Vibroseis hybrid wave field separation method and device, computer equipment and storage medium

Abstract

The invention provides a vibroseis mixed wave field separation method, which comprises the following steps of: acquiring a Doppler effect correction operator and a deconvolution operator, and performing first separation processing on original data based on the Doppler effect correction operator and the deconvolution operator to obtain data field signal data; the curvelet domain operator converts the data domain signal data into curvelet domain signal data; determining a sparse item of the curvelet domain signal data; based on a Doppler effect correction operator, a deconvolution operator and a curvelet domain operator, constructing a curvelet domain-based functional expression of a sparse item about curvelet domain signal data and original data; and carrying out sparse inversion on the target function, and carrying out secondary separation processing on the original data by utilizing a sparse term of the original data and based on a Doppler effect correction operator and a deconvolution operator to obtain mixed wave field separation data. According to the method for separating the hybrid wave field of the vibroseis, Doppler time difference correction and deconvolution are realized at the same time, and the separation effect of the hybrid wave field of the vibroseis is ensured.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic data processing, and in particular to a controllable seismic source mixed wave field separation method, device, computer equipment and storage medium. Background Art

[0002] In marine geophysical exploration, compared with traditional airgun seismic sources, marine controllable seismic sources, as a new type of non-pulse excitation source, can achieve continuous excitation by designing different scanning signals. It is not only more in line with the current economic and environmental requirements of marine exploration, but also can obtain marine controllable seismic source mixed wave field data by phase encoding and combining mixed seismic sources, so as to achieve lower frequency and more efficient acquisition of marine seismic data. However, the addition of mixed seismic sources will also bring a series of challenges to the processing of marine seismic data. As a continuous long-term excitation source, marine controllable seismic sources can be excited at the same time by designing different scanning signals. During the excitation process, different scanning signals overlap with each other, generating a series of aliasing noises, making the seismic wave field excited by the marine mixed seismic source more complex than that of the airgun seismic source. In addition, since the position between the marine controllable seismic source and the detector is constantly changing during the acquisition process, the Doppler effect will cause time errors between different sources and detectors, which also makes it difficult to separate the wave field of the mixed source.

[0003] Therefore, to achieve mixed wave field separation of marine vibroseis, it is necessary not only to solve the time error caused by the Doppler effect between the moving source and the detector, but also to consider how to use deconvolution to convert the source scanning signal into a pulse signal. Therefore, a new method for mixed wave field separation of marine vibroseis is urgently needed, which can solve the problem of excitation of the scanning signal of the marine vibroseis while performing Doppler correction, and achieve mixed wave field separation of marine vibroseis. Summary of the invention

[0004] Based on this, it is necessary to provide a vibroseis hybrid wavefield separation method for the above technical problems, including:

[0005] Acquire raw data, acquire a Doppler effect correction operator and a deconvolution operator, and perform a first separation process on the raw data based on the Doppler effect correction operator and the deconvolution operator to obtain scanning signal data based on the data domain, and determine the data domain signal data;

[0006] Acquire a curvelet domain operator, and use the curvelet domain operator to convert the data domain signal data into scanning signal data based on the curvelet domain, and determine it as curvelet domain signal data;

[0007] Increasing the sparsity of the curvelet domain signal data to determine a sparse term of the curvelet domain signal data;

[0008] Based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, construct a function formula based on the curvelet domain about the sparse terms of the curvelet domain signal data and the original data, and determine it as the objective function;

[0009] The objective function is subjected to sparse inversion to determine the sparse items of the original data. The original data is subjected to a second separation process based on the Doppler effect correction operator and the deconvolution operator using the sparse items of the original data to obtain mixed wavefield separation data.

[0010] In one embodiment, the steps of acquiring raw data, acquiring a Doppler effect correction operator and a deconvolution operator, performing a first separation process on the raw data based on the Doppler effect correction operator and the deconvolution operator to obtain scanning signal data based on the data domain, and determining the data domain signal data include:

[0011] Get the original data;

[0012] Obtaining Doppler effect correction operator and deconvolution operator;

[0013] Using the Doppler effect correction operator and the deconvolution operator, a data processing calculation formula is constructed;

[0014] Based on the data processing calculation formula, the original data is subjected to a first separation process to obtain scanning signal data based on the data domain, which is determined as data domain signal data.

[0015] In one embodiment, the data processing calculation formula is:

[0016] d=L d L s d0

[0017] Wherein, d is the original data, L d is the deconvolution operator, L s is the Doppler effect correction operator, and d0 is the data domain signal data.

[0018] In one embodiment, the step of increasing the sparsity of the curvelet domain signal data to determine the sparse terms of the curvelet domain signal data comprises:

[0019] Get the sparse processing calculation formula;

[0020] Based on the sparse processing calculation formula, fine grid interpolation is performed on the missing seismic traces in the curvelet domain signal data to increase the sparsity of the curvelet domain signal data and determine the sparse items of the curvelet domain signal data.

[0021] In one embodiment, the sparse processing calculation formula is:

[0022] d0=L c m

[0023] Wherein, d0 is the data domain signal data, L c is the curvelet domain operator, and m is the sparse item of the curvelet domain signal data.

[0024] In one embodiment, the step of constructing a function of the sparse terms of the curvelet domain signal data and the original data based on the curvelet domain based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, and determining the function as the objective function includes:

[0025] Based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, construct a function formula based on the curvelet domain about the sparse terms of the curvelet domain signal data and the original data, and determine it as the objective function;

[0026] Based on the sparsity of the original data, a sparse constraint is added to the original data.

[0027] In one embodiment, the objective function is:

[0028] J=||dL d L s L c m|| 2 +μ||m||1

[0029] Wherein, f is the original data, d is the original data, L d is the deconvolution operator, L s is the Doppler effect correction operator, μ is the inversion regularization operator, m is the sparse term of the curvelet domain signal data, and ||m||1 represents adding a sparse constraint to the original data.

