Wave number tuning-based least square migration imaging method and device

Abstract

The invention provides a wave number tuning-based least square migration imaging method and device, and belongs to the technical field of seismic wave imaging, and the method comprises the steps: obtaining a reverse time migration image and a point spread function body of seismic data; performing uniform partitioning on the reverse time migration image and the point spread function body, and in any block of data, performing calculation by using the reverse time migration image and the point spread function body to obtain a least square imaging result li; filtering the least square imaging result li by adopting a pre-constructed wave number domain tuning operator g to obtain a wave number domain scattered wave imaging result si; obtaining a spatial domain wave number tuning least square imaging result p'i according to the wave number domain scattered wave imaging result si; and splicing the spatial domain wave number tuning least square imaging results p'i of all block data to obtain a complete wave number tuning least square migration imaging result p '. According to the invention, the least square imaging low-wave-number component is improved, the problem of low-frequency leakage caused by backscattering is suppressed, and the least square imaging effect is improved.

Description

Technical Field

[0001] The present application belongs to the technical field of seismic wave imaging, and in particular relates to a least squares migration imaging method and device based on wave number tuning. Background Art

[0002] Classical least squares migration imaging estimates the underground reflectivity model by iteratively matching seismic observation data. However, this method is highly dependent on the velocity model and seismic wavelet accuracy, and uses a data matching mechanism based on waveform residuals, which still poses great challenges in actual seismic data applications. The imaging domain least squares migration method calculates the point spread function and approximates the inverse operator of the Hessian. It does not require an iterative step to obtain the least squares migration result, which alleviates the algorithm's requirements for high-precision velocity and wavelets, and has demonstrated good application results in actual seismic data processing.

[0003] When the wave equation is used to calculate the globally distributed point spread function, all scattering points simultaneously excite the scattered wave field. Therefore, in the process of wave field propagation, the interference between adjacent point spread functions cannot be avoided. In addition, due to the influence of backscattering noise during the imaging process, there is energy leakage in the low wave number components in the imaging results. How to improve the wave number distribution characteristics of migration imaging and obtain high-quality least squares imaging results is a technical problem that needs to be solved urgently. Summary of the invention

[0004] Based on the above technical problems, the present application proposes a least squares migration imaging method and device based on wavenumber tuning.

[0005] In a first aspect, the present application proposes a least squares migration imaging method based on wavenumber tuning, comprising:

[0006] Obtain the reverse time migration image p and point spread function body k of seismic data;

[0007] The reverse time migration image p is uniformly divided into blocks to obtain a plurality of first blocks of data, and the point spread function body k is uniformly divided into blocks to obtain a plurality of second blocks of data;

[0008] The least squares imaging result l is calculated using the reverse time migration image in the first block of data and the point spread function in the second block of data. i ;

[0009] The pre-built wavenumber domain tuning operator g is used to perform the least squares imaging result l i Filter and obtain the wavenumber domain scattered wave imaging result s i ;

[0010] According to the wave number domain scattered wave imaging results s i , and obtain the spatial domain wavenumber tuning least squares imaging result p′i ;

[0011] The spatial domain wavenumber-tuned least squares imaging result p′ for all block data i After stitching, the complete wavenumber-tuned least squares migration imaging result p′ is obtained.

[0012] The least square imaging result l is obtained by calculating the reverse time migration image in the first block of data and the point spread function in the second block of data. i ,include:

[0013] The reverse time migration image p is transformed by Fourier transform i and the point spread function k i Switching to the frequency wavenumber domain, the reverse time migration in the frequency wavenumber domain is like p i and the point spread function k i Perform spatial deconvolution to obtain the least squares imaging result l i , where p i is the reverse time migration image of the first block of data, k i is the point spread function of the i-th second block of data;

[0014] According to the wave number domain scattered wave imaging results s i The spatial domain wavenumber tuning least squares imaging result p′ is obtained i , including: based on the wave number domain scattered wave imaging results s i Perform spatial inverse Fourier transform to obtain the spatial domain wavenumber tuned least squares imaging result p′ i .

[0015] The pre-constructed wavenumber domain tuning operator g is calculated as follows:

[0016]

[0017] Among them, g is the pre-constructed wavenumber domain tuning operator, r is the component factor, r0 is the set decay wavenumber starting point, and δ is the set regularization factor.

