducing their usability in actual data. The anti-aliasing F-K domain seismic trace interpolation method (UFKI) proposed by Gulunay can correctly interpolate seismic traces with spatial aliasing, and has a fast operation speed and high efficiency. However, its interpolation coefficient cannot be any integer, nor can it perform seismic trace interpolation on three-dimensional seismic data, which greatly reduces its practicality. Summary of the Invention
[0005] To solve the above technical problems, the present invention provides a method, apparatus, device, and medium for determining a regularized seismic data volume. The present application obtains the superimposed seismic data volume of the target area; equidistantly sets a plurality of blank seismic channels as interpolation seismic channels in the seismic data volume; selects data blocks of a preset size in the seismic data volume according to each interpolation seismic channel, where there is an overlapping area between the data blocks of two adjacent interpolation seismic channels; determines the interpolation data of each interpolation seismic channel according to each data block; and determines the regularized seismic data volume according to all the interpolation data and the seismic data volume. This improves the prediction accuracy of 3D data. By adopting the idea of data block overlapping, the reliability of regularization is improved, and the aliasing phenomenon is prevented. The effect of steep dips after regularization of complex exploration areas is significantly improved by this method.
[0006] To solve the above technical problems, the technical solution adopted by the present invention includes four aspects.
[0007] In a first aspect, a method for determining a regularized seismic data volume is provided, including: obtaining the superimposed seismic data volume of the target area; equidistantly setting a plurality of blank seismic channels as interpolation seismic channels in the seismic data volume; selecting data blocks of a preset size in the seismic data volume according to each interpolation seismic channel, where there is an overlapping area between the data blocks of two adjacent interpolation seismic channels; determining the interpolation data of each interpolation seismic channel according to each data block; and determining the regularized seismic data volume according to all the interpolation data and the seismic data volume.
[0008] In some embodiments, the step of selecting data blocks of a preset size in the seismic data volume according to each interpolation seismic channel includes: determining the central position of the data block according to the target interpolation seismic channel; obtaining a preset point range, line range, and time window range, where the point range, the line range, and the time window range are all greater than the distance between two adjacent interpolation seismic channels; and determining the data block according to the point range, the line range, the time window range, and the central position.
[0009] In some embodiments, the step of determining the interpolation data of each interpolation seismic channel according to each data block includes: performing Fourier transform on each seismic data trace in the data block to obtain a frequency domain data block; establishing a linear equation system of a half-step prediction operator according to the frequency domain data block; determining a forward prediction operator and a backward prediction operator according to the linear equation system; and determining the interpolation data according to the forward prediction operator and the backward prediction operator.
[0010] In some embodiments, determining the forward prediction operator and the backward prediction operator according to the system of linear equations includes: solving the system of linear equations by using the least squares method to obtain a forward half-step prediction operator and a backward half-step prediction operator; determining the forward prediction operator according to the forward half-step prediction operator; and determining the backward prediction operator according to the backward half-step prediction operator.
[0011] In some embodiments, determining the interpolation data according to the forward prediction operator and the backward prediction operator includes: performing convolution calculations on the forward prediction operator and the backward prediction operator respectively to obtain forward interpolation data and backward interpolation data; determining average interpolation data according to the forward interpolation data and the backward interpolation data; and performing an inverse Fourier transform on the average interpolation data to obtain the interpolation data in the spatio-temporal domain.
[0012] In some embodiments, determining the regularized seismic data volume according to all the interpolation data and the seismic data volume includes: interpolating all the interpolation data into corresponding interpolation seismic traces to form an interpolation data volume; and fusing the interpolation data volume with the seismic data volume to obtain the regularized seismic data volume.
[0013] In some embodiments, establishing a system of linear equations for the half-step prediction operator according to the frequency-domain data block includes: obtaining the seismic traces with values in the frequency-domain data block; and establishing the system of linear equations according to the seismic traces with values and the target seismic trace.