[0030] A vibroseis hybrid wavefield separation device, comprising:

[0031] A first separation processing module is used to obtain raw data, obtain a Doppler effect correction operator and a deconvolution operator, and perform a first separation processing on the raw data based on the Doppler effect correction operator and the deconvolution operator to obtain scanning signal data based on the data domain, and determine it as data domain signal data;

[0032] A data conversion module, used to obtain a curvelet domain operator, and use the curvelet domain operator to convert the data domain signal data into scanning signal data based on the curvelet domain, and determine it as the curvelet domain signal data;

[0033] A sparse processing module, used for increasing the sparsity of the curvelet domain signal data to determine a sparse item of the curvelet domain signal data;

[0034] An objective function construction module is used to construct a function formula of the sparse terms of the curvelet domain signal data and the original data based on the curvelet domain based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, and determine it as an objective function;

[0035] The second separation processing module is used to perform sparse inversion on the target function, determine the sparse items of the original data, use the sparse items of the original data, and perform a second separation process on the original data based on the Doppler effect correction operator and the deconvolution operator to obtain mixed wave field separation data.

[0036] A computer device comprises a memory and a processor, wherein the memory stores a computer program, and the processor implements the steps of the method described in any one of the above embodiments when executing the computer program.

[0037] A computer-readable storage medium stores a computer program, which, when executed by a processor, implements the steps of the method described in any one of the above embodiments.

[0038] The application scope of the vibroseis hybrid wavefield separation method of the present invention includes but is not limited to marine vibroseis hybrid wavefield separation.

[0039] Compared with the prior art, the vibroseis hybrid wavefield separation method provided by the present invention has the following advantages or beneficial effects:

[0040] The above-mentioned controllable seismic source mixed wave field separation method, device, computer equipment and storage medium, the Doppler effect correction operator solves the time error caused by the Doppler effect between the moving source and the detector, and the deconvolution operator suppresses the aliasing noise well, and can perform a better first separation processing on the original data, so that the data domain signal data is optimized, that is, the objective function is constructed on the basis of the optimized seismic data, so the objective function can optimize the inversion of the seismic data, and the objective function is constructed based on the Doppler effect correction operator and the deconvolution operator. In this way, when the objective function is used to perform a second separation processing on the original data, Doppler time difference correction and deconvolution are simultaneously realized to ensure the separation effect of the controllable seismic source mixed wave field. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 A schematic diagram of a flow chart of a vibroseis hybrid wavefield separation method in one embodiment;

[0042] Figure 2A schematic diagram of a flow chart of a vibroseis hybrid wavefield separation method in another embodiment;

[0043] Figure 3 is a schematic diagram of the vibroseis wave field data in a comparative example;

[0044] Figure 4 A schematic diagram of the original vibroseis hybrid wavefield data in a comparative example;

[0045] Figure 5 It is a schematic diagram of the traditional first vibroseis hybrid wave field data;

[0046] Figure 6 is a schematic diagram of a second vibroseis hybrid wavefield data in one embodiment;

[0047] Figure 7 A schematic diagram of the raw data of the mixed wave field of the marine vibroseis in a comparative example;

[0048] Figure 8 A schematic diagram of marine vibroseis hybrid wave field separation data in one embodiment;

[0049] Fig. 9 A structural block diagram of a vibroseis hybrid wavefield separation device in one embodiment;

[0050] Fig.10 FIG. 4 is a diagram showing the internal structure of a computer device in one embodiment. DETAILED DESCRIPTION

[0051] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0052] Embodiment 1

[0053] In this embodiment, Figure 1 As shown, a controllable seismic source hybrid wave field separation method is provided, comprising:

[0054] S110, acquiring original data, acquiring a Doppler effect correction operator and a deconvolution operator, and performing a first separation process on the original data based on the Doppler effect correction operator and the deconvolution operator to obtain scanning signal data based on the data domain, and determining the data domain signal data.

[0055] In this embodiment, the Doppler effect correction operator solves the time error caused by the Doppler effect between the moving source and the detector, and the deconvolution operator suppresses the aliasing noise well, and can perform a better first separation process on the original data, so that the data domain signal data is optimized.

[0056] S120, obtaining a curvelet domain operator, and using the curvelet domain operator to convert the data domain signal data into scan signal data based on the curvelet domain, and determining the data as curvelet domain signal data.

[0057] In this embodiment, the scanning signal data is converted from the data domain to the curvelet domain, which can remove noise and interference in the seismic signal and ensure the separation effect of the vibroseis mixed wavefield separation method on the vibroseis mixed wavefield.

[0058] S130, increasing the sparsity of the curvelet domain signal data to determine a sparse item of the curvelet domain signal data.

[0059] In this embodiment, increasing the sparsity of the curvelet domain signal data can highlight sparse items and make them easier to observe and identify.

[0060] S140, based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, construct a function formula based on the curvelet domain about the sparse terms of the curvelet domain signal data and the original data, and determine it as the objective function.

[0061] In this embodiment, the wave field separation problem of the controllable vibrator is transformed into a least square solution problem of the objective function.

[0062] Furthermore, the least square method is used to construct an objective function so that the sparse terms of the curvelet domain signal data and the original data fit well on the fitting curve of the objective function, thereby achieving the optimal inversion of the original data in the subsequent second separation processing.

[0063] S150, performing sparse inversion on the objective function to determine the sparse items of the original data, using the sparse items of the original data and based on the Doppler effect correction operator and the deconvolution operator, performing a second separation process on the original data to obtain mixed wavefield separation data.