[0018] The calculation formula of the component factor is as follows:

[0019]

[0020] Among them, kx is the wave number component in the x-axis direction in the spatial rectangular coordinate system, ky is the wave number component in the y-axis direction in the spatial rectangular coordinate system, and kz is the wave number component in the z-axis direction in the spatial rectangular coordinate system, and the wave number components are calculated from seismic data.

[0021] The wavenumber domain scattered wave imaging result s i , the calculation formula is as follows:

[0022] s i = l i ·g

[0023] Where g is a pre-built wavenumber domain tuning operator, l i is the least squares imaging result.

[0024] In a second aspect, the present application proposes a least squares migration imaging device based on wavenumber tuning, comprising:

[0025] A data acquisition module, used to acquire the reverse time migration image p and point spread function body k of seismic data;

[0026] A data block module is used to uniformly block the reverse time migration image p to obtain a plurality of first blocks of data, and to uniformly block the point spread function body k to obtain a plurality of second blocks of data;

[0027] The first result imaging module is used to calculate the least square imaging result l using the reverse time migration image in the first block of data and the point spread function in the second block of data. i ;

[0028] The data filtering module is used to use the pre-built wavenumber domain tuning operator g to filter the least squares imaging result l i Filter and obtain the wavenumber domain scattered wave imaging result s i ;

[0029] The second result imaging module is used to image the scattered wave results s in the wave number domain i , and the spatial domain wavenumber tuning least squares imaging result p is obtained i ′;

[0030] The result stitching module is used to perform the spatial domain wavenumber tuning least squares imaging results p for all block data. i ’ are spliced ​​together to obtain the complete wavenumber tuned least squares migration imaging result p’.

[0031] The first result imaging module includes: a frequency conversion unit and a result imaging unit;

[0032] The frequency conversion unit is used to convert the reverse time shift image p by Fourier transform i and the point spread function k i Go to the frequency wavenumber domain;

[0033] The result imaging unit is used to image the reverse time migration in the frequency wave number domain. i and the point spread function k i Perform spatial deconvolution to obtain the least squares imaging result l i , where p i is the reverse time migration image of the i-th data in the first block of data, ki is the point spread function of the i-th data in the second block of data;

[0034] The second result imaging module is used to image the scattered wave according to the wave number domain. i Perform spatial inverse Fourier transform to obtain the spatial domain wavenumber tuning least squares imaging result p i ′.

[0035] In the data filtering module, the pre-constructed wavenumber domain tuning operator g is calculated as follows:

[0036]

[0037] Among them, g is the pre-constructed wavenumber domain tuning operator, r is the component factor, r0 is the set decay wavenumber starting point, and δ is the set regularization factor.

[0038] In a third aspect, the present application proposes an electronic device, comprising: a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the least squares migration imaging method based on wavenumber tuning is executed.

[0039] In a fourth aspect, the present application proposes a computer-readable storage medium storing executable instructions, which, when executed, enable a processor to perform the least squares migration imaging method based on wavenumber tuning.

[0040] Beneficial effects:

[0041] The present application proposes a least squares migration imaging method and device based on wavenumber tuning. In the least squares inversion framework, the wavenumber domain spectral tuning operator is used to optimize the migration imaging results within the block data, thereby improving the low-wavenumber component of the least squares imaging, suppressing the low-frequency leakage problem caused by backscattering, and improving the least squares imaging effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] Figure 1 This is a flow chart of a least squares migration imaging method based on wavenumber tuning according to an embodiment of the present application;

[0043] Figure 2 This is a flow chart of the least squares migration imaging method based on wavenumber tuning exemplified in this application;

[0044] Figure 3 It is a two-dimensional slice of the three-dimensional actual data of the embodiment of the present application reversely migrated in time;

[0045] Figure 4 It is a local two-dimensional slice of the three-dimensional point spread function of the embodiment of the present application;

[0046] Figure 5A local slice of a three-dimensional wave number tuning operator according to an embodiment of the present application;

[0047] Figure 6 It is a two-dimensional slice of the three-dimensional actual data wave number tuned least square imaging of the embodiment of the present application;

[0048] Figure 7 This is a principle block diagram of a least squares migration imaging device based on wavenumber tuning according to an embodiment of the present application. DETAILED DESCRIPTION

[0049] The present disclosure is further described below in conjunction with the embodiments shown in the accompanying drawings.

