Data-driven direction signal deconvolution method and device and readable storage medium

Abstract

The invention provides a data-driven direction signal deconvolution method and device and a readable storage medium, and belongs to the technical field of seismic data processing. The method comprises the following steps: acquiring a pre-stack seismic trace set and a preset expected wavelet; fourier forward transformation, three-dimensional # imgabs0 # transformation and inverse Fourier transformation are carried out on the pre-stack seismic channel set, and first seismic data are obtained; performing time difference correction on the first seismic data to obtain second seismic data; projecting the first seismic data and the second seismic data to a preset surface element grid, and forming first directional seismic data and second directional seismic data; obtaining a direction matching operator based on the first directional seismic data and a preset expected wavelet; and correcting the second directional seismic data by using a direction matching operator, and carrying out three-dimensional # imgabs1 # inverse transformation on the corrected data to obtain final seismic trace set data. The method has the advantages that the calculation precision and efficiency are high, the occupancy rate of a memory and the calculation cost are greatly reduced, and the signal-to-noise ratio of seismic data is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic data processing, and in particular to a data-driven directional signal deconvolution method, a data-driven directional signal deconvolution device and a readable storage medium. Background Art

[0002] In the process of marine oil and gas exploration, air guns are usually selected as the excitation source due to the limitation of sea surface excitation conditions to reduce damage to the marine environment and provide stable excitation energy. However, with the increase of the seabed depth and underground target layer depth of the detection area, the energy excited by the seismic signal released by a single air gun is insufficient, so that the signal reflected from the underground received by the detector end is easily covered by the bubble response formed by the instantaneous pulse, and it is impossible to obtain a satisfactory quality of seismic data. In order to increase the energy of the excitation source and improve the energy proportion of the effective signal, an air gun array combination is selected as the excitation source in actual marine seismic acquisition.

[0003] The airgun array combination is to arrange multiple single airguns in a certain spatial combination (including horizontal and vertical arrangement), and the signals excited by each airgun are synthesized into a main excitation wavelet signal according to the spatial position of the airgun. Although this array combination can effectively enhance the excitation energy, since the center of its spatial combination no longer meets the assumption of point source excitation, the superposition response of the signals excited by each airgun at different angles is different. Finally, the synthesized far-field wavelet will change with the change of different superposition angles, and obviously show directional dependence. In the processing of marine seismic data, in order to improve the quality of the data, seismic wavelets with high signal-to-noise ratio and stable morphology will be extracted as much as possible, and the directional effect will destroy the lateral consistency of the wavelet and must be eliminated. In the past, marine seismic exploration was mainly based on towing cable collection, which could only obtain seismic data in narrow azimuths. The directional effect generated by the superposition of far-field wavelets at different angles was not very obvious. The use of one-dimensional signal deconvolution can better solve this problem. In addition, in recent years, with the development of ocean OBN (Ocean Bottom Nodes) acquisition technology, it has also gained popularity because it can provide all-round, high-density, long-offset information, and is more helpful in improving the quality of seismic imaging of complex oil and gas reservoirs. However, it also poses more severe challenges to the processing of OBN data. Among them, the directional effect of far-field wavelets has become extremely prominent. In order to solve this problem, three technical difficulties are faced: (1) How to characterize the directionality of far-field wavelets; (2) How to extract far-field wavelets with directions; (3) How to eliminate the directional effect of far-field wavelets. In view of the above three technical difficulties, a method and device that can effectively eliminate the directional effect of far-field wavelets is urgently needed. Summary of the invention

[0004] The purpose of the embodiments of the present invention is to provide a data-driven directional signal deconvolution method, device and readable storage medium, so as to at least solve the problems in the above-mentioned prior art that the directional effect of the far-field wavelet is abnormally prominent, the directionality of the far-field wavelet cannot be characterized, the far-field wavelet with direction cannot be extracted; and the directional effect of the far-field wavelet cannot be eliminated.

