OBN transverse wave leakage noise attenuation method based on curvelet domain extended filtering, computer storage medium and equipment

Abstract

The invention discloses an OBN shear wave leakage noise attenuation method based on curvelet domain extended filtering, and the method comprises the following steps: creating a Hilbert transform record and a time derivative record of a Z component and a time derivative record of Hilbert transform based on the shear wave data of X and Y components in OBN data, and on the basis, a transverse wave leakage matching subtraction method of curvelet domain least square extended filtering is applied, so that high-precision separation of effective information and transverse wave leakage noise is realized. Theoretical model experiment and field data processing experiment results show that the method gives consideration to the separation advantage of curvelet transformation to effective signals and shear wave leakage noise and the adaptability of extended filtering to shear wave leakage prediction errors, can significantly improve the elimination precision of shear wave leakage interference on the premise of avoiding effective signal damage, and has good application prospects. And the imaging precision of the OBN data is improved.

Description

Technical Field

[0001] The present invention belongs to the field of seismic data processing, and in particular, relates to an OBN shear wave leakage noise attenuation method based on curvelet domain extension filtering, a computer storage medium and a device. Background Art

[0002] Ocean bottom node (OBN) acquisition has been widely used in geophysical exploration to obtain richer multi-component seismic data. In an ideal OBN acquisition, the vertical Z-component receiver only records pure P-waves. However, when the receiver is not placed as expected due to the rugged seabed, the S-waves that the horizontal component receiver should record will be released into the Z-component record, limiting the application of the Z-component in the entire OBN data processing.

[0003] In early seafloor node exploration, the horizontal component shear wave leakage noise of the Z component was mostly achieved through wave field separation methods based on wave equations. These methods work well in synthetic data, but are not satisfactory in field data. Therefore, in order to fully tap the potential of OBN exploration, it is necessary to develop a more accurate shear wave leakage elimination algorithm. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems existing in the prior art. To this end, the present invention provides an OBN shear wave leakage noise attenuation method based on curvelet domain extension filtering, which aims to significantly improve the elimination accuracy of shear wave leakage interference while avoiding effective signal damage, thereby improving the imaging accuracy of OBN data.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present invention provides an OBN shear wave leakage noise attenuation method based on curvelet domain extension filtering, comprising the following steps:

[0007] S100. Based on the X and Y component data in the OBN data, the shear wave leakage noise in the Z component data is expressed as Z N (x,t);

[0008] S200. The shear wave leakage noise Z in the Z component data is N (x, t) is converted to the curvelet domain;

[0009] S300. Transverse wave leakage noise Z N The curvelet coefficient of (x, t) is expanded by integral terms to obtain the expansion of the curvelet coefficient;

[0010] S400. Taking each sample point in the curvelet domain as the center, intercepting a record block of appropriate size, and constructing an extended expression of the curvelet domain shear wave leakage noise of the partition block using the data in the intercepted record block;

[0011] S500. Obtain the matching factor of each sample point in the intercepted record block;

[0012] S600. Based on the obtained matching factor, the shear wave leakage noise matching subtraction processing is implemented for the target point of the Z component data curve coefficient;

[0013] S700. Repeat steps S400, S500 and S600 for each sample point in the curvelet domain to obtain the curvelet coefficient of the Z component that eliminates the shear wave leakage noise, and then inversely transform it back to the time-space domain to obtain the Z component data that eliminates the shear wave leakage noise.

[0014] As a preference: in the above step S100, the shear wave leakage noise Z in the Z component data N The expression for (x,t) is as follows:

[0015]

[0016] Where x is the offset distance; t is the travel time; Z N (x, t) is the shear wave leakage noise in the Z component data; X(x, t) is the X component data; X′(x, t) is the time derivative of X(x, t); X H (x, t) is the Hilbert transform of X(x, t); [X H (x,t)]′ is X H (x, t); Y(x, t) is the time derivative of Y(x, t); Y′(x, t) is the time derivative of Y(x, t); Y H (x, t) is the Hilbert transform of Y(x, t); [Y H (x,t)]′ is Y H (x, t); f1, f2, f3, f4, f5, f6, f7 and f8 represent the time derivative of Z N The matching factors corresponding to each item when (x, t) is expanded to the sum of the above items.