[0050] Classical least squares migration imaging iteratively estimates the underground reflectivity model by matching seismic observation data. However, this method is highly dependent on the velocity model and the accuracy of the seismic wavelet. The low wavenumber components obtained by classical least squares imaging are prone to suppressing backscattering, resulting in low-frequency leakage problems. The present application proposes a least squares migration imaging method and device based on wavenumber tuning. Under the framework of least squares inversion, the wavenumber domain spectral tuning operator is used to optimize the migration imaging results in the block data, thereby improving the low wavenumber components of least squares imaging, solving the low-frequency leakage problem caused by suppressing backscattering, and improving the least squares imaging effect.

[0051] Embodiment 1

[0052] This embodiment proposes a least squares migration imaging method based on wave number tuning, such as Figure 1 As shown, including:

[0053] Step S1: Obtaining the reverse time migration image p and point spread function body k of seismic data;

[0054] In this embodiment, seismic data is first acquired, and then the reverse time migration image p is calculated based on the acquired seismic data. This process belongs to the prior art and will not be described in detail in this application. In some specific implementations, based on the acquired seismic data, a point spread function body k is obtained through a series of calculations, for example, the point spread function calculation method provided in the patent application publication document entitled Point Spread Function Calculation Method, Device, Electronic Equipment and Medium for Shot Data with application number 202111205359.9 is adopted, wherein shot data is a type of seismic data.

[0055] Step S2: uniformly divide the reverse time migration image p into blocks to obtain a plurality of first blocks of data, and uniformly divide the point spread function body k into blocks to obtain a plurality of second blocks of data;

[0056] In this embodiment, both the reverse time migration image p and the point spread function body k need to be uniformly divided into blocks, and the two need to be uniformly divided into blocks using the same block division method, so that the sizes of the first block of data and the second block of data obtained are consistent.

[0057] Step S3: Calculate the least squares imaging result l using the reverse time migration image in the first block of data and the point spread function in the second block of data i ;,include:

[0058] The reverse time migration image p is transformed by Fourier transform i and the point spread function k i Switching to the frequency wavenumber domain, the reverse time migration in the frequency wavenumber domain is like p i and the point spread function k i Perform spatial deconvolution to obtain the least squares imaging result l i , where p i is the reverse time migration image of the first block of data, k i is the point spread function of the i-th second block of data;

[0059] According to the wave number domain scattered wave imaging results s i The spatial domain wavenumber tuning least squares imaging result p′ is obtained i , including: based on the wave number domain scattered wave imaging results s i Perform spatial inverse Fourier transform to obtain the spatial domain wavenumber tuned least squares imaging result p′ i .

[0060] Step S4: Use the pre-constructed wavenumber domain tuning operator g to perform the least squares imaging result l i Filter and obtain the wavenumber domain scattered wave imaging result s i ;

[0061] The pre-constructed wavenumber domain tuning operator g is calculated as follows:

[0062]

[0063] Among them, g is the pre-constructed wavenumber domain tuning operator, r is the component factor, r0 is the set decay wavenumber starting point, and δ is the set regularization factor.

[0064] The calculation formula of the component factor is as follows:

[0065]

[0066] Among them, kx is the wave number component in the x-axis direction in the spatial rectangular coordinate system, ky is the wave number component in the y-axis direction in the spatial rectangular coordinate system, and kz is the wave number component in the z-axis direction in the spatial rectangular coordinate system, and the wave number components are calculated from seismic data.

[0067] The wavenumber domain scattered wave imaging result s i , the calculation formula is as follows:

[0068] s i = l i ·g

[0069] Where g is a pre-built wavenumber domain tuning operator, l i is the least squares imaging result.

[0070] In the prior art, seismic data are generally first filtered after being acquired, which may miss some important seismic information after filtering. However, the present application performs block processing after calculating the reverse time migration image p and the point spread function body k, and uses a pre-constructed wavenumber domain tuning operator for filtering in any block. Finally, the least squares imaging results are spliced ​​to obtain a complete wavenumber tuned least squares migration imaging result, which improves the low wavenumber component of the least squares imaging, solves the low-frequency leakage problem caused by suppressing backscattering, and improves the least squares imaging effect.