[0014] In a second aspect, the present application provides a device for determining a regularized seismic data volume, including: a first acquisition module configured to acquire a stacked seismic data volume of a target area; a first execution module configured to equidistantly set a plurality of blank seismic traces as interpolation seismic traces in the seismic data volume; a second execution module configured to select data blocks of a preset size in the seismic data volume according to each interpolation seismic trace, where there is an overlapping area between the data blocks of two adjacent interpolation seismic traces; a first determination module configured to determine the interpolation data of each interpolation seismic trace according to each data block; and a second determination module configured to determine the regularized seismic data volume according to all the interpolation data and the seismic data volume.
[0015] In a third aspect, the present application provides an electronic device, including: a memory and a processor, where a computer program is stored on the memory, and when the computer program is executed by the processor, it executes the method according to any one of the first aspect.
[0016] In a fourth aspect, the present application provides a storage medium storing a computer program that can be executed by one or more processors, and the computer program can be used to implement the method according to any one of the first aspect.
[0017] Advantages of the present invention: This application obtains the seismic data volume after superposition of the target area; sets a plurality of blank seismic traces at equal intervals in the seismic data volume as interpolation seismic traces; selects data blocks of a preset size in the seismic data volume according to each interpolation seismic trace, where there is an overlapping area between the data blocks of two adjacent interpolation seismic traces; determines the interpolation data of each interpolation seismic trace according to each data block; and determines the regularized seismic data volume according to all the interpolation data and the seismic data volume. The prediction accuracy of 3D data is improved. By adopting the idea of data block overlapping, the reliability of regularization is improved, and the aliasing phenomenon is prevented. The effect of steep dip angles after regularization of complex exploration areas by this method is significantly improved. BRIEF DESCRIPTION OF THE DRAWINGS
[0018] The scope of the present disclosure can be better understood by reading the following detailed description of exemplary embodiments in conjunction with the accompanying drawings. The accompanying drawings included are:
[0019] Figure 1 It is the overall flowchart of a method for determining a regularized seismic data volume provided by an embodiment of the present application;
[0020] Figure 2 It is the structural block diagram of a device for determining a regularized seismic data volume provided by an embodiment of the present application. DETAILED DESCRIPTION OF THE EMBODIMENTS
[0021] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. The described embodiments should not be regarded as limitations of the present application. All other embodiments obtained by those of ordinary skill in the art without creative efforts fall within the scope of protection of the present application.
[0022] In the following description, reference is made to "some embodiments", which describe a subset of all possible embodiments. However, it can be understood that "some embodiments" can be the same subset or different subsets of all possible embodiments, and can be combined with each other without conflict.
[0023] If similar descriptions such as "first / second / third" appear in the application documents, the following explanation is added. In the following description, the terms "first / second / third" only distinguish similar objects and do not represent a specific order for the objects. It can be understood that "first / second / third" can be interchanged with a specific order or sequence when allowed, so that the embodiments of the present application described here can be implemented in an order other than that illustrated or described here.
[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the technical field to which this application belongs. The terms used herein are for the purpose of describing embodiments of this application only and are not intended to limit this application.
[0025] Embodiment 1:
[0026] Existing methods for regularizing data volumes all have their respective problems. Among them, the Sinc seismic trace interpolation method is fast and easy to implement when performing seismic trace interpolation, but it cannot correctly interpolate seismic traces with spatial aliasing. Although methods such as Spitz's F-X domain seismic trace interpolation method and Claerbout's T-X domain prediction error filtering interpolation method can correctly interpolate seismic traces with spatial aliasing, these methods have extremely large computational amounts, greatly reducing their usability in actual data. The anti-aliasing F-K domain seismic trace interpolation method (UFKI) proposed by Gulunay can correctly interpolate seismic traces with spatial aliasing, and has a fast operation speed and high efficiency. However, its interpolation coefficients cannot be any integer, and it cannot perform seismic trace interpolation on 3D seismic data, which greatly reduces its practicality.