[0005] In order to achieve the above object, the present invention provides a data-driven directional signal deconvolution method in a first aspect, the method comprising: Obtain pre-stack seismic gather data and preset expected wavelets during seismic data acquisition; The pre-stack seismic gather data are sequentially subjected to Fourier forward transform, three-dimensional transform and inverse Fourier transform to obtain first seismic data;

[0006] Performing time difference correction on each seismic trace in the first seismic data in the same plane to obtain second seismic data; Projecting the azimuth of each seismic trace in the second seismic data onto a preset bin grid, determining a seismic trace in each bin, and forming first directional seismic data based on the seismic traces of all bins; Projecting the azimuth of each seismic trace in the first seismic data onto a preset bin grid and determining a seismic trace in each bin, and forming second directional seismic data based on the seismic traces of all bins; Obtaining a direction matching operator based on the first directional seismic data and the preset expected wavelet; The second directional seismic data is corrected by using the direction matching operator, and the corrected data is subjected to three-dimensional Perform inverse transformation to obtain the final seismic gather data.

[0007] Optionally, the pre-stack seismic gather data is subjected to Fourier forward transform, three-dimensional Transform and inverse Fourier transform to obtain the first seismic data, including:

[0008] Based on the shot point coordinates and receiver point coordinates of pre-stack seismic gather data, the shot offset of each seismic trace is calculated; Performing Fourier forward transform on the pre-stack seismic gather data along the time direction to obtain first seismic sub-data; Based on the offset of each seismic trace, the conjugate operator of the lateral transformation operator and the longitudinal transformation operator is obtained; The seismic sub-data are three-dimensionally processed based on the conjugate operator. Forward transformation to obtain the second seismic sub-data;

[0009] Perform an inverse Fourier transform on the second seismic sub-data along the time direction to obtain the first seismic data.

[0010] Optionally, the expression of the conjugate operator of the transverse transformation operator is: ;

[0011] in, is the conjugate operator of the transverse transformation operator; is the circular frequency of the seismic data; for x Offset in direction; m is the number of lateral seismic traces; is the transverse ray parameter; k for The number of channels in the horizontal direction of the domain;

[0012] The expression of the conjugate operator of the longitudinal transformation operator is: ;

[0013] in, is the conjugate operator of the transverse transformation operator; is the circular frequency of the seismic data; for y Offset in direction; n is the number of lateral seismic traces; is the transverse ray parameter; j for The number of channels in the vertical direction of the domain.

[0014] Optionally, performing time difference correction on each seismic trace in the first seismic data in the same plane to obtain second seismic data includes: The following formula is used for time difference correction: ;

[0015] in, is the second earthquake data; is the first earthquake data; is the intercept time at zero offset, is the layer velocity of the first medium; and is the ray parameter of each seismic trace in the first seismic data; The distance from the correction plane to the water surface.

[0016] Optionally, the azimuth angle includes a horizontal azimuth angle and a vertical emission angle, and the method further includes: The horizontal azimuth angle and vertical emission angle are calculated using the following formula: ;

[0017] ;

[0018] in, is the horizontal azimuth; is the vertical incidence angle; and is the ray parameter of each seismic trace; is the layer velocity of the first medium.

[0019] Optionally, obtaining a direction matching operator based on the first directional seismic data and the preset expected wavelet includes: Performing wavelet matching on the first directional seismic data and the preset expected wavelet to obtain a matching operator; Based on the matching operator, a direction matching operator is obtained by using the least squares criterion.

[0020] Optionally, obtaining a direction matching operator based on the first directional seismic data and the preset expected wavelet further includes: The direction matching operator is obtained using the following formula: ;

[0021] ;

[0022] in, is the direction matching operator; is the first directional seismic data; is the preset expected wavelet.

[0023] Optionally, the second directional seismic data is corrected using the direction matching operator, and the corrected data is subjected to three-dimensional Inverse transformation is performed to obtain the final seismic gather data, including:

[0024] The final seismic gather data is obtained using the following formula: ;

[0025] in, is the final seismic gather data; is the lateral operator; is the second directional seismic data; is the direction matching operator; is the vertical operator.