[0071] Step S5: Based on the wave number domain scattered wave imaging result s i , and obtain the spatial domain wavenumber tuning least squares imaging result p′ i ;

[0072] Step S6: The spatial domain wavenumber tuning least square imaging result p′ of all block data i After stitching, the complete wavenumber-tuned least squares migration imaging result p′ is obtained.

[0073] The least squares migration imaging method based on wavenumber tuning proposed in this embodiment first obtains the reverse time migration image p and the point spread function body k of the seismic data; the reverse time migration image p and the point spread function body k are uniformly divided into blocks, and the least squares imaging result l is calculated in any block data. i ; Secondly, the pre-constructed wavenumber domain tuning operator g is used to perform the least squares imaging result l i Filter and obtain the wavenumber domain scattered wave imaging result s i ; According to the wave number domain scattered wave imaging results s i , and obtain the spatial domain wavenumber tuning least squares imaging result p′ i ; Finally, the spatial domain wavenumber-tuned least squares imaging result p′ of all block data is i After stitching, the complete wavenumber-tuned least squares migration imaging result p′ is obtained. The low-wavenumber component of least squares imaging is improved, the low-frequency leakage problem caused by suppressed backscattering is solved, and the least squares imaging effect is improved.

[0074] Embodiment 2

[0075] In order to further illustrate the specific application process of the present application, this embodiment provides a specific example based on the first embodiment. Figure 2 As shown:

[0076] Step S101: Obtaining a reverse time migration image p and a point spread function body k of seismic data;

[0077] In the example, seismic data is first acquired, and then the reverse time migration image p is calculated based on the acquired seismic data. This process belongs to the prior art and will not be described in detail in this application. In some specific implementations, based on the acquired seismic data, a point spread function body k is obtained through a series of calculations, for example, the point spread function calculation method provided in the patent application publication document entitled Point Spread Function Calculation Method, Device, Electronic Device and Medium for Shot Data with application number 202111205359.9 is adopted, where shot data is a type of seismic data.

[0078] like Figure 3 , Figure 4 As shown, Figure 4 It is a two-dimensional slice of the three-dimensional actual data of the embodiment of the present application reversely migrated in time; Figure 4 This is a local two-dimensional slice of the three-dimensional point spread function of the embodiment of the present application; it can be seen that there is backscattered energy with strong amplitude in the reverse time migration image. Except for the relatively concentrated energy in the center of the block in the point spread function, interference noise still appears in other areas. In this case, it is difficult to solve with existing technologies.

[0079] Step S102: uniformly divide the reverse time migration image p into blocks to obtain a plurality of first blocks of data, and uniformly divide the point spread function body k into blocks to obtain a plurality of second blocks of data;

[0080] In this example, both the reverse time migration image p and the point spread function body k need to be evenly divided into blocks, and the two need to be evenly divided into blocks using the same block division method, so that the sizes of the first block of data and the second block of data obtained are consistent.

[0081] Step S103: Using Fourier transform to transform the reverse time shift image p i and the point spread function k i Switching to the frequency wavenumber domain, the reverse time migration in the frequency wavenumber domain is like p i and the point spread function k i Perform spatial deconvolution to obtain the least squares imaging result l i , where p i is the reverse time migration image of the first block of data, k i is the point spread function of the i-th second block of data;

[0082] Step S104: Use the pre-constructed wavenumber domain tuning operator g to perform the least squares imaging result l i Filter and obtain the wavenumber domain scattered wave imaging result s i ;

[0083] The pre-constructed wavenumber domain tuning operator g is calculated as follows:

[0084]

[0085] Where g is the pre-constructed wavenumber domain tuning operator, r is the component factor, r0 is the set decay wavenumber starting point, and δ is the set regularization factor. The local slice of the three-dimensional pre-constructed wavenumber tuning operator is as follows: Figure 5 shown.

[0086] The calculation formula of the component factor is as follows:

[0087]

[0088] Among them, kx is the wave number component in the x-axis direction in the spatial rectangular coordinate system, ky is the wave number component in the y-axis direction in the spatial rectangular coordinate system, and kz is the wave number component in the z-axis direction in the spatial rectangular coordinate system, and the wave number components are calculated from seismic data.

[0089] The wavenumber domain scattered wave imaging result s i , the calculation formula is as follows:

[0090] s i = l i ·g

[0091] Where g is a pre-built wavenumber domain tuning operator, l i is the least squares imaging result.