[0027] In view of the problems existing in the prior art, as Figure 1 shown, this application provides a method for determining a regularized seismic data volume. The method is applied to an electronic device, which can be a server, a mobile terminal, a computer, a cloud platform, etc. The functions implemented by the device data processing in the embodiments of this application can be realized by a processor of the electronic device calling program code. Among them, the program code can be stored in a computer storage medium. The method for determining the regularized seismic data volume includes:
[0028] Step S1: Obtain the stacked seismic data volume of the target area.
[0029] During the acquisition process of seismic data, multiple shot points need to be set on the ground, then shots are carried out at each shot point, and then seismic waves generated by each shot are collected by multiple seismographs. Then, the multiple shot data collected by each seismograph are stacked and processed to form the seismic data volume of the target area.
[0030] Step S2: Equally spacedly set a plurality of blank seismic traces as interpolation seismic traces in the seismic data volume.
[0031] Due to various factors such as terrain and environment, problems such as insufficient spatial sampling density, bad channels, and irregular data distribution are widespread. This leads to a large distance between each seismic trace in the seismic data volume, resulting in limited accuracy of the seismic data volume. To improve the accuracy of the seismic data volume, interpolation processing of the seismic data volume is required. Moreover, by improving the overall accuracy of the seismic data volume, the impact of bad channels on the entire seismic data volume can also be reduced. Therefore, in this application, a plurality of blank seismic traces are first equidistantly set in the seismic data volume as interpolation seismic traces.
[0032] Step S3: Select data blocks of a preset size in the seismic data volume according to each of the interpolation seismic traces, where there is an overlapping area between the data blocks of two adjacent interpolation seismic traces.
[0033] When performing interpolation on each interpolation seismic trace, it mainly relies on the seismic trace data around the interpolation seismic trace to predict the data in the interpolation seismic trace. Therefore, we need to determine the data block used to predict the interpolation data in the seismic data volume based on the interpolation seismic trace. In this application, to prevent aliasing during the interpolation process, constraints need to be imposed on the size of the data block and the distance between the interpolation seismic traces.
[0034] Therefore, in some embodiments, step S3 "Select data blocks of a preset size in the seismic data volume according to each of the interpolation seismic traces" includes:
[0035] Step S31: Determine the center position of the data block according to the target interpolation seismic trace.
[0036] Step S32: Obtain a preset point range, line range, and time window range, where the point range, the line range, and the time window range are all greater than the distance between two adjacent interpolation seismic traces.
[0037] Step S33: Determine the data block according to the point range, the line range, the time window range, and the center position.
[0038] Since interpolation needs to be performed on the target interpolation seismic trace, and the interpolation data of the target seismic trace needs to be determined based on the seismic trace data around the target interpolation seismic trace. Therefore, in this application, the target interpolation seismic trace is selected as the center, and then the data block used to determine the interpolation data is determined according to the points, lines, and time windows that meet the preset size. In order to prevent aliasing during interpolation, in this application, the ranges of the points, lines, and time windows need to be greater than the distance between two interpolation seismic traces. That is to say, in addition to the target interpolation seismic trace, a data block will also include two interpolation seismic traces adjacent to the target interpolation seismic trace.
[0039] Step S4: Determine the interpolation data of each interpolation seismic trace according to each data block.
[0040] After obtaining the data block corresponding to the interpolated seismic trace, the interpolated data of the corresponding interpolated seismic trace can be obtained according to each data block.
[0041] Therefore, in some embodiments, step S4 "determine the interpolated data of each of the interpolated seismic traces according to each of the data blocks" includes:
[0042] Step S41: Perform Fourier transform on each seismic data trace in the data block to obtain a frequency-domain data block.
[0043] In step S41, it is necessary to perform Fourier transform on each seismic data trace in the data block to obtain a frequency-domain data block in the frequency-space domain. Therefore, in some embodiments, the expression of the frequency-domain data block is as follows:
[0044]
[0045] In the formula, m and n represent the spatial position of the trace, there are L linear events, and b k (f) is the spectrum of the kth linear event, where S k is the time difference between event k and the adjacent trace.
[0046] Step S42: Establish a linear equation system of a half-step prediction operator according to the frequency-domain data block.
[0047] After obtaining the frequency-domain data block, a linear equation system can be established according to the data of each seismic trace in the frequency-domain data block.