[0026] A second aspect of the present invention provides a data-driven direction signal deconvolution device, the device comprising: A data acquisition module, used to acquire pre-stack seismic gather data and preset expected wavelets during seismic data acquisition; The data transformation module is used to sequentially perform Fourier forward transformation, three-dimensional transformation and transform and inverse Fourier transform to obtain first seismic data;

[0027] A time difference correction module, used for performing time difference correction on each seismic trace in the first seismic data in the same plane to obtain second seismic data; A first determination module is used to project the azimuth of each seismic trace in the second seismic data onto a preset bin grid, and determine a seismic trace in each bin, and form first directional seismic data based on the seismic traces of all bins; A second determination module is used to project the azimuth of each seismic trace in the first seismic data onto a preset bin grid and determine a seismic trace in each bin, and form second directional seismic data based on the seismic traces of all bins; An operator determination module, used for obtaining a direction matching operator based on the first directional seismic data and the preset expected wavelet; A data output module is used to modify the second directional seismic data using the direction matching operator and perform three-dimensional analysis on the modified data. Perform inverse transformation to obtain the final seismic gather data.

[0028] On the other hand, the present invention further provides a readable storage medium having instructions stored thereon, the instructions being used to enable a machine to execute the above-mentioned data-driven directional signal deconvolution method.

[0029] This technical solution does not require known prior information and interference from human factors during the seismic data processing process, avoids the problem of low-frequency signals of seismic data not converging as the offset distance increases in the time and space domain, has high calculation accuracy, is easy to implement, improves the signal-to-noise ratio of seismic data, greatly reduces memory occupancy and computing costs, and is suitable for processing large amounts of seismic data.

[0030] Other features and advantages of the embodiments of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] The accompanying drawings are used to provide a further understanding of the embodiments of the present invention and constitute a part of the specification. Together with the following specific embodiments, they are used to explain the embodiments of the present invention, but do not constitute a limitation on the embodiments of the present invention. In the accompanying drawings: Figure 1 is a flow chart of a data-driven direction signal deconvolution method provided by the present invention; Figure 2 It is a schematic diagram of the common detection point gather of the marine OBN seismic data provided by the present invention; Figure 3 It is a schematic diagram of a preset expected sub-wave of the source acquisition design provided by the present invention; Figure 4 The present invention provides a common detection point gather transformation to three-dimensional τ- p Schematic diagram of domain seismic data; Figure 5 The three-dimensional τ- p Schematic diagram of the first arrival correction of the domain seismic data; Figure 6 The three-dimensional τ- p Schematic diagram of horizontal azimuth information extracted from the domain; Figure 7 The three-dimensional τ- p Schematic diagram of vertical emission angle information extracted from the domain; Figure 8 The three-dimensional τ- p Schematic diagram of the display result of projecting the data onto the angle bin after domain first arrival correction; Fig. 9 The three-dimensional τ- p Schematic diagram of extracting directional far-field wavelets from the domain; Fig.10 is a schematic diagram of an operator after matching the far-field wavelet with the expected wavelet provided by the present invention; Fig.11 The three-dimensional τ- p Schematic diagram of the application of domain matching operator; Fig.12 is the three-dimensional τ- p Schematic diagram of the inverse transformed data; Fig.13 It is a schematic diagram of seismic wavelet spectrum data for eliminating directional effect provided by the present invention; Fig.14 It is a structural schematic diagram of a data-driven direction signal deconvolution device provided by the present invention.

[0032] Description of Reference Numerals 10-data acquisition module; 20-data conversion module; 30-time difference correction module; 40-first determination module; 50-second determination module; 60-operator determination module; 70-Data output module. DETAILED DESCRIPTION

[0033] The specific implementation of the present invention is described in detail below in conjunction with the accompanying drawings. It should be understood that the specific implementation described here is only used to illustrate and explain the present invention, and is not used to limit the present invention.