[0064] In this embodiment, the objective function is constructed using the least squares method, and the objective function is constructed based on the Doppler effect correction operator and the deconvolution operator, while realizing Doppler time difference correction and deconvolution, and realizing the separation and solution of the mixed wave field by the multi-dimensional inversion process. In this way, the objective function is used to realize the optimal inversion of the original data, ensure the separation effect of the mixed wave field of the controllable vibroseis source, and improve the resolution of the marine controllable vibroseis source seismic data.

[0065] The above-mentioned controllable seismic source mixed wave field separation method is based on pure data-driven, does not require prior information such as known medium structure and velocity model, and is easy to implement; and compared with the traditional deconvolution-based mixed wave field separation method, this method can effectively suppress the aliasing noise generated by the mixed source.

[0066] The above-mentioned vibroseis hybrid wavefield separation method can obtain seismic data after hybrid wavefield separation through iterative inversion, and improves the fidelity of marine vibroseis hybrid wavefield separation during the iterative inversion process.

[0067] In the above-mentioned controllable seismic source mixed wave field separation method, the Doppler effect correction operator solves the time error caused by the Doppler effect between the moving source and the detector, and the deconvolution operator suppresses the aliasing noise well, and can perform a better first separation processing on the original data, so that the data domain signal data is optimized, that is, the objective function is constructed on the basis of the optimized seismic data, so the objective function can optimize the inversion of the seismic data, and the objective function is constructed based on the Doppler effect correction operator and the deconvolution operator. In this way, when the objective function is used to perform the second separation processing on the original data, Doppler time difference correction and deconvolution are simultaneously realized to ensure the separation effect of the controllable seismic source mixed wave field.

[0068] In one embodiment, the steps of acquiring raw data, acquiring a Doppler effect correction operator and a deconvolution operator, performing a first separation process on the raw data based on the Doppler effect correction operator and the deconvolution operator to obtain scanning signal data based on the data domain, and determining the data domain signal data include:

[0069] S111, obtaining original data;

[0070] S112, obtaining a Doppler effect correction operator and a deconvolution operator;

[0071] S113, constructing a data processing calculation formula using the Doppler effect correction operator and the deconvolution operator;

[0072] S114, based on the data processing calculation formula, performing a first separation process on the original data to obtain scanning signal data based on the data domain, and determining it as data domain signal data.

[0073] In this embodiment, the Doppler effect correction operator and the deconvolution operator are used to construct a data processing formula. In this way, when the original data is separated for the first time using the data processing formula, Doppler time difference correction and deconvolution are simultaneously realized. Not only is the mixed wave field of the marine controllable seismic source well separated, but the Doppler effect and aliasing noise are also significantly suppressed.

[0074] In one embodiment, the data processing calculation formula is:

[0075] d=L d L s d0

[0076] Wherein, d is the original data, L d is the deconvolution operator, L s is the Doppler effect correction operator, and d0 is the data domain signal data.

[0077] In this embodiment, when the original data is separated for the first time using the data processing formula, Doppler time difference correction and deconvolution are simultaneously implemented, so that not only the mixed wave field of the marine controllable vibroseis source is well separated, but also the Doppler effect and aliasing noise are significantly suppressed.

[0078] In one embodiment, the step of increasing the sparsity of the curvelet domain signal data to determine the sparse terms of the curvelet domain signal data comprises:

[0079] S131, obtaining a sparse processing calculation formula;

[0080] S132, based on the sparse processing calculation formula, fine grid interpolation is performed on the missing seismic traces in the curvelet domain signal data to increase the sparsity of the curvelet domain signal data to determine the sparse items of the curvelet domain signal data.

[0081] In this embodiment, fine grid interpolation is performed on the missing seismic traces in the curvelet domain signal data, which can increase the sparsity of the curvelet domain signal data so that the sparse items can be highlighted later, that is, the sparse items can be easily determined, and the curvelet domain signal data can be made denser and more complete, so that the objective function obtained through the curvelet domain signal data has a good fitting effect with the actual seismic data, thereby improving the fidelity of the marine controllable source mixed wave field separation in the iterative inversion process.

[0082] In one embodiment, the sparse processing calculation formula is:

[0083] d0=L c m

[0084] Wherein, d0 is the data domain signal data, L c is the curvelet domain operator, and m is the sparse item of the curvelet domain signal data.

[0085] In this embodiment, the curvelet domain operator is composed of curvelet domain coefficients.

[0086] In this embodiment, fine grid interpolation is performed between observation points of curvelet domain signal data, which can improve the effect and accuracy of fine grid interpolation, increase the sparsity of curvelet domain signal data, and supplement the data of seismic traces missing in the curvelet domain signal data, so that the curvelet domain signal data is relatively dense and complete, thereby making the objective function obtained through the curvelet domain signal data have a good fitting effect with the actual seismic data, thereby improving the fidelity of marine controllable source mixed wave field separation in the iterative inversion process.

[0087] In one embodiment, the step of constructing a function of the sparse terms of the curvelet domain signal data and the original data based on the curvelet domain based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, and determining the function as the objective function includes:

[0088] S141, based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, construct a function formula of the sparse terms of the curvelet domain signal data and the original data based on the curvelet domain, and determine it as the objective function;

[0089] S142: Add a sparse constraint to the original data based on the sparsity of the original data.

[0090] In this embodiment, sparse constraints are added to the original data to optimize the original data, ensure the effect of sparse inversion, and improve the fidelity of marine vibroseis hybrid wave field separation during the iterative inversion process.

[0091] In one embodiment, the objective function is: J = || dL d L s L c m|| 2 +μ||m||1, where d is the original data, d is the original data, L d is the deconvolution operator, L s is the Doppler effect correction operator, μ is the inversion regularization operator, m is the sparse term of the curvelet domain signal data, and ||m||1 represents adding a sparse constraint to the original data.