[0017] As a preferred embodiment: in the above step S200, the shear wave leakage noise Z in the Z component data is N The formula for converting (x, t) to the curvelet domain is as follows:

[0018]

[0019] Where j, l and k represent the scale, direction and position of the curve wave respectively; c(j,l,k) is the curve wave coefficient of the shear wave leakage noise; Represents the curvelet basis function. In actual processing, the entire Z component data Z(x, t) can be used to replace Z N (x,t).

[0020] Preferably, in the above step S300, the expansion of the obtained curvelet coefficient is as follows:

[0021]

[0022] In the formula, c X (j,l,k),c XD (j,l,k),c XH (j,l,k),c XHD (j,l,k),c Y (j,l,k),c YD (j,l,k),c YH (j,l,k), and c YHD (j, l, k) are X(x, t), X′(x, t), X H (x,t),[X H (x,t)]′、Y(x,t)、Y′(x,t)、Y H (x,t) and [Y H (x, t)]′.

[0023] Preferably, in the above step S400, the record block size is q*k, q and k are the number of horizontal and vertical blocks of the intercepted record block, respectively, and the extended expression of the curvelet domain shear wave leakage noise of the constructed partition block is as follows:

[0024]

[0025] In the formula, c i X (i=1,2...n),c i XD (i=1,2...n),c i XH (i=1,2...n),c i XHD (i=1,2...n),c i Y (i=1,2...n),c i YD (i=1,2...n),c i YH (i=1,2...n) and c i YHD (i=1,2...n) are c X (j,l,k),c XD (j,l,k),c XH (j,l,k),c XHD (j,l,k),c Y(j,l,k),c YD (j,l,k),c YH (j,l,k) and c YHD (j, l, k) are the sample points in the intercepted record block; n is the sample point sequence number in the intercepted record block; f n1 、f n2 、f n3 、f n4 、f n5 、f n6 、f n7 and f n8 are the matching factors to be sought in the intercepted record blocks corresponding to f1, f2, f3, f4, f5, f6, f7 and f8 respectively; c n It is the sample point in the intercepted record block.

[0026] Preferably, in the above step S500, the matching factor of each sample point in the intercepted record block is obtained based on the following formula:

[0027] f=(M T M+εI) -1 (M T C) (5)

[0028] Where f is the matching factor vector [f n1 ,f n2 ,f n3 ,f n4 ,f n5 ,f n6 ,f n7 ,f n8 ] T ; M is the intercepted record block c i X (i=1,2...n),c i XD (i=1,2...n),c i XH (i=1,2...n),c i XHD (i=1,2...n),c i Y (i=1,2...n),c i YD (i=1,2...n),c i YH (i=1,2...n) and c i YHD (i=1,2...n);C is the sample point c in the intercepted record block i (i=1,2...n) vector; I is the unit matrix; ε is the damping coefficient.

[0029] Preferably, in the above step S600, the shear wave leakage noise matching subtraction processing for the Z component data curve coefficient target point is implemented using the following formula:

[0030]

[0031] Where p(j,l,k) is the curve coefficient of the Z component that eliminates the shear wave leakage noise.

[0032] Preferably, in the above step S700, the expression of the Z component data after removing the shear wave leakage noise is as follows:

[0033]

[0034] In a second aspect, the present invention provides a computer storage medium having a computer program stored thereon, and when the computer program is executed by a processor, the steps of the OBN shear wave leakage noise attenuation method described in the first aspect of the present invention are implemented.

[0035] In a third aspect, the present invention provides a computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of the OBN shear wave leakage noise attenuation method described in the first aspect of the present invention when executing the computer program.

[0036] The present invention adopts the above technical solution, which has the following advantages:

[0037] The present invention takes into account the advantages of curvelet transform in separating effective signals from shear wave leakage noise and the adaptability of extended filtering to shear wave leakage prediction errors. It can significantly improve the accuracy of eliminating shear wave leakage interference while avoiding damage to effective signals, thereby improving the imaging accuracy of OBN data. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Various other advantages and benefits will become apparent to those of ordinary skill in the art by reading the detailed description of the preferred embodiments below. The accompanying drawings are only for the purpose of illustrating the preferred embodiments and are not to be considered as limiting the present invention. Throughout the accompanying drawings, the same reference numerals are used to represent the same components. In the accompanying drawings:

[0039] Figure 1 A flow chart of an OBN shear wave leakage noise attenuation method based on curvelet domain extension filtering provided in one embodiment of the present invention;

[0040] Figure 2 It is a layered fault block model;

[0041] Figure 3 (a)-(c) are synthetic OBN data volumes;

[0042] Figure 4 (a)-(d) are the effects of Z-component shear wave noise removal;

[0043] Figure 5(a)-(c) shows the effect of shear wave noise removal on the Z component near-offset profile. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present invention.