[0034] Figure 1 is a flow chart of a data-driven direction signal deconvolution method provided by the present invention; Figure 2 It is a schematic diagram of the common detection point gather of the marine OBN seismic data provided by the present invention; Figure 3 It is a schematic diagram of a preset expected sub-wave of the source acquisition design provided by the present invention; Figure 4 The present invention provides a common detection point gather to transform to three-dimensional Schematic diagram of domain seismic data; Figure 5 The present invention provides a three-dimensional Schematic diagram of the first arrival correction of the domain seismic data; Figure 6 The present invention provides a three-dimensional Schematic diagram of horizontal azimuth information extracted from the domain; Figure 7 The present invention provides a three-dimensional Schematic diagram of vertical emission angle information extracted from the domain; Figure 8 The present invention provides a three-dimensional Schematic diagram of the display result of projecting the data onto the angle bin after domain first arrival correction; Fig. 9 The present invention provides a three-dimensional Schematic diagram of extracting directional far-field wavelets from the domain; Fig.10 is a schematic diagram of an operator after matching the far-field wavelet with the expected wavelet provided by the present invention; Fig.11 The present invention provides a three-dimensional Schematic diagram of the application of domain matching operator; Fig.12 is the three-dimensional image after the operator provided by the present invention is applied Schematic diagram of the inverse transformed data; Fig.13 It is a schematic diagram of seismic wavelet spectrum data for eliminating directional effect provided by the present invention; Fig.14 It is a structural schematic diagram of a data-driven direction signal deconvolution device provided by the present invention.

[0035] like Figure 1 As shown, an embodiment of the present invention provides a data-driven direction signal deconvolution method, the method comprising: Step 1, obtaining pre-stack seismic gather data and preset expected wavelets during seismic data acquisition; Specifically, in this example, the known prestack seismic gathers and the preset expected wavelet of source acquisition design As input data, and are the horizontal and vertical coordinates in the seismic acquisition area, is the travel time coordinate of the seismic wave propagation. Figure 2 The input prestack common detection point gathers and Figure 3The desired wavelet of the acquisition design shown;

[0036] Step 2: Perform Fourier forward transform, three-dimensional transform and inverse Fourier transform to obtain first seismic data;

[0037] Specifically include: Based on the pre-stack seismic gathers The shot point coordinates in ) and the detection point coordinates ( ), where prestack seismic gathers For a common detection point gather (the coordinates of the detection points of each gather are the same, but the coordinates of the shot points are different), calculate the distance from the detection point to each shot point, called the shot offset, and use the vector and express.

[0038] Seismic Gathers Each trace in the time direction is transformed by fast Fourier transform, and the time-space domain data is transformed into the frequency-space domain, and the seismic data is obtained as , that is, as the first seismic sub-data, where is the circular frequency of the seismic data, given by Calculate and obtain, The acquisition frequency of seismic data is a known parameter.

[0039] For earthquake data 3D Transformation, first, using the vector offset of each channel in step 2) and , construct three-dimensional The horizontal transformation operator and the vertical transformation operator of the transformation are expressed as:

[0040] (1)

[0041] (2)

[0042] In formula (1), is the lateral transformation operator; is the circular frequency of the seismic data, m is the number of lateral seismic traces, is the transverse ray parameter (slope), k for The number of channels in the horizontal direction of the domain. Similarly, in formula (2), is the longitudinal transformation operator; is the circular frequency of the seismic data, n is the number of longitudinal seismic traces, is the longitudinal ray parameter, j for The number of channels in the vertical direction of the domain.

[0043] The three-dimensional shape of each channel can be calculated by formula (1) and (2). Conjugate operator of transformation operator , ,The calculation formula is as follows (3), (4);

[0044] (3)

[0045] (4)

[0046] in, is the conjugate operator of the transverse transformation operator; is the circular frequency of the seismic data; for x Offset in direction; m is the number of lateral seismic traces; is the transverse ray parameter; k for The number of channels in the horizontal direction of the domain; is the conjugate operator of the transverse transformation operator; is the circular frequency of the seismic data; for y Offset in direction; n is the number of lateral seismic traces; is the transverse ray parameter; j for The number of channels in the vertical direction of the domain.