[0092] In this embodiment, the sparse terms and sparse constraints are optimized for the original data simultaneously to ensure the effect of sparse inversion, and the inversion regularization operator is obtained by using the least squares method to achieve the optimal inversion of the original data by the second separation processing, thereby improving the fidelity of the marine controllable seismic source mixed wave field separation in the iterative inversion process.

[0093] In one embodiment, based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, a function formula of the sparse terms of the curvelet domain signal data and the original data based on the curvelet domain is constructed and determined as the objective function; the objective function is sparsely inverted to determine the sparse terms of the original data, and the sparse terms of the original data are used, and based on the Doppler effect correction operator and the deconvolution operator, the original data is subjected to a second separation process to obtain mixed wavefield separation data, which is determined as an iterative inversion step, and the number of iterative inversions is at least two times. From the second time onwards, each iterative inversion uses the mixed wavefield separation data obtained by the previous iterative inversion as the original data.

[0094] In this embodiment, at least two iterative inversions can continuously optimize the interpretation results of the seismic data and ensure the fidelity of the hybrid wavefield separation method of the vibroseis hybrid wavefield separation.

[0095] It should be understood that although Figure 1 The steps in the flowchart are shown in sequence as indicated by the arrows, but these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified in this document, there is no strict order restriction for the execution of these steps, and these steps can be executed in other orders. Moreover, Figure 1 At least part of the steps may include multiple sub-steps or multiple stages. These sub-steps or stages are not necessarily executed at the same time, but can be executed at different times. The execution order of these sub-steps or stages is not necessarily sequential, but can be executed in turn or alternately with other steps or at least part of the sub-steps or stages of other steps.

[0096] Embodiment 2

[0097] In this embodiment, Figure 2 As shown, a controllable seismic source hybrid wave field separation method is provided, comprising:

[0098] Step 1: Input data;

[0099] Step 2: constructing an objective function based on the data;

[0100] Step 3, using the objective function to find the optimal solution of the data by least squares;

[0101] Step 4, performing iterative inversion through the optimal solution of the data to obtain optimized seismic data;

[0102] Step 5: The number of iterative inversions is multiple, and each iterative inversion uses the optimized seismic data obtained by the previous iterative inversion as data.

[0103] In this embodiment, multiple iterative inversions can continuously optimize the interpretation results of seismic data and ensure the fidelity of the mixed wavefield separation method of the vibroseis mixed wavefield.

[0104] Embodiment 3

[0105] In this embodiment, a method for verifying the fidelity of vibroseis hybrid wavefield separation is provided, including:

[0106] Set the data of three source ships;

[0107] Using the data from the three source ships, without considering the mixed source and Doppler effect, the controllable source wave field data is obtained, such as Figure 3 As shown;

[0108] Taking into account the mixed sources among the three source ships, the original vibroseis mixed wavefield data are obtained, such as Figure 4 As shown;

[0109] Using the traditional deconvolution method, the original vibroseis mixed wavefield data is processed by vibroseis mixed wavefield separation to obtain the first vibroseis mixed wavefield data, such as Figure 5 As shown, the first vibroseis hybrid wavefield data is compared with the vibroseis wavefield data and the original vibroseis hybrid wavefield data respectively;

[0110] Using the above-mentioned vibroseis mixed wavefield separation method, the original vibroseis mixed wavefield data is subjected to vibroseis mixed wavefield separation processing to obtain the second vibroseis mixed wavefield data, such as Figure 6 As shown, the second vibroseis hybrid wavefield data is compared with the vibroseis wavefield data, the original vibroseis hybrid wavefield data and the first vibroseis hybrid wavefield data respectively;

[0111] The speed of each source ship is 4.8 m / s, the number of gun points is set to 80, the number of detection points is set to 15, the spacing between the source and the detection points is set to 24 m, and the maximum frequency of the source and the detection points is set to 25 Hz.

[0112] like Figure 3 As shown in the figure, Sx(m) represents the amplitude value of the in-phase axis of the seismic wave, and Rx(m) represents the amplitude value of the anti-phase axis of the seismic wave. Figures 4 to 8 The same is true and will not be elaborated in the following text.

[0113] In this embodiment, the original vibroseis hybrid wavefield data is different from conventional seismic gather data and is formed by the correlation of linear scanning signals. Doppler correction and deconvolution processing are also required during the processing. It can be seen that compared with the first vibroseis hybrid wavefield data obtained after the traditional deconvolution method, the second vibroseis hybrid wavefield data obtained by the above-mentioned vibroseis hybrid wavefield separation method suppresses the aliasing noise well.

[0114] And combining the controllable seismic source wave field data and the original controllable seismic source mixed wave field data, it can be seen that without considering the mixed seismic source and the Doppler effect, the seismic source has a greater impact on the wave field separation effect, and the traditional deconvolution method has a poor effect in eliminating the interference of this influence. The second controllable seismic source mixed wave field data obtained by the above-mentioned controllable seismic source mixed wave field separation method has extremely well eliminated the interference of this influence, that is, it has well suppressed the aliasing noise.

[0115] Embodiment 4

[0116] The actual marine data of a certain work area were selected to further test the above-mentioned vibroseis hybrid wave field separation method:

[0117] like Figure 7 and Figure 8 As shown, a mixed 80-shot system is set, the number of detection points is 150, the spacing between the shot points and the detection points is 12.5 m, and the speed of the source ship is 1.8 m / s.

[0118] As can be seen, Figure 7 As shown in Figure 2, the aliasing noise of the original data of the marine vibroseis hybrid wave field is relatively large, such as Figure 8 As shown in the figure, the aliasing noise of the marine vibroseis mixed wavefield separation data obtained after separation and processing by the above-mentioned vibroseis mixed wavefield separation method is small. It can be seen that after separation and processing by the above-mentioned vibroseis mixed wavefield separation method, not only the marine vibroseis mixed wavefield is well separated, but the Doppler effect and aliasing noise are also significantly suppressed, which proves the effectiveness of the above-mentioned vibroseis mixed wavefield separation method.