[0045] The OBN shear wave leakage noise attenuation method based on curvelet domain extended filtering provided by the present invention comprises the following steps: based on the shear wave data of the X and Y components in the OBN data, the Hilbert transform record, the time derivative record and the time derivative record of the Hilbert transform of the Z component are created, and on this basis, the shear wave leakage matching subtraction method of the least squares extended filtering in the curvelet domain is applied, so as to achieve high-precision separation of effective information and shear wave leakage noise. The results of theoretical model experiments and field data processing experiments both show that the present invention takes into account the advantages of the curvelet transform in separating effective signals and shear wave leakage noise and the adaptability of the extended filtering to the shear wave leakage prediction error, and can significantly improve the elimination accuracy of the shear wave leakage interference under the premise of avoiding damage to the effective signal, thereby improving the imaging accuracy of the OBN data.

[0046] The OBN shear wave leakage noise attenuation method based on curvelet domain extension filtering provided by an embodiment of the present invention is described in detail below with reference to the accompanying drawings.

[0047] Embodiment 1:

[0048] This embodiment uses Figure 2 The layered fault block model shown in the figure is used as an example to illustrate the description. The model has a lateral length of 10 km and a vertical depth of 2 km. Forward simulation is performed based on the layered fault block model, with a total of 302 shots, 239 channels per shot, a shot interval of 25 m, and a channel interval of 12.5 m. The shot point depth is 0 m, and the detection point is located on the seabed with a water depth of 200 m. The model with a lateral length of 10 km and a vertical length of 2 km is gridded. The grid steps in the x and z directions of the model are both 12.5 m, and a model with a grid size of 800×160 is obtained; given the seismic wavelet W(t), t represents time, based on the initial velocity model, firstly, the Ricker wavelet with a main frequency of 30 Hz is used as the source, and the source position is given (0 m, 0 m). The finite difference numerical simulation of the acoustic wave equation is used to obtain the pure P wave record P(x, t) (such as Figure 3(a)), where x is the spatial position coordinate and t is the time. Then, the Ricker wavelet with a main frequency of 20 Hz is used as the earthquake source, and the elastic wave equation is used for numerical simulation to obtain the X-component data X(x, t) (as shown in Figure 3 (b)) and the Y component data Y(x,t) (as shown Figure 3 Finally, after giving X(x, t) and Y(x, t) a time shift of 10 ms, both are added to the P component P(x, t) to obtain the Z component data Z(x, t) containing the shear wave leakage noise.

[0049] Based on this, see Figure 1 The present invention provides an OBN shear wave leakage noise attenuation method based on curvelet domain extension filtering, comprising the following steps:

[0050] S100. Based on the X and Y component data in the OBN data, the shear wave leakage noise in the Z component data is expressed as the following formula (1):

[0051]

[0052] Where x is the offset distance; t is the travel time; Z N (x, t) is the shear wave leakage noise in the Z component data; X(x, t) is the X component data; X′(x, t) is the time derivative of X(x, t); X H (x, t) is the Hilbert transform of X(x, t); [X H (x,t)]′ is X H (x, t); Y(x, t) is the time derivative of Y(x, t); Y′(x, t) is the time derivative of Y(x, t); Y H (x, t) is the Hilbert transform of Y(x, t); [Y H (x,t)]′ is Y H (x, t); f1, f2, f3, f4, f5, f6, f7 and f8 represent the time derivative of Z N When (x, t) is expanded into the sum of the above items, the matching factors corresponding to each item;

[0053] S200. Use the following formula (2) to convert the shear wave leakage noise Z in the Z component data into N (x,t) is converted to the curvelet domain:

[0054]