[0047] Using the conjugate operator of each seismic trace obtained above, the seismic data 3D The forward transformation process is to transform from the frequency-space domain to the frequency-slowness domain, i.e., the second seismic sub-data, which can be expressed by the following formula:

[0048] (5)

[0049] In formula (5), For three-dimensional The seismic data volume after positive transformation (the second seismic sub-data) is , perform fast inverse Fourier transform along the time direction to obtain the three-dimensional Spectral data of the domain , i.e. the first seismic data; Figure 4 As shown, the input pre-stack gathers ( Figure 2 ) Transform to three dimensions The spectral data of the domain are displayed.

[0050] Step 3, performing time difference correction on each seismic trace in the first seismic data in the same plane to obtain second seismic data; Specifically, the three-dimensional Seismic data in the domain Perform the first arrival coaxial correction. Using the flattened coaxial axis, the expansion process of the bubble energy can be identified. The correction time difference formula for each data is:

[0051] (6)

[0052] In formula (6), is the correction time difference of each track, is the intercept time at zero offset, is the layer velocity of the first medium, generally the water velocity is 1500m / s, To correct the distance from the plane to the water surface, the correction plane is an artificially defined horizontal plane, which is a constant. All traces in the image are corrected to this plane to obtain the corrected seismic data. , that is, the initial arrival co-axial correction process is realized. Figure 5 For three-dimensional Spectral data of the domain ( Figure 4 ) After the initial arrival correction to the horizontal plane, it can be seen that the reverse arc axis is effectively flattened, and the low-frequency bubble expansion process is easily identified (the position marked by the arrow in the figure).

[0053] (7)

[0054] The final transformation is: ;

[0055] in, is the second earthquake data; is the first earthquake data; is the intercept time at zero offset, is the layer velocity of the first medium, generally the water velocity is 1500m / s; and is the ray parameter of each seismic trace in the first seismic data; To correct the distance from the plane to the water surface;

[0056] Step 4: projecting the azimuth of each seismic trace in the second seismic data onto a preset bin grid, and determining a seismic trace in each bin, and forming first directional seismic data based on the seismic traces of all bins; For the first arrival corrected seismic data in the above steps , that is, the ray parameter of each seismic trace in the second seismic data and Calculate the horizontal azimuth , Figure 6 It is the azimuth information extracted from the seismic data after first arrival correction (same departure angle, different azimuth display).

[0057] (8)

[0058] Similarly, according to the ray parameters of each seismic trace , , and the layer velocity of the first medium , generally the water speed is 1500m / s, calculate the vertical angle of each channel , Figure 7 It is the departure angle information extracted from the seismic data after first arrival correction (same azimuth, different departure angles are displayed).

[0059] (9)

[0060] The range of azimuth angle and emission angle in formula (8) and formula (9) is [0°~90°]. and the exit angle , according to 1° 1° method is used to perform surface element meshing.

[0061] Seismic data The azimuth and exit angle of each trace in the image are projected onto the corresponding bin grid defined in the above steps, and the seismic data are rearranged to obtain new seismic data with angle information. ;like Figure 8 As shown, the display result of projecting seismic data onto angle bins is shown, and the phase of the first arrival information in each bin is the same.

[0062] Since the azimuth and departure angle of the seismic traces in each bin are very small, and the first arrival signal has been leveled, it can achieve the purpose of in-phase superposition and enhance the effective signal. All the traces in each bin are superimposed to obtain a unique seismic trace in each bin. In this way, the seismic data in all bins are superimposed to form a directional seismic data, which is the directional far-field wavelet. , i.e. the first directional seismic data; Fig. 9 The directional far-field wavelet data in each bin are obtained by stacking the seismic traces in the bin.

[0063] Step 5, projecting the azimuth of each seismic trace in the first seismic data onto a preset bin grid and determining a seismic trace in each bin, and forming second directional seismic data based on the seismic traces of all bins; Specifically, for seismic data that have not been leveled for the first arrival, , that is, the first seismic data is also divided into the same surface element grid using the same method to obtain the new seismic data , i.e., the second directional seismic data. The specific method is the same as the steps of projecting the azimuth of each seismic trace in the second seismic data onto a preset bin grid, determining a seismic trace in each bin, and forming the first directional seismic data based on the seismic traces of all bins, which will not be repeated here.

