Land interlayer multiple suppression method and device

Abstract

The invention provides a land interlayer multiple suppression method and device, and relates to the technical field of seismic data processing. According to the technical scheme, the land interlayer multiple suppression method comprises the steps that seismic data needing land interlayer multiple suppression are acquired; performing far-trace noise removal and random noise suppression on the seismic data to obtain de-noised data; based on the de-noised data, using multiples to remove medium and far offset data to fit an amplitude curve, and approximately calculating theoretical seismic data not including multiples according to the amplitude curve; calculating a normalized cross correlation coefficient of the theoretical seismic data and the actual data; and performing data reconstruction according to the normalized cross correlation coefficient to obtain seismic data after land interlayer multiple suppression. The method has the advantages that data reconstruction is carried out through AVA fitting and the normalized cross correlation coefficient, and land earthquake near-trace interlayer multiples are suppressed.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic data processing, and in particular to a method and device for suppressing multiple waves between land layers. Background Art

[0002] The attenuation of multiple waves is one of the most prominent problems in land seismic data processing. At present, there are two main methods for attenuating land multiple waves: filtering method and attenuation method based on wave theory. Among them, filtering method mainly uses the difference in apparent velocity between multiple waves and primary waves or the periodicity of multiple waves (such as predictive deconvolution method), and such methods have fast calculation speed. However, they can only effectively attenuate land multiple waves when there is a large difference in apparent velocity between primary waves and multiple waves.

[0003] Therefore, for the mid-to-far offset part of land seismic data, the time difference between the primary wave and the multiple waves is large, and it is relatively easy to suppress it using conventional filtering methods; however, in the near-offset part, the time difference between the multiple waves and the primary wave is small, and they interfere with each other, making it difficult to suppress. The existence of the remaining interlayer multiple waves, especially the near-track small difference interlayer multiple waves, will affect the accuracy of prestack inversion. In order to protect the effective signal, the current suppression method will still leave a lot of near-track multiple waves, which seriously affects the use of the subsequent AVO technology for the near-track information. Summary of the invention

[0004] In view of the