[0092] Step S105: Based on the wave number domain scattered wave imaging result s i Perform spatial inverse Fourier transform to obtain the spatial domain wavenumber tuned least squares imaging result p′ i .

[0093] Step S106: The spatial domain wavenumber tuning least square imaging result p′ of all block data i After stitching, the complete wavenumber-tuned least squares migration imaging result p′ is obtained.

[0094] like Figure 6 The figure shows the complete wavenumber-tuned least squares migration imaging result calculated by the method proposed in this example. It can be clearly seen that after being processed by the wavenumber-tuned least squares imaging method, the imaging result is significantly improved, the backscattered energy is significantly suppressed, and the imaging effect of the shallow weak energy reflection axis is significantly improved.

[0095] The least squares migration imaging method based on wavenumber tuning proposed in this embodiment uses the actual seismic data obtained to calculate the reverse time migration image p and the point spread function body k; the reverse time migration image p and the point spread function body k are evenly divided into blocks, and in any block data, the reverse time migration image p is converted into i and the point spread function k i Switching to the frequency wavenumber domain, the reverse time migration in the frequency wavenumber domain is like p i and the point spread function k i Perform spatial deconvolution to obtain the least squares imaging result l i Secondly, the pre-constructed wavenumber domain tuning operator g is used to perform the least squares imaging result l i Filter and obtain the wavenumber domain scattered wave imaging result s i ; According to the wave number domain scattered wave imaging results s i Perform spatial inverse Fourier transform to obtain the spatial domain wavenumber tuned least squares imaging result p′ i ; Finally, the spatial domain wavenumber-tuned least squares imaging result p′ of all block data is i The complete wavenumber-tuned least squares migration imaging result p′ is obtained by stitching. The simulation results of this embodiment show that the backscattered energy is significantly suppressed, which improves the imaging effect of the shallow weak energy reflection axis.

[0096] Embodiment 3

[0097] This embodiment proposes a least squares migration imaging device based on wave number tuning, such as Figure 7 As shown, including:

[0098] A data acquisition module, used to acquire the reverse time migration image p and point spread function body k of seismic data;

[0099] A data block module is used to uniformly block the reverse time migration image p to obtain a plurality of first blocks of data, and to uniformly block the point spread function body k to obtain a plurality of second blocks of data;

[0100] The first result imaging module is used to calculate the least square imaging result l using the reverse time migration image in the first block of data and the point spread function in the second block of data. i ;

[0101] The data filtering module is used to use the pre-built wavenumber domain tuning operator g to filter the least squares imaging result l i Filter and obtain the wavenumber domain scattered wave imaging result s i ;

[0102] The second result imaging module is used to image the scattered wave results s in the wave number domain i, and obtain the spatial domain wavenumber tuning least squares imaging result p′ i ;

[0103] The result stitching module is used to tune the least square imaging results p′ in the spatial domain of all block data. i After stitching, the complete wavenumber-tuned least squares migration imaging result p′ is obtained.

[0104] The first result imaging module includes: a frequency conversion unit and a result imaging unit;

[0105] The frequency conversion unit is used to convert the reverse time shift image p by Fourier transform i and the point spread function k i Go to the frequency wavenumber domain;

[0106] The result imaging unit is used to image the reverse time migration in the frequency wave number domain. i and the point spread function k i Perform spatial deconvolution to obtain the least squares imaging result l i , where p i is the reverse time migration image of the i-th data in the first block of data, k i is the point spread function of the i-th data in the second block of data;

[0107] The second result imaging module is used to image the scattered wave according to the wave number domain. i Perform spatial inverse Fourier transform to obtain the spatial domain wavenumber tuned least squares imaging result p′ i .

[0108] The pre-constructed wavenumber domain tuning operator g is calculated as follows:

[0109]

[0110] Where g is the pre-constructed wavenumber domain tuning operator, r is the component factor, r0 is the set decay wavenumber starting point, and δ is the set regularization factor. The local slice of the three-dimensional pre-constructed wavenumber tuning operator is as follows: Figure 5 shown.

[0111] The calculation formula of the component factor is as follows:

[0112]

[0113] Among them, kx is the wave number component in the x-axis direction in the spatial rectangular coordinate system, ky is the wave number component in the y-axis direction in the spatial rectangular coordinate system, and kz is the wave number component in the z-axis direction in the spatial rectangular coordinate system, and the wave number components are calculated from seismic data.