[0119] Embodiment 5

[0120] In this embodiment, Fig. 9 As shown, in this embodiment, a controllable seismic source hybrid wave field separation device is provided, comprising:

[0121] The first separation processing module 210 is used to obtain raw data, obtain a Doppler effect correction operator and a deconvolution operator, and perform a first separation processing on the raw data based on the Doppler effect correction operator and the deconvolution operator to obtain scanning signal data based on the data domain, and determine it as data domain signal data;

[0122] A data conversion module 220 is used to obtain a curvelet domain operator, and use the curvelet domain operator to convert the data domain signal data into scanning signal data based on the curvelet domain, and determine it as the curvelet domain signal data;

[0123] A sparse processing module 230, configured to increase the sparsity of the curvelet domain signal data to determine a sparse item of the curvelet domain signal data;

[0124] An objective function construction module 240 is used to construct a function of the sparse terms of the curvelet domain signal data and the original data based on the curvelet domain based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, and determine it as an objective function;

[0125] The second separation processing module 250 is used to perform sparse inversion on the target function, determine the sparse items of the original data, and perform a second separation process on the original data based on the Doppler effect correction operator and the deconvolution operator using the sparse items of the original data to obtain mixed wavefield separation data.

[0126] In this embodiment, the first separation processing module 210 not only solves the time error caused by the Doppler effect between the moving source and the detector, but also suppresses the aliasing noise well, and can perform better first separation processing on the original data, so that the data domain signal data is optimized.

[0127] In this embodiment, the data conversion module 220 converts the scanning signal data from the data domain to the curvelet domain, which can remove noise and interference in the seismic signal and ensure the separation effect of the vibroseis mixed wavefield separation device on the vibroseis mixed wavefield.

[0128] In this embodiment, increasing the sparsity of the curvelet domain signal data can highlight sparse items and make them easier to observe and identify.

[0129] In this embodiment, the wave field separation problem of the controllable vibrator is transformed into a least square solution problem of the objective function.

[0130] Furthermore, the least square method is used to construct an objective function so that the sparse terms of the curvelet domain signal data and the original data fit well on the fitting curve of the objective function, thereby achieving the optimal inversion of the original data in the subsequent second separation processing.

[0131] In this embodiment, the objective function is constructed using the least squares method, and the first separation processing module simultaneously implements Doppler time difference correction and deconvolution, and uses the multi-dimensional inversion process to achieve the separation and solution of the mixed wave field. In this way, the objective function is used to achieve the optimal inversion of the original data, ensure the separation effect of the controllable source mixed wave field, and improve the resolution of marine controllable source seismic data.

[0132] In the above-mentioned controllable seismic source mixed wave field separation device, the first separation processing module not only solves the time error caused by the Doppler effect between the moving source and the detector, but also suppresses the aliasing noise very well, and can perform a better first separation processing on the original data, so that the data domain signal data is optimized, that is, the objective function is constructed on the basis of the optimized seismic data, so the objective function can optimize the inversion of the seismic data, and the objective function is constructed based on the Doppler effect correction operator and the deconvolution operator. In this way, when the objective function is used to perform the second separation processing on the original data, Doppler time difference correction and deconvolution are simultaneously realized to ensure the separation effect of the controllable seismic source mixed wave field.

[0133] In one embodiment, the first separation processing module includes:

[0134] A raw data acquisition unit, used for acquiring raw data;

[0135] An operator acquisition unit, used for acquiring a Doppler effect correction operator and a deconvolution operator;

[0136] A data construction unit, used to construct a data processing calculation formula using the Doppler effect correction operator and the deconvolution operator;

[0137] The data processing unit performs a first separation process on the original data based on the data processing calculation formula to obtain scanning signal data based on the data domain and determines it as data domain signal data.

[0138] In this embodiment, the Doppler effect correction operator and the deconvolution operator are used to construct a data processing formula. In this way, when the original data is separated for the first time using the data processing unit, Doppler time difference correction and deconvolution are simultaneously realized. Not only is the mixed wave field of the controllable seismic source well separated, but the Doppler effect and aliasing noise are also significantly suppressed.

[0139] In one embodiment, the data processing calculation formula is:

[0140] d=L d L s d0

[0141] Wherein, d is the original data, L d is the deconvolution operator, L s is the Doppler effect correction operator, and d0 is the data domain signal data.

[0142] In this embodiment, when the original data is separated for the first time using the data processing formula, Doppler time difference correction and deconvolution are simultaneously implemented, so that not only the mixed wave field of the marine controllable vibroseis source is well separated, but also the Doppler effect and aliasing noise are significantly suppressed.

[0143] In one embodiment, the vibroseis hybrid wavefield separation device further includes a sparse processing module, and the sparse processing module includes:

[0144] A sparse calculation formula acquisition unit, used for acquiring a sparse processing calculation formula;

[0145] A fine grid interpolation unit performs fine grid interpolation on the missing seismic traces in the curvelet domain signal data based on the sparse processing calculation formula.

[0146] In this embodiment, after the sparse calculation formula acquisition unit obtains the sparse processing calculation formula, the fine grid interpolation unit performs fine grid interpolation on the missing seismic traces in the curvelet domain signal data, which can increase the sparsity of the curvelet domain signal data so as to highlight the sparse items later, that is, it is easy to determine the sparse items, and make the curvelet domain signal data more dense and complete, so that the objective function obtained through the curvelet domain signal data has a good fitting effect with the actual seismic data, thereby improving the fidelity of the marine controllable source mixed wave field separation in the iterative inversion process.