[0048] Therefore, in some embodiments, step S42 "establish a linear equation system of a half-step prediction operator according to the frequency-domain data block" includes:
[0049] Step S421: Obtain the seismic traces with values in the frequency-domain data block.
[0050] Step S422: Establish the linear equation system according to the seismic traces with values and the target seismic trace.
[0051] To obtain the interpolated data of the target interpolated seismic trace, it is necessary to rely on the values in each seismic trace with values in the data block. Therefore, it is necessary to obtain the seismic traces with values in the frequency-domain data block, and then establish a linear equation system according to the seismic traces with values. The linear equation system includes a forward interpolation operator linear equation and a backward interpolation operator linear equation.
[0052] Step S43: Determine the forward prediction operator and the backward prediction operator according to the linear equation system.
[0053] Therefore, we can obtain the forward prediction operator and the backward prediction operator according to the forward interpolation operator linear equation and the backward interpolation operator linear equation respectively.
[0054] Therefore, in some embodiments, step S43 "determine the forward prediction operator and the backward prediction operator according to the linear equation set" includes:
[0055] Step S431: Solve the linear equation set by using the least squares method to obtain the forward half-step prediction operator and the backward half-step prediction operator.
[0056] Step S432: Determine the forward prediction operator according to the forward half-step prediction operator.
[0057] Step S433: Determine the backward prediction operator according to the backward half-step prediction operator.
[0058] By solving the normal interpolation operator linear equation and the backward interpolation operator linear equation in the linear equation set by using the least squares method respectively, the normal half-step prediction operator and the backward half-step prediction operator can be obtained.
[0059] Then, since Porsani proved that the linear in-phase axis signal can calculate the interpolation trace at frequency f and half the trace interval by calculating the half-step prediction operator at the f / 2 frequency point. Extending this principle to multi-trace interpolation, the prediction operator satisfies the following relationship: P(f / k) = P′(f).
[0060] Therefore, we can obtain the forward prediction operator according to the normal half-step prediction operator, and similarly, we can also obtain the backward prediction operator according to the backward half-step prediction operator.
[0061] Step S44: Determine the interpolation data according to the forward prediction operator and the backward prediction operator.
[0062] After obtaining the forward prediction operator and the backward prediction operator, the interpolation data for the target interpolation seismic trace can be determined according to the forward prediction operator and the backward prediction operator.
[0063] Therefore, in some embodiments, step S44 "determine the interpolation data according to the forward prediction operator and the backward prediction operator" includes:
[0064] Step S441: Perform convolution calculations on the forward prediction operator and the backward prediction operator respectively to obtain forward interpolation data and backward interpolation data.
[0065] Step S442: Determine the average interpolation data according to the forward interpolation data and the backward interpolation data.
[0066] Step S443: Perform an inverse Fourier transform on the average interpolation data to obtain the interpolation data in the spatio-temporal domain.
[0067] In order to make the obtained interpolation data more in line with reality, in this application, the forward prediction operator and the backward prediction operator are convolved through convolution, and finally the forward interpolation data and the backward interpolation data for the target interpolation seismic trace can be obtained.
[0068] The forward interpolation data and the backward interpolation data are averaged to obtain the average interpolation data of the target interpolation seismic trace. However, this average interpolation data is the interpolation data in the frequency domain, so an inverse Fourier transform needs to be performed on the average interpolation data, and finally the interpolation data in the spatio-temporal domain is obtained, that is, the interpolation data of the target interpolation seismic trace.
[0069] Therefore, in this application, the above operations can be performed on each interpolation seismic trace, and the interpolation data corresponding to each interpolation seismic trace can be obtained.
[0070] Step S5: Determine a regularized seismic data volume based on all the interpolation data and the seismic data volume.
[0071] Since the interpolation data needs to be interpolated into the interpolation seismic trace, and the interpolation seismic trace is set on the seismic data volume, in this application, all the interpolation data needs to be fused into the seismic data volume to form a regularized seismic data volume.