[0114] The wavenumber domain scattered wave imaging result si , the calculation formula is as follows:

[0115] s i = l i ·g

[0116] Where g is a pre-built wavenumber domain tuning operator, l i is the least squares imaging result.

[0117] The least squares migration imaging device based on wave number tuning proposed in this embodiment adopts a data acquisition module to acquire a reverse time migration image p and a point spread function body k of seismic data, adopts a data blocking module to evenly block the reverse time migration image p and the point spread function body k to obtain a plurality of block data, and uses the reverse time migration image in the first block data and the point spread function body in the second block data to calculate the least squares imaging result l i The data filtering module is used to filter the least squares imaging result l through the pre-built wavenumber domain tuning operator g. i Filter and obtain the wavenumber domain scattered wave imaging result s i , the second result imaging module is used to image the scattered wave according to the wave number domain i , and obtain the spatial domain wavenumber tuning least squares imaging result p′ i Finally, the result stitching module is used to perform the spatial domain wavenumber tuning least squares imaging results p′ of all block data. i The stitching is performed to obtain a complete wavenumber-tuned least squares migration imaging result p′. This embodiment improves the least squares imaging low wavenumber component, solves the low-frequency leakage problem caused by suppressing backscattering, and improves the least squares imaging effect.

[0118] Embodiment 4:

[0119] This embodiment provides an electronic device, including: a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the least squares migration imaging method based on wavenumber tuning is executed.

[0120] The electronic device may be a mobile phone, a computer or a tablet computer, etc., including a memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the least squares migration imaging method based on wave number tuning as described in the embodiment is implemented. It can be understood that the electronic device may also include an input / output (I / O) interface and a communication component.

[0121] The processor is used to execute all or part of the steps in the least squares migration imaging method based on wave number tuning as described in the above embodiment. The memory is used to store various types of data, which may include instructions of any application or method in the electronic device, as well as data related to the application.

[0122] The processor can be an application specific integrated circuit (ASIC), a digital signal processor (DSP), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor or other electronic components, and is used to execute the least squares migration imaging method based on wavenumber tuning described in the above embodiments.

[0123] Embodiment 5

[0124] This embodiment provides a computer-readable storage medium storing executable instructions, which, when executed, enable a processor to perform the least squares migration imaging method based on wavenumber tuning.

[0125] If implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0126] Based on this understanding, the technical solution of the present application, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes a number of instructions for enabling a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the least squares migration imaging method based on wavenumber tuning described in each embodiment of the present application.

[0127] The aforementioned storage media include: flash memory, hard disk, multimedia card, card-type memory (for example, SD (Secure Digital Memory Card) or DX (Memory Data Register, MDR abbreviation) memory, etc.), random access memory (RAM), static random access memory (SRAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), programmable read-only memory (PROM), magnetic memory, disk, CD, server, APP (Application, abbreviation of application software) application store and other media that can store program verification codes, on which a computer program is stored. When the computer program is executed by a processor, the various steps of the least squares migration imaging method based on wavenumber tuning described above can be implemented.

[0128] The various embodiments in the present disclosure are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

[0129] The protection scope of the present disclosure is not limited to the above-mentioned embodiments. Obviously, those skilled in the art can make various changes and modifications to the present disclosure without departing from the scope and spirit of the present disclosure. If these changes and modifications fall within the scope of the claims of the present disclosure and their equivalents, the intention of the present disclosure also includes these changes and modifications.

Claims

1. A least squares migration imaging method based on wavenumber tuning, characterized in that: include: Obtain the reverse time migration image p and point spread function body k of seismic data; The reverse time migration image p is uniformly divided into blocks to obtain a plurality of first blocks of data, and the point spread function body k is uniformly divided into blocks to obtain a plurality of second blocks of data; The least squares imaging result l is calculated using the reverse time migration image in the first block of data and the point spread function in the second block of data. i ; The pre-built wavenumber domain tuning operator g is used to perform the least squares imaging result l i Filter and obtain the wavenumber domain scattered wave imaging result s i ; According to the wave number domain scattered wave imaging results s i , and obtain the spatial domain wavenumber tuning least squares imaging result p′ i ; The spatial domain wavenumber-tuned least squares imaging result p′ for all block data i After stitching, the complete wavenumber-tuned least squares migration imaging result p′ is obtained.