[0147] In one embodiment, the sparse processing calculation formula is:

[0148] d0=L c m

[0149] Wherein, d0 is the data domain signal data, L c is the curvelet domain operator, and m is the sparse item of the curvelet domain signal data.

[0150] In this embodiment, the curvelet domain operator is composed of curvelet domain coefficients.

[0151] In this embodiment, fine grid interpolation is performed between observation points of curvelet domain signal data, which can improve the effect and accuracy of fine grid interpolation, increase the sparsity of curvelet domain signal data, and supplement the data of seismic traces missing in the curvelet domain signal data, so that the curvelet domain signal data is relatively dense and complete, thereby making the objective function obtained through the curvelet domain signal data have a good fitting effect with the actual seismic data, thereby improving the fidelity of marine controllable source mixed wave field separation in the iterative inversion process.

[0152] In one embodiment, the controllable vibroseis hybrid wavefield separation device further comprises:

[0153] The sparse constraint module is used to add sparse constraints to the original data based on the sparsity of the original data.

[0154] In this embodiment, the sparse constraint module adds sparse constraints to the original data, which can optimize the original data, ensure the effect of sparse inversion, and improve the fidelity of marine vibroseis hybrid wave field separation during the iterative inversion process.

[0155] In one embodiment, the objective function is:

[0156] J=||dL d L s L c m|| 2 +μ||m||1

[0157] In the formula, d is the original data, d is the original data, Ld is the deconvolution operator, L s is the Doppler effect correction operator, μ is the inversion regularization operator, m is the sparse term of the curvelet domain signal data, and ||m||1 represents adding a sparse constraint to the original data.

[0158] In this embodiment, the sparse terms and sparse constraints are optimized for the original data simultaneously to ensure the effect of sparse inversion, and the inversion regularization operator is obtained by using the least squares method to achieve the optimal inversion of the original data by the second separation processing, thereby improving the fidelity of the marine controllable seismic source mixed wave field separation in the iterative inversion process.

[0159] For the specific definition of the controllable seismic source hybrid wavefield separation device, please refer to the definition of the controllable seismic source hybrid wavefield separation method above, which will not be repeated here. Each unit in the above-mentioned controllable seismic source hybrid wavefield separation device can be fully or partially implemented by software, hardware and their combination. The above-mentioned units can be embedded in or independent of the processor in the computer device in the form of hardware, or can be stored in the memory of the computer device in the form of software, so that the processor can call and execute the operations corresponding to the above-mentioned units.

[0160] Embodiment 6

[0161] In this embodiment, Fig.10 As shown in FIG. 1 , a computer device is provided. The internal structure diagram thereof can be shown as Fig.10 As shown. The computer device includes a processor, a memory, a network interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program, and the non-volatile storage medium is deployed with a database, which is used to store raw data. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The network interface of the computer device is used to communicate with other computer devices deployed with application software. When the computer program is executed by the processor, a controllable seismic source hybrid wave field separation method is implemented. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covered on the display screen, or a key, trackball or touchpad set on the computer device shell, or an external keyboard, touchpad or mouse.

[0162] Those skilled in the art will understand that Fig.10The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0163] In one embodiment, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor executes the computer program, the following steps are implemented:

[0164] S110, acquiring original data, acquiring a Doppler effect correction operator and a deconvolution operator, and performing a first separation process on the original data based on the Doppler effect correction operator and the deconvolution operator to obtain scanning signal data based on the data domain, and determining the data domain signal data.

[0165] In this embodiment, the Doppler effect correction operator solves the time error caused by the Doppler effect between the moving source and the detector, and the deconvolution operator suppresses the aliasing noise well, and can perform a better first separation process on the original data, so that the data domain signal data is optimized.

[0166] S120, obtaining a curvelet domain operator, and using the curvelet domain operator to convert the data domain signal data into scan signal data based on the curvelet domain, and determining the data as curvelet domain signal data.

[0167] In this embodiment, the scanning signal data is converted from the data domain to the curvelet domain, which can remove noise and interference in the seismic signal and ensure the separation effect of the computer equipment on the controllable vibroseis mixed wave field.

[0168] S130, increasing the sparsity of the curvelet domain signal data to determine a sparse item of the curvelet domain signal data.

[0169] In this embodiment, increasing the sparsity of the curvelet domain signal data can highlight sparse items and make them easier to observe and identify.

[0170] S140, based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, construct a function formula based on the curvelet domain about the sparse terms of the curvelet domain signal data and the original data, and determine it as the objective function.

[0171] In this embodiment, the wave field separation problem of the controllable vibrator is transformed into a least square solution problem of the objective function.

[0172] Furthermore, the least square method is used to construct an objective function so that the sparse terms of the curvelet domain signal data and the original data fit well on the fitting curve of the objective function, thereby achieving the optimal inversion of the original data in the subsequent second separation processing.

[0173] S150, performing sparse inversion on the objective function to determine the sparse items of the original data, using the sparse items of the original data and based on the Doppler effect correction operator and the deconvolution operator, performing a second separation process on the original data to obtain mixed wavefield separation data.

[0174] In this embodiment, the objective function is constructed using the least squares method, and the objective function is constructed based on the Doppler effect correction operator and the deconvolution operator, while realizing Doppler time difference correction and deconvolution, and realizing the separation and solution of the mixed wave field by the multi-dimensional inversion process. In this way, the objective function is used to realize the optimal inversion of the original data, ensure the separation effect of the mixed wave field of the controllable vibroseis source, and improve the resolution of the marine controllable vibroseis source seismic data.