[0072] Therefore, in some embodiments, step S5 "Determine a regularized seismic data volume based on all the interpolation data and the seismic data volume" includes:
[0073] Step S51: Interpolate all the interpolation data into the corresponding interpolation seismic traces to form an interpolation data volume.
[0074] Step S52: Fuse the interpolation data volume with the seismic data volume to obtain the regularized seismic data volume.
[0075] Therefore, this application obtains the seismic data volume after stacking in the target area; equidistantly sets a plurality of blank seismic traces as interpolation seismic traces in the seismic data volume; selects data blocks of a preset size in the seismic data volume according to each interpolation seismic trace, where there is an overlapping area between the data blocks of two adjacent interpolation seismic traces; determines the interpolation data of each interpolation seismic trace according to each data block; determines a regularized seismic data volume based on all the interpolation data and the seismic data volume. The prediction accuracy of 3D data is improved. By adopting the idea of data block overlapping, the reliability of regularization is improved, and the aliasing phenomenon is prevented. The effect of steep dips after regularization of complex exploration areas by this method is significantly improved.
[0076] Embodiment 2:
[0077] Based on the foregoing embodiments, an apparatus for determining a regularized seismic data volume provided by an embodiment of the present application includes various modules and various units included in each module, which can be implemented by a processor in a computer device; of course, it can also be implemented by specific logic circuits; in the implementation process, the processor can be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP), or a field programmable gate array (FPGA), etc.
[0078] As Figure 2 shown, an apparatus for determining a regularized seismic data volume includes: a first acquisition module 1, a first execution module 2, a second execution module 3, a first determination module 4, and a second determination module 5.
[0079] The first acquisition module 1 is configured to acquire the stacked seismic data volume of the target area. The first execution module 2 is configured to equidistantly set a plurality of blank seismic traces as interpolation seismic traces in the seismic data volume. The second execution module 3 is configured to select data blocks of a preset size in the seismic data volume according to each interpolation seismic trace, where there is an overlapping area between the data blocks of two adjacent interpolation seismic traces. The first determination module 4 is configured to determine the interpolation data of each interpolation seismic trace according to each data block. The second determination module 5 is configured to determine the regularized seismic data volume according to all the interpolation data and the seismic data volume.
[0080] In some embodiments, the second execution module 3 includes: a third determination module, a second acquisition module, and a fourth determination module.
[0081] The third determination module is configured to determine the central position of the data block according to the target interpolation seismic trace. The second acquisition module is configured to acquire a preset point range, line range, and time window range, where the point range, the line range, and the time window range are all greater than the distance between two adjacent interpolation seismic traces. The fourth determination module is configured to determine the data block according to the point range, the line range, the time window range, and the central position.
[0082] In some embodiments, the first determination module 4 includes: a third execution module, a fourth execution module, a fifth execution module, and a fifth determination module.
[0083] The third execution module is used to perform Fourier transform on each seismic data trace in the data block to obtain a frequency-domain data block. The fourth execution module is used to establish a linear equation system of the half-step prediction operator based on the frequency-domain data block. The fifth execution module is used to determine the forward prediction operator and the backward prediction operator according to the linear equation system. The fifth determination module is used to determine the interpolation data according to the forward prediction operator and the backward prediction operator.
[0084] In some embodiments, the fifth execution module includes: a sixth execution module, a sixth determination module, and a seventh determination module.
[0085] The sixth execution module is used to solve the linear equation system by using the least squares method to obtain a forward half-step prediction operator and a backward half-step prediction operator. The sixth determination module is used to determine the forward prediction operator according to the forward half-step prediction operator. The seventh determination module is used to determine the backward prediction operator according to the backward half-step prediction operator.
[0086] In some embodiments, the fifth determination module includes: a seventh execution module, an eighth determination module, and an eighth execution module.
[0087] The seventh execution module is used to perform convolution calculations on the forward prediction operator and the backward prediction operator respectively to obtain forward interpolation data and backward interpolation data. The eighth determination module is used to determine average interpolation data according to the forward interpolation data and the backward interpolation data. The eighth execution module is used to perform inverse Fourier transform on the average interpolation data to obtain the interpolation data in the spatio-temporal domain.