[0064] Step six, obtaining a direction matching operator based on the first directional seismic data and the preset expected wavelet; Specifically, using the obtained preset expected sub-wave And the directional far-field wavelet obtained , i.e., the first directional seismic data, performs wavelet matching to obtain a matching operator; Fig.10 The matching operator displayed results are obtained by wavelet matching. The specific calculation formula is as follows.

[0065] (10)

[0066] Then, using the least squares criterion, we can find the direction matching operator from formula (10): , the calculation formula is as follows:

[0067] (11)

[0068] in, is the direction matching operator; is the first directional seismic data; is the preset expected wavelet.

[0069] Step 7: Use the direction matching operator to correct the second directional seismic data, and perform three-dimensional Perform inverse transformation to obtain the final seismic gather data.

[0070] The direction matching operator determined in formula (11) ,like Fig.11 The direction matching operator shown is applied to the seismic data The above is the second directional seismic data, as follows:

[0071] (12)

[0072] Seismic data The lateral operator calculated above and the longitudinal operator Interaction, resulting in three-dimensional Inverse transformed seismic data , which is the time-space domain seismic data after the directional signal deconvolution is applied, as the final seismic gather data, the inverse transformation formula is as follows;

[0073] (13)

[0074] After fusion, the final formula is:

[0075] in, is the final seismic gather data; is the lateral operator; is the second directional seismic data; is the direction matching operator; is the vertical operator.

[0076] like Fig.12 The comparison results of seismic data before and after the directional signal deconvolution are shown in the figure. The arrows mark the positions in the figure. The low-frequency interference is effectively eliminated, and the lateral consistency of the seismic wavelet is more continuous and reliable. Fig.12 In FIG. 1 , the left image is a schematic diagram before the application of the directional signal deconvolution technique, and the right image is a schematic diagram after the application of the directional signal deconvolution technique; Fig.13 As shown, Data1 (black line) is a schematic diagram of the spectrum analysis of seismic data before the application of directional signal deconvolution, and Data2 (grey line) is a schematic diagram of the spectrum analysis of seismic data after the application of directional signal deconvolution. After the directionality of the far-field wavelet is eliminated, the spectrum of the seismic data is effectively expanded and the resolution is significantly improved.

[0077] Through the above-mentioned processing steps, the data-driven directional signal deconvolution process is completed, eliminating the problem of seismic wavelet directionality introduced by the combination of exciting sources. And for the processing of marine OBN wide-azimuth seismic data, this scheme proposes a method for eliminating the directional effect of far-field wavelets. Due to the different spatial arrangement positions of each gun in the airgun array, the signal excited by each gun, in the process of superposition to form a far-field wavelet, obviously shows a directional effect, which easily causes the lateral consistency of the wavelet to deteriorate, seriously affecting the quality of seismic data, and the present application can effectively eliminate the directionality of the far-field wavelet, which is of great significance to the processing of OBN data; using a completely data-driven method, only the original seismic data and the expected wavelet need to be input to complete the directional elimination process of the far-field wavelet, without the need for known prior information and interference from human factors, with high calculation accuracy and easy implementation; in three dimensions The azimuth and exit angle information obtained in the three-dimensional domain avoids the problem that the low-frequency signal of seismic data in the time and space domain does not converge with the increase of offset distance. The domain can highlight the low-frequency information more, and it is easy to identify the propagation period of low-frequency bubbles and virtual reflections at the shot point end, so as to suppress the two and improve the signal-to-noise ratio of the data; the "first arrival correction" + "small facet grid" method is adopted, among which the first arrival correction achieves the purpose of effective signal in-phase enhancement, and the small facet grid can more accurately calculate the azimuth and exit angle information, which provides high-precision data guarantee for the subsequent synthesis of directional far-field wavelets; the pre-stack gathers are processed, and multi-core parallel computing is realized, with fast computing efficiency; at the same time, taking advantage of the fact that the pre-stack gathers are not very sensitive to underground structural changes, the matching operator calculated by one gather can be applied to several adjacent gathers, which greatly reduces the memory occupancy and computing cost. This technology is suitable for seismic data processing with large amounts of data.