[0055] Where j, l and k represent the scale, direction and position of the curve wave respectively; c(j,l,k) is the curve wave coefficient of the shear wave leakage noise; Represents the curvelet basis function. In actual processing, the entire Z component data Z(x, t) can be used to replace Z N(x,t);

[0056] S300. Expand the curve coefficient c(j,l,k) of the shear wave leakage noise by integral terms to obtain the expansion formula of the curve coefficient c(j,l,k):

[0057]

[0058] In the formula, c X (j,l,k),c XD (j,l,k),c XH (j,l,k),c XHD (j,l,k),c Y (j,l,k),c YD (j,l,k),c YH (j,l,k), and c YHD (j, l, k) are X(x, t), X′(x, t), X H (x,t),[X H (x,t)]′、Y(x,t)、Y′(x,t)、Y H (x,t) and [Y H (x, t)]′;

[0059] S400. Taking each sample point in the curvelet domain as the center, intercept a record block of appropriate size, where the record block size is q*k (q>1, k>1), where q and k are the number of horizontal and vertical blocks of the intercepted record block, respectively, and use the data in the intercepted record block to construct an extended expression of the curvelet domain shear wave leakage noise of the partition block:

[0060]

[0061] In the formula, c i X (i=1,2...n),c i XD (i=1,2...n),c i XH (i=1,2...n),c i XHD (i=1,2...n),c i Y (i=1,2...n),c i YD (i=1,2...n),c i YH (i=1,2...n) and c i YHD (i=1,2...n) are c X (j,l,k),c XD(j,l,k),c XH (j,l,k),c XHD (j,l,k),c Y (j,l,k),c YD (j,l,k),c YH (j,l,k) and c YHD (j, l, k) are the sample points of each item in the intercepted record block; n is the sequence number of the sample point in the intercepted record block (to ensure the stability of the equation solution, n ≥ 4 is usually required); f n1 、f n2 、f n3 、f n4 、f n5 、f n6 、f n7 and f n8 are the matching factors to be sought in the intercepted record blocks corresponding to f1, f2, f3, f4, f5, f6, f7 and f8 respectively; c n is the sample point in the record block;

[0062] S500. Obtain the matching factor of each sample point in the record block intercepted by equation (4) based on the following equation (5):

[0063] f=(M T M+εI) -1 (M T C) (5)

[0064] Where f is the matching factor vector [f n1 ,f n2 ,f n3 ,f n4 ,f n5 ,f n6 ,f n7 ,f n8 ] T ; M is the intercepted record block c i X (i=1,2...n),c i XD (i=1,2...n),c i XH (i=1,2...n),c i XHD (i=1,2...n),c i Y (i=1,2...n),c i YD (i=1,2...n),c i YH (i=1,2...n) and c i YHD(i=1,2...n);C is the sample point c in the intercepted record block i (i=1,2...n) vector; I is the unit matrix; ε is the damping coefficient (ε∈(0,1), usually 0.001);

[0065] S600. Based on the matching factor obtained in step S500, the following formula (6) can be used to implement the shear wave leakage noise matching subtraction processing for the Z component data curve coefficient target point:

[0066]

[0067] Where p(j,l,k) is the curve coefficient of the Z component that eliminates the shear wave leakage noise;

[0068] S700. Repeat steps S400, S500 and S600 for each sample point in the curvelet domain to obtain the curvelet coefficient of the Z component that eliminates the shear wave leakage noise, and then use formula (7) to inversely transform it back to the time-space domain to obtain the Z component data that eliminates the shear wave leakage noise:

[0069]

[0070] In order to illustrate the effectiveness of the method of the present invention, the noise removal effect of the conventional curvelet transform is compared. The shear wave leakage noise removal results based on the conventional curvelet transform method are shown in Figure 4 (a), the shear wave noise removed is shown in Figure 4 (b) The results of shear wave leakage noise removal using curvelet domain extension filtering are shown in Figure 4 (c), the removed shear wave noise is shown in Figure 4 (d) As shown in Figure 5, in the removed shot set based on the curvelet domain extension filter, the residual shear wave noise is significantly less than the result of the conventional curvelet transform (as shown in the red circle in the figure), and there is no obvious effective wave information in the removed noise, indicating that the shear wave leakage removal accuracy of the curvelet domain extension filter is significantly higher than that of the conventional curvelet transform method.