2. The least squares migration imaging method based on wavenumber tuning according to claim 1, characterized in that: The least square imaging result l is obtained by calculating the reverse time migration image in the first block of data and the point spread function in the second block of data. i ,include: The reverse time migration image p is transformed by Fourier transform i and the point spread function k i Switching to the frequency wavenumber domain, the reverse time migration in the frequency wavenumber domain is like p i and the point spread function k i Perform spatial deconvolution to obtain the least squares imaging result l i , where p i is the reverse time migration image of the first block of data, k i is the point spread function of the i-th second block of data; According to the wave number domain scattered wave imaging results s i The spatial domain wavenumber tuning least squares imaging result p′ is obtained i , including: based on the wave number domain scattered wave imaging results s i Perform spatial inverse Fourier transform to obtain the spatial domain wavenumber tuned least squares imaging result p′ i .

3. The least squares migration imaging method based on wavenumber tuning according to claim 1, characterized in that: The pre-constructed wavenumber domain tuning operator g is calculated as follows: Among them, g is the pre-constructed wavenumber domain tuning operator, r is the component factor, r0 is the set decay wavenumber starting point, and δ is the set regularization factor.

4. The least squares migration imaging method based on wavenumber tuning according to claim 3, characterized in that: The calculation formula of the component factor is as follows: Among them, kx is the wave number component in the x-axis direction in the spatial rectangular coordinate system, ky is the wave number component in the y-axis direction in the spatial rectangular coordinate system, and kz is the wave number component in the z-axis direction in the spatial rectangular coordinate system, and the wave number components are calculated from seismic data.

5. The least squares migration imaging method based on wavenumber tuning according to claim 1, characterized in that: The wavenumber domain scattered wave imaging result s i , the calculation formula is as follows: s i =l i ·g Where g is a pre-built wavenumber domain tuning operator, l i is the least squares imaging result.

6. A least squares migration imaging device based on wave number tuning, characterized in that: include: A data acquisition module, used to acquire the reverse time migration image p and point spread function body k of seismic data; A data block module is used to uniformly block the reverse time migration image p to obtain a plurality of first blocks of data, and to uniformly block the point spread function body k to obtain a plurality of second blocks of data; The first result imaging module is used to calculate the least square imaging result l using the reverse time migration image in the first block of data and the point spread function in the second block of data. i ; The data filtering module is used to use the pre-built wavenumber domain tuning operator g to filter the least squares imaging result l i Filter and obtain the wavenumber domain scattered wave imaging result s i ; The second result imaging module is used to image the scattered wave results s in the wave number domain i , and obtain the spatial domain wavenumber tuning least squares imaging result p′ i ; The result stitching module is used to tune the least square imaging results p′ in the spatial domain of all block data. i After stitching, the complete wavenumber-tuned least squares migration imaging result p′ is obtained.

7. The least squares migration imaging device based on wavenumber tuning according to claim 6, characterized in that: The first result imaging module includes: a frequency conversion unit and a result imaging unit; The frequency conversion unit is used to convert the reverse time shift image p by Fourier transform i and the point spread function k i Go to the frequency wavenumber domain; The result imaging unit is used to image the reverse time migration in the frequency wave number domain. i and the point spread function k i Perform spatial deconvolution to obtain the least squares imaging result l i , where p i is the reverse time migration image of the i-th data in the first block of data, k i is the point spread function of the i-th data in the second block of data; The second result imaging module is used to image the scattered wave according to the wave number domain. i Perform spatial inverse Fourier transform to obtain the spatial domain wavenumber tuned least squares imaging result p′ i .

8. The least squares migration imaging device based on wavenumber tuning according to claim 6, characterized in that: In the data filtering module, the pre-constructed wavenumber domain tuning operator g is calculated as follows: Among them, g is the pre-constructed wavenumber domain tuning operator, r is the component factor, r0 is the set decay wavenumber starting point, and δ is the set regularization factor.

9. An electronic device, characterized in that: include: A memory and a processor, wherein a computer program is stored in the memory, and when the computer program is executed by the processor, the least squares migration imaging method based on wavenumber tuning according to any one of claims 1 to 5 is executed.

10. A computer-readable storage medium, characterized in that: The device stores executable instructions, which, when executed, enable a processor to perform the least squares migration imaging method based on wave number tuning as described in any one of claims 1 to 5.

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