[0175] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0176] S111, obtaining original data;

[0177] S112, obtaining a Doppler effect correction operator and a deconvolution operator;

[0178] S113, constructing a data processing calculation formula using the Doppler effect correction operator and the deconvolution operator;

[0179] S114, based on the data processing calculation formula, performing a first separation process on the original data to obtain scanning signal data based on the data domain, and determining it as data domain signal data.

[0180] In one embodiment, the data processing calculation formula is:

[0181] d=L d L s d0

[0182] Wherein, d is the original data, L d is the deconvolution operator, L s is the Doppler effect correction operator, and d0 is the data domain signal data.

[0183] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0184] S131, obtaining a sparse processing calculation formula;

[0185] S132, based on the sparse processing calculation formula, fine grid interpolation is performed on the missing seismic traces in the curvelet domain signal data to increase the sparsity of the curvelet domain signal data to determine the sparse items of the curvelet domain signal data.

[0186] In one embodiment, the sparse processing calculation formula is:

[0187] d0=L c m

[0188] Wherein, k0 is the data domain signal data, L c is the curvelet domain operator, and m is the sparse item of the curvelet domain signal data.

[0189] In one embodiment, when the processor executes the computer program, the processor further implements the following steps:

[0190] S141, based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, construct a function formula of the sparse terms of the curvelet domain signal data and the original data based on the curvelet domain, and determine it as the objective function;

[0191] S142: Add a sparse constraint to the original data based on the sparsity of the original data.

[0192] In one embodiment, the objective function is:

[0193] J=||dL d L s L c m|| 2 +μ||m||1

[0194] In the formula, d is the original data, d is the original data, L d is the deconvolution operator, L s is the Doppler effect correction operator, μ is the inversion regularization operator, m is the sparse term of the curvelet domain signal data, and ||m||1 represents adding a sparse constraint to the original data.

[0195] Embodiment 7

[0196] In this embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the following steps are implemented:

[0197] S110, acquiring original data, acquiring a Doppler effect correction operator and a deconvolution operator, and performing a first separation process on the original data based on the Doppler effect correction operator and the deconvolution operator to obtain scanning signal data based on the data domain, and determining the data domain signal data.

[0198] In this embodiment, the Doppler effect correction operator solves the time error caused by the Doppler effect between the moving source and the detector, and the deconvolution operator suppresses the aliasing noise well, and can perform a better first separation process on the original data, so that the data domain signal data is optimized.

[0199] S120, obtaining a curvelet domain operator, and using the curvelet domain operator to convert the data domain signal data into scan signal data based on the curvelet domain, and determining the data as curvelet domain signal data.

[0200] In this embodiment, the scanning signal data is converted from the data domain to the curvelet domain, which can remove noise and interference in the seismic signal and ensure the separation effect of the computer program on the vibroseis mixed wave field.

[0201] S130, increasing the sparsity of the curvelet domain signal data to determine a sparse item of the curvelet domain signal data.

[0202] In this embodiment, increasing the sparsity of the curvelet domain signal data can highlight sparse items and make them easier to observe and identify.

[0203] S140, based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, construct a function formula based on the curvelet domain about the sparse terms of the curvelet domain signal data and the original data, and determine it as the objective function.

[0204] In this embodiment, the wave field separation problem of the controllable vibrator is transformed into a least square solution problem of the objective function.

[0205] Furthermore, the least square method is used to construct an objective function so that the sparse terms of the curvelet domain signal data and the original data fit well on the fitting curve of the objective function, thereby achieving the optimal inversion of the original data in the subsequent second separation processing.

[0206] S150, performing sparse inversion on the objective function to determine the sparse items of the original data, using the sparse items of the original data and based on the Doppler effect correction operator and the deconvolution operator, performing a second separation process on the original data to obtain mixed wavefield separation data.

[0207] In this embodiment, the objective function is constructed using the least squares method, and the objective function is constructed based on the Doppler effect correction operator and the deconvolution operator, while realizing Doppler time difference correction and deconvolution, and realizing the separation and solution of the mixed wave field by the multi-dimensional inversion process. In this way, the objective function is used to realize the optimal inversion of the original data, ensure the separation effect of the mixed wave field of the controllable vibroseis source, and improve the resolution of the marine controllable vibroseis source seismic data.

[0208] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0209] S111, obtaining original data;

[0210] S112, obtaining a Doppler effect correction operator and a deconvolution operator;

[0211] S113, constructing a data processing calculation formula using the Doppler effect correction operator and the deconvolution operator;

[0212] S114, based on the data processing calculation formula, performing a first separation process on the original data to obtain scanning signal data based on the data domain, and determining it as data domain signal data.

[0213] In this embodiment, the Doppler effect correction operator and the deconvolution operator are used to construct a data processing formula. In this way, when the original data is separated for the first time using the data processing formula, Doppler time difference correction and deconvolution are simultaneously realized. Not only is the mixed wave field of the marine controllable seismic source well separated, but the Doppler effect and aliasing noise are also significantly suppressed.

[0214] In one embodiment, the data processing calculation formula is:

[0215] d=L d L s d0

[0216] Wherein, d is the original data, L d is the deconvolution operator, L s is the Doppler effect correction operator, and d0 is the data domain signal data.

[0217] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0218] S131, obtaining a sparse processing calculation formula;

[0219] S132, based on the sparse processing calculation formula, fine grid interpolation is performed on the missing seismic traces in the curvelet domain signal data to increase the sparsity of the curvelet domain signal data to determine the sparse items of the curvelet domain signal data.

[0220] In this embodiment, fine grid interpolation is performed on the missing seismic traces in the curvelet domain signal data, which can increase the sparsity of the curvelet domain signal data so that the sparse items can be highlighted later, that is, the sparse items can be easily determined, and the curvelet domain signal data can be made denser and more complete, so that the objective function obtained through the curvelet domain signal data has a good fitting effect with the actual seismic data, thereby improving the fidelity of the marine controllable source mixed wave field separation in the iterative inversion process.