[0071] The Z component near-offset profile before shear wave noise removal is shown in Figure 5(a), the Z component near-offset profile after conventional curvelet transform noise removal is shown in Figure 5(b), and the Z component near-offset profile after curvelet domain extended filtering noise removal is shown in Figure 5(c). As shown in Figure 5, the shear wave noise in the Z component near-offset profile after curvelet domain extended filtering noise removal is also significantly less than the conventional curvelet transform noise removal result. The model experiment results show that the method of the present invention takes into account the advantages of curvelet transform in separating effective signals and shear wave leakage noise and the adaptability of extended filtering to shear wave leakage prediction errors. It can significantly improve the removal accuracy of shear wave leakage interference while avoiding damage to effective signals, thereby improving the imaging accuracy of OBN data.

[0072] Embodiment 2:

[0073] This embodiment provides a processing device for implementing the OBN shear wave leakage noise attenuation method based on curvelet domain expansion filtering provided in this embodiment 1. The processing device can be a processing device for a client, such as a mobile phone, a laptop computer, a tablet computer, a desktop computer, etc., to execute the method of embodiment 1.

[0074] The processing device includes a processor, a memory, a communication interface and a bus, and the processor, the memory and the communication interface are connected through the bus to complete mutual communication. The memory stores a computer program that can be run on the processor, and the processor executes the OBN shear wave leakage noise attenuation method based on curvelet domain expansion filtering provided in this embodiment 1 when running the computer program.

[0075] Preferably, the memory may be a high-speed random access memory (RAM), and may also include a non-volatile memory, such as at least one disk memory.

[0076] Preferably, the processor may be a central processing unit (CPU), a digital signal processor (DSP) or other general-purpose processors of various types, which are not limited here.

[0077] Embodiment 3:

[0078] The OBN shear wave leakage noise attenuation method based on curvelet domain extension filtering of this embodiment 1 can be specifically implemented as a computer program product. The computer program product may include a computer-readable storage medium carrying computer-readable program instructions for executing the method described in this embodiment 1.

[0079] Computer readable storage media can be tangible devices that hold and store instructions used by instruction execution devices. Computer readable storage media can be, for example, but not limited to, electronic storage devices, magnetic storage devices, optical storage devices, electromagnetic storage devices, semiconductor storage devices, or any combination thereof.

[0080] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them; although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or replace some or all of the technical features therein by equivalents; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the scope of the technical solutions of the embodiments of the present application, and they should all be included in the scope of the claims and specification of the present application. In particular, as long as there is no structural conflict, the various technical features mentioned in the various embodiments can be combined in any way. The present application is not limited to the specific embodiments disclosed herein, but includes all technical solutions that fall within the scope of the claims.

Claims

1. A method for attenuating OBN shear wave leakage noise based on curvelet domain extension filtering, characterized in that: The following steps are involved: S100. Based on the X and Y component data in the OBN data, the shear wave leakage noise in the Z component data is expressed as Z N (x,t); S200. The shear wave leakage noise Z in the Z component data is N (x, t) is converted to the curvelet domain; S300. Transverse wave leakage noise Z N The curvelet coefficient of (x, t) is expanded by integral terms to obtain the expansion of the curvelet coefficient; S400. Taking each sample point in the curvelet domain as the center, intercepting a record block of appropriate size, and constructing an extended expression of the curvelet domain shear wave leakage noise of the partition block using the data in the intercepted record block; S500. Obtain the matching factor of each sample point in the intercepted record block; S600. Based on the obtained matching factor, the shear wave leakage noise matching subtraction processing is implemented for the target point of the Z component data curve coefficient; S700. Repeat steps S400, S500 and S600 for each sample point in the curvelet domain to obtain the curvelet coefficient of the Z component that eliminates the shear wave leakage noise, and then inversely transform it back to the time-space domain to obtain the Z component data that eliminates the shear wave leakage noise.