[0088] In some embodiments, the second determination module 5 includes: a ninth execution module and a tenth execution module.
[0089] The ninth execution module is used to interpolate all the interpolation data into the corresponding interpolation seismic traces to form an interpolation data volume. The tenth execution module is used to fuse the interpolation data volume with the seismic data volume to obtain the regularized seismic data volume.
[0090] In some embodiments, the fourth execution module includes: a third acquisition module and an eleventh execution module.
[0091] The third acquisition module is used to acquire the seismic traces with values in the frequency-domain data block. The eleventh execution module is used to establish the linear equation system according to the seismic traces with values and the target seismic trace.
[0092] Each module in the above-mentioned device for determining a regularized seismic data volume can be implemented in whole or in part by software, hardware, or a combination thereof. Each of the above modules can be embedded in the processor in the device in the form of hardware or be independent of the processor, or can be stored in the memory in the processing device in the form of software, so as to facilitate the processor to call and execute the operations corresponding to each of the above modules. It should be noted that the division of modules in the embodiments of the present application is illustrative, only a logical function division, and there may be other division methods in actual implementation.
[0093] Embodiment 3:
[0094] In a third aspect, an electronic device is provided, including a storage and a processor. The storage stores a computer program, and when the processor executes the computer program, the steps of a method for determining a regularized seismic data volume are implemented.
[0095] Embodiment 4:
[0096] In a fourth aspect, a storage medium is provided. The computer program stored in the storage medium can be executed by one or more processors, and the computer program can be used to implement the steps of the method for determining a regularized seismic data volume according to any one of the first aspects.
[0097] Those of ordinary skill in the art can understand that all or part of the processes of implementing the methods in the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided in the present application can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.
[0098] It should be understood that the "one embodiment" or "an embodiment" mentioned throughout the specification means that the specific features, structures or characteristics related to the embodiment are included in at least one embodiment of the present application. Therefore, the "in one embodiment" or "in an embodiment" that appears throughout the specification does not necessarily refer to the same embodiment. In addition, these specific features, structures or characteristics may be combined in one or more embodiments in any suitable manner. It should be understood that in various embodiments of the present application, the magnitudes of the serial numbers of the above processes do not mean the sequence of execution, and the execution sequence of each process should be determined by its function and internal logic, and should not constitute any limitation to the implementation process of the embodiments of the present application. The serial numbers of the embodiments of the present application above are only for description and do not represent the advantages or disadvantages of the embodiments.
[0099] It should be noted that in this article, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "including a..." does not exclude the existence of additional identical elements in the process, method, article or device including the element.
[0100] In several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are only illustrative. For example, the division of the units is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units or components can be combined, or can be integrated into another system, or some features can be ignored, or not executed. In addition, the coupling, direct coupling or communication connection between the components shown or discussed with each other can be through some interfaces, and the indirect coupling or communication connection of the devices or units can be electrical, mechanical or other forms.
[0101] The units described as separate components above may or may not be physically separated, and the components shown as units may or may not be physical units; they can be located in one place or distributed to multiple network units; some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
[0102] In addition, each functional unit in the embodiments of the present application can be all integrated in a processing unit, or each unit can be separately a unit, or two or more units can be integrated in one unit; the above integrated unit can be implemented in the form of hardware, or in the form of a hardware plus software functional unit.
[0103] Those of ordinary skill in the art can understand that all or part of the steps to implement the above method embodiments can be completed by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When the program is executed, it performs the steps including those of the above method embodiments; and the aforementioned storage medium includes: various media such as removable storage devices, read-only memory (ROM), magnetic disks, or optical discs that can store program codes.
[0104] Alternatively, if the above integrated units of the present application are implemented in the form of software function modules and sold or used as independent products, they can also be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the embodiments of the present application, in essence or the part that contributes to the prior art, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a controller to execute all or part of the methods described in the various embodiments of the present application. And the aforementioned storage medium includes: various media such as removable storage devices, ROM, magnetic disks, or optical discs that can store program codes.