[0221] In one embodiment, the sparse processing calculation formula is:

[0222] d0=L c m

[0223] Wherein, d0 is the data domain signal data, L c is the curvelet domain operator, and m is the sparse item of the curvelet domain signal data.

[0224] In one embodiment, when the computer program is executed by a processor, the following steps are also implemented:

[0225] S141, based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, construct a function formula of the sparse terms of the curvelet domain signal data and the original data based on the curvelet domain, and determine it as the objective function;

[0226] S142: Add a sparse constraint to the original data based on the sparsity of the original data.

[0227] In this embodiment, sparse constraints are added to the original data to optimize the original data, ensure the effect of sparse inversion, and improve the fidelity of marine vibroseis hybrid wave field separation during the iterative inversion process.

[0228] In one embodiment, the objective function is:

[0229] J=||dL d L s L c m|| 2 +μ||m||1

[0230] In the formula, d is the original data, d is the original data, L d is the deconvolution operator, L s is the Doppler effect correction operator, μ is the inversion regularization operator, m is the sparse term of the curvelet domain signal data, and ||m||1 represents adding a sparse constraint to the original data.

[0231] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing the relevant hardware through a computer program, and 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-mentioned methods. Among them, any reference to memory, storage, database or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM) or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. As an illustration and not limitation, RAM is available in many forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link (Synchlink) DRAM (SLDRAM), memory bus (Rambus) direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).

[0232] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0233] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A vibroseis hybrid wavefield separation method, characterized in that: include: Acquire raw data, acquire a Doppler effect correction operator and a deconvolution operator, and perform a first separation process on the raw data based on the Doppler effect correction operator and the deconvolution operator to obtain scanning signal data based on the data domain, and determine the data domain signal data; Acquire a curvelet domain operator, and use the curvelet domain operator to convert the data domain signal data into scanning signal data based on the curvelet domain, and determine it as curvelet domain signal data; Increasing the sparsity of the curvelet domain signal data to determine a sparse term of the curvelet domain signal data; Based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, construct a function formula based on the curvelet domain about the sparse terms of the curvelet domain signal data and the original data, and determine it as the objective function; The objective function is subjected to sparse inversion to determine the sparse items of the original data. The original data is subjected to a second separation process based on the Doppler effect correction operator and the deconvolution operator using the sparse items of the original data to obtain mixed wavefield separation data.

2. The method according to claim 1, characterized in that: The steps of acquiring raw data, acquiring a Doppler effect correction operator and a deconvolution operator, performing a first separation process on the raw data based on the Doppler effect correction operator and the deconvolution operator to obtain scanning signal data based on the data domain, and determining the data domain signal data include: Get the original data; Obtaining Doppler effect correction operator and deconvolution operator; Using the Doppler effect correction operator and the deconvolution operator, a data processing calculation formula is constructed; Based on the data processing calculation formula, the original data is subjected to a first separation process to obtain scanning signal data based on the data domain, which is determined as data domain signal data.

3. The method according to claim 2, characterized in that The data processing calculation formula is: d=L d L s d0 Wherein, d is the original data, L d is the deconvolution operator, L s is the Doppler effect correction operator, and d0 is the data domain signal data.

4. The method according to claim 1, characterized in that: The step of increasing the sparsity of the curvelet domain signal data to determine the sparse items of the curvelet domain signal data comprises: Get the sparse processing calculation formula; Based on the sparse processing calculation formula, fine grid interpolation is performed on the missing seismic traces in the curvelet domain signal data to increase the sparsity of the curvelet domain signal data and determine the sparse items of the curvelet domain signal data.

5. The method according to claim 4, characterized in that The sparse processing calculation formula is: d0=L c m Wherein, d0 is the data domain signal data, L c is the curvelet domain operator, and m is the sparse item of the curvelet domain signal data.

6. The method according to claim 1, characterized in that The step of constructing a function of the sparse terms of the curvelet domain signal data and the original data based on the curvelet domain based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, and determining the function as the objective function comprises: Based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, construct a function formula based on the curvelet domain about the sparse terms of the curvelet domain signal data and the original data, and determine it as the objective function; Based on the sparsity of the original data, a sparse constraint is added to the original data.

7. The method according to claim 6, characterized in that The objective function is: J=||dL d L s L c m|| 2 +μ||m||1 In the formula, d is the original data, d is the original data, L d is the deconvolution operator, L s is the Doppler effect correction operator, μ is the inversion regularization operator, m is the sparse term of the curvelet domain signal data, and ||m||1 represents adding a sparse constraint to the original data.

8. A vibroseis hybrid wavefield separation device, characterized in that: include: A first separation processing module is used to obtain raw data, obtain a Doppler effect correction operator and a deconvolution operator, and perform a first separation processing on the raw data based on the Doppler effect correction operator and the deconvolution operator to obtain scanning signal data based on the data domain, and determine it as data domain signal data; A data conversion module, used to obtain a curvelet domain operator, and use the curvelet domain operator to convert the data domain signal data into scanning signal data based on the curvelet domain, and determine it as the curvelet domain signal data; A sparse processing module, used for increasing the sparsity of the curvelet domain signal data to determine a sparse item of the curvelet domain signal data; An objective function construction module is used to construct a function formula of the sparse terms of the curvelet domain signal data and the original data based on the curvelet domain based on the Doppler effect correction operator, the deconvolution operator and the curvelet domain operator, and determine it as an objective function; The second separation processing module is used to perform sparse inversion on the target function, determine the sparse items of the original data, use the sparse items of the original data, and perform a second separation process on the original data based on the Doppler effect correction operator and the deconvolution operator to obtain mixed wave field separation data.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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