[0078] like Fig.14 As shown, an embodiment of the present invention further provides a data-driven direction signal deconvolution device, the device comprising: A data acquisition module 10 is used to acquire pre-stack seismic gather data and preset expected wavelets during seismic data acquisition; The data transformation module 20 is used to sequentially perform Fourier forward transformation, three-dimensional transformation and transform and inverse Fourier transform to obtain first seismic data;

[0079] A time difference correction module 30, used for performing time difference correction on each seismic trace in the first seismic data in the same plane to obtain second seismic data; A first determination module 40 is used to project the azimuth of each seismic trace in the second seismic data onto a preset bin grid, and determine a seismic trace in each bin, and form first directional seismic data based on the seismic traces of all bins; A second determination module 50 is used to project the azimuth of each seismic trace in the first seismic data onto a preset bin grid and determine a seismic trace in each bin, and form second directional seismic data based on the seismic traces of all bins; An operator determination module 60, configured to obtain a direction matching operator based on the first directional seismic data and the preset expected wavelet; The data output module 70 is used to modify the second directional seismic data using the direction matching operator and perform three-dimensional transformation on the modified data. Perform inverse transformation to obtain the final seismic gather data.

[0080] An embodiment of the present invention further provides a readable storage medium, on which instructions are stored, and the instructions are used to enable a machine to execute the above-mentioned data-driven directional signal deconvolution method.

[0081] Those skilled in the art will understand that all or part of the steps in the method for implementing the above-mentioned embodiments can be completed by instructing the relevant hardware through a program, and the program is stored in a storage medium, including several instructions for making a single-chip microcomputer, a chip or a processor execute all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk and other media that can store program codes.

[0082] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional units and modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The above-mentioned integrated unit can be implemented in the form of hardware or in the form of software functional units. In addition, the specific names of the functional units and modules are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application.

[0083] The optional embodiments of the present invention are described in detail above in conjunction with the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the technical concept of the embodiments of the present invention, the technical scheme of the embodiments of the present invention can be subjected to a variety of simple modifications, and these simple modifications all belong to the protection scope of the embodiments of the present invention. It should also be noted that the various specific technical features described in the above specific embodiments can be combined in any suitable manner without contradiction. In order to avoid unnecessary repetition, the embodiments of the present invention will not further describe various possible combinations.

[0084] In addition, various embodiments of the present invention may be arbitrarily combined, and as long as they do not violate the concept of the embodiments of the present invention, they should also be regarded as the contents disclosed in the embodiments of the present invention.

Claims

1. A data-driven directional signal deconvolution method, characterized in that: The method comprises: Obtain pre-stack seismic gather data and preset expected wavelets during seismic data acquisition; The pre-stack seismic gather data are sequentially subjected to Fourier forward transform, three-dimensional transform and inverse Fourier transform to obtain first seismic data; Performing time difference correction on each seismic trace in the first seismic data in the same plane to obtain second seismic data; Projecting the azimuth of each seismic trace in the second seismic data onto a preset bin grid, determining a seismic trace in each bin, and forming first directional seismic data based on the seismic traces of all bins; Projecting the azimuth of each seismic trace in the first seismic data onto a preset bin grid, determining a seismic trace in each bin, and forming second directional seismic data based on the seismic traces of all bins; Obtaining a direction matching operator based on the first directional seismic data and the preset expected wavelet; The second directional seismic data is corrected by using the direction matching operator, and the corrected data is subjected to three-dimensional Perform inverse transformation to obtain the final seismic gather data.

2. The data-driven directional signal deconvolution method according to claim 1, characterized in that: The pre-stack seismic gather data are sequentially subjected to Fourier forward transform, three-dimensional Transform and inverse Fourier transform to obtain the first seismic data, including: Based on the shot point coordinates and receiver point coordinates of pre-stack seismic gather data, the shot offset of each seismic trace is calculated; Performing Fourier forward transform on the pre-stack seismic gather data along the time direction to obtain first seismic sub-data; Based on the offset of each seismic trace, the conjugate operator of the lateral transformation operator and the longitudinal transformation operator is obtained; The seismic sub-data are three-dimensionally processed based on the conjugate operator. Forward transformation to obtain the second seismic sub-data; Perform an inverse Fourier transform on the second seismic sub-data along the time direction to obtain the first seismic data.