[0105] As described above, the above are only the implementation manners of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art within the technical scope disclosed by the present application can easily think of changes or substitutions, which should all be covered by the protection scope of the present application. Therefore, the protection scope of the present application should be subject to the protection scope of the claims.
Claims
1. A method for determining a regularized seismic data volume, characterized in that, it includes: Obtain the stacked seismic data volume of the target area; Equidistantly set a plurality of blank seismic traces as interpolation seismic traces in the seismic data volume; Select data blocks of a preset size in the seismic data volume according to each interpolation seismic trace, where there is an overlapping area between the data blocks of two adjacent interpolation seismic traces; Determine the interpolation data of each interpolation seismic trace according to each data block; Determine the regularized seismic data volume according to all the interpolation data and the seismic data volume.
2. The method according to claim 1, characterized in that, The step of selecting data blocks of a preset size in the seismic data volume according to each interpolation seismic trace includes: Determine the central position of the data block according to the target interpolation seismic trace; Obtain a preset point range, line range and time window range, where the point range, the line range and the time window range are all greater than the distance between two adjacent interpolation seismic traces; Determine the data block according to the point range, the line range, the time window range and the central position.
3. The method according to claim 2, characterized in that, The step of determining the interpolation data of each interpolation seismic trace according to each data block includes: Perform Fourier transform on each seismic trace in the data block to obtain a frequency-domain data block; Establish a linear equation system of a half-step prediction operator according to the frequency-domain data block; Determine the forward prediction operator and the backward prediction operator according to the linear equation system; Determine the interpolation data according to the forward prediction operator and the backward prediction operator.
4. The method according to claim 3, characterized in that, The step of determining the forward prediction operator and the backward prediction operator according to the linear equation system includes: Solve the linear equation system by using the least squares method to obtain the forward half-step prediction operator and the backward half-step prediction operator; Determine the forward prediction operator according to the forward half-step prediction operator; Determine the backward prediction operator according to the backward half-step prediction operator.
5. The method according to claim 3, characterized in that, The step of determining the interpolation data according to the forward prediction operator and the backward prediction operator includes: Perform convolution calculations on the forward prediction operator and the backward prediction operator respectively to obtain forward interpolation data and backward interpolation data; Determine the average interpolation data according to the forward interpolation data and the backward interpolation data; Perform inverse Fourier transform on the average interpolation data to obtain the interpolation data in the spatio-temporal domain.
6. The method according to claim 1, characterized in that, The step of determining the regularized seismic data volume according to all the interpolation data and the seismic data volume includes: Interpolate all the interpolation data into the corresponding interpolation seismic traces to form an interpolation data volume; Fuse the interpolation data volume with the seismic data volume to obtain the regularized seismic data volume.
7. The method according to claim 3, characterized in that, The step of establishing a linear equation system of a half-step prediction operator according to the frequency-domain data block includes: Obtain the valid seismic traces with values in the frequency-domain data block; Establish the linear equation set according to the valid seismic traces and the target seismic trace.
8. A device for determining a regularized seismic data volume, characterized in that, it includes: A first acquisition module, configured to acquire the superimposed seismic data volume of the target area; A first execution module, configured to equidistantly set a plurality of blank seismic traces as interpolation seismic traces in the seismic data volume; A second execution module, configured to select data blocks of a preset size in the seismic data volume according to each of the interpolation seismic traces, wherein there is an overlapping area between the data blocks of two adjacent interpolation seismic traces; A first determination module, configured to determine the interpolation data of each of the interpolation seismic traces according to each of the data blocks; A second determination module, configured to determine the regularized seismic data volume according to all the interpolation data and the seismic data volume.
9. An electronic device, characterized in that, it includes: A memory and a processor, where a computer program is stored on the memory, and when the computer program is executed by the processor, it executes the method according to any one of claims 1-7.
10. A storage medium, characterized in that, the computer program stored in the storage medium can be executed by one or more processors, and the computer program can be used to implement the method according to any one of claims 1-7.