2. The OBN shear wave leakage noise attenuation method according to claim 1, characterized in that: In the above step S100, the shear wave leakage noise Z in the Z component data N The expression for (x,t) is as follows: Where x is the offset distance; t is the travel time; Z N (x, t) is the shear wave leakage noise in the Z component data; X(x, t) is the X component data; X′(x, t) is the time derivative of X(x, t); X H (x, t) is the Hilbert transform of X(x, t); [X H (x,t)]′ is X H (x, t); Y(x, t) is the time derivative of Y(x, t); Y′(x, t) is the time derivative of Y(x, t); Y H (x, t) is the Hilbert transform of Y(x, t); [Y H (x,t)]′ is Y H (x, t); f1, f2, f3, f4, f5, f6, f7 and f8 represent the time derivative of Z N The matching factors corresponding to each item when (x, t) is expanded to the sum of the above items.

3. The OBN shear wave leakage noise attenuation method according to claim 2, characterized in that: In the above step S200, the shear wave leakage noise Z in the Z component data is converted into N The formula for converting (x, t) to the curvelet domain is as follows: Where j, l and k represent the scale, direction and position of the curve wave respectively; c(j,l,k) is the curve wave coefficient of the shear wave leakage noise; Represents the curvelet basis function. In actual processing, the entire Z component data Z(x, t) can be used to replace Z N (x,t).

4. The OBN shear wave leakage noise attenuation method according to claim 3, characterized in that: In the above step S300, the expansion of the obtained curvelet coefficient is as follows: In the formula, c X (j,l,k),c XD (j,l,k),c XH (j,l,k),c XHD (j,l,k),c Y (j,l,k),c YD (j,l,k),c YH (j,l,k), and c YHD (j, l, k) are X(x, t), X′(x, t), X H (x,t),[X H (x,t)]′、Y(x,t)、Y′(x,t)、Y H (x,t) and [Y H (x, t)]′.

5. The OBN shear wave leakage noise attenuation method according to claim 4, characterized in that: In the above step S400, the record block size is q*k, q and k are the number of horizontal and vertical blocks of the intercepted record block, respectively, and the extended expression of the curvelet domain shear wave leakage noise of the constructed partition block is as follows: In the formula, c i X (i=1,2...n),c i XD (i=1,2...n),c i XH (i=1,2...n),c i XHD (i=1,2...n),c i Y (i=1,2...n),c i YD (i=1,2...n),c i YH (i=1,2...n) and c i YHD (i=1,2...n) are c X (j,l,k),c XD (j,l,k),c XH (j,l,k),c XHD (j,l,k),c Y (j,l,k),c YD (j,l,k),c YH (j,l,k) and c YHD (j, l, k) are the sample points in the intercepted record block; n is the sample point sequence number in the intercepted record block; f n1 、f n2 、f n3 、f n4 、f n5 、f n6 、f n7 and f n8 are the matching factors to be sought in the intercepted record blocks corresponding to f1, f2, f3, f4, f5, f6, f7 and f8 respectively; c n It is the sample point in the intercepted record block.

6. The OBN shear wave leakage noise attenuation method according to claim 5, characterized in that: In the above step S500, the matching factor of each sample point in the intercepted record block is obtained based on the following formula: f=(M T M+εI) -1 (M T C) (5) Where f is the matching factor vector [f n1 ,f n2 ,f n3 ,f n4 ,f n5 ,f n6 ,f n7 ,f n8 ] T ; M is the intercepted record block c i X (i=1,2...n),c i XD (i=1,2...n),c i XH (i=1,2...n),c i XHD (i=1,2...n),c i Y (i=1,2...n),c i YD (i=1,2...n),c i YH (i=1,2...n) and c i YHD (i=1,2...n);C is the sample point c in the intercepted record block i (i=1,2...n) vector; I is the unit matrix; ε is the damping coefficient.

7. The OBN shear wave leakage noise attenuation method according to claim 6, characterized in that: In the above step S600, the shear wave leakage noise matching subtraction processing for the Z component data curvelet coefficient target point is implemented using the following formula: Where p(j,l,k) is the curve coefficient of the Z component that eliminates the shear wave leakage noise.

8. The OBN shear wave leakage noise attenuation method according to claim 7, characterized in that: In the above step S700, the expression of the Z component data after eliminating the shear wave leakage noise is obtained as follows:

9. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the OBN shear wave leakage noise attenuation method according to any one of claims 1 to 8 are implemented.

10. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the steps of the OBN shear wave leakage noise attenuation method according to any one of claims 1 to 8 are implemented.

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