3. The data-driven directional signal deconvolution method according to claim 2, characterized in that: The expression of the conjugate operator of the transverse transformation operator is: ； in, is the conjugate operator of the transverse transformation operator; is the circular frequency of the seismic data; for x Offset in direction; m is the number of lateral seismic traces; is the transverse ray parameter; k for The number of channels in the horizontal direction of the domain; The expression of the conjugate operator of the longitudinal transformation operator is: ； in, is the conjugate operator of the transverse transformation operator; is the circular frequency of the seismic data; for y Offset in direction; n is the number of lateral seismic traces; is the transverse ray parameter; j for The number of channels in the vertical direction of the domain.

4. The data-driven directional signal deconvolution method according to claim 1, characterized in that: Performing time difference correction on each seismic trace in the first seismic data in the same plane to obtain second seismic data includes: The following formula is used for time difference correction: ； in, is the second earthquake data; is the first earthquake data; is the intercept time at zero offset, is the layer velocity of the first medium; and is the ray parameter of each seismic trace in the first seismic data; The distance from the correction plane to the water surface.

5. The data-driven directional signal deconvolution method according to claim 1, characterized in that: The azimuth angle includes a horizontal azimuth angle and a vertical emission angle, and the method further includes: The horizontal azimuth angle and vertical emission angle are calculated using the following formula: ； ； in, is the horizontal azimuth; is the vertical exit angle; and is the ray parameter of each seismic trace; is the layer velocity of the first medium.

6. The data-driven directional signal deconvolution method according to claim 1, characterized in that: Based on the first directional seismic data and the preset expected wavelet, a direction matching operator is obtained, including: Performing wavelet matching on the first directional seismic data and the preset expected wavelet to obtain a matching operator; Based on the matching operator, a direction matching operator is obtained by using the least squares criterion.

7. The data-driven directional signal deconvolution method according to claim 1, characterized in that: Based on the first directional seismic data and the preset expected wavelet, a direction matching operator is obtained, further comprising: The direction matching operator is obtained using the following formula: ； ； in, is the direction matching operator; is the first directional seismic data; is the preset expected wavelet.

8. The data-driven directional signal deconvolution method according to claim 1, characterized in that: The second directional seismic data is corrected by using the direction matching operator, and the corrected data is subjected to three-dimensional Inverse transformation is performed to obtain the final seismic gather data, including: The final seismic gather data is obtained using the following formula: ； in, is the final seismic gather data; is the lateral operator; is the second directional seismic data; is the direction matching operator; is the vertical operator.

9. A data-driven directional signal deconvolution device, characterized in that: The device comprises: A data acquisition module, used to acquire pre-stack seismic gather data and preset expected wavelets during seismic data acquisition; The data transformation module is used to sequentially perform Fourier forward transformation, three-dimensional transformation and transform and inverse Fourier transform to obtain first seismic data; A time difference correction module, used for performing time difference correction on each seismic trace in the first seismic data in the same plane to obtain second seismic data; A first determination module is used to project the azimuth of each seismic trace in the second seismic data onto a preset bin grid, and determine a seismic trace in each bin, and form first directional seismic data based on the seismic traces of all bins; A second determination module is used to project the azimuth of each seismic trace in the first seismic data onto a preset bin grid and determine a seismic trace in each bin, and form second directional seismic data based on the seismic traces of all bins; An operator determination module, used for obtaining a direction matching operator based on the first directional seismic data and the preset expected wavelet; A data output module is used to modify the second directional seismic data using the direction matching operator and perform three-dimensional analysis on the modified data. Perform inverse transformation to obtain the final seismic gather data.

10. A readable storage medium having instructions stored thereon, the instructions being used to enable a machine to execute the data-driven directional signal deconvolution method according to any one of claims 1 to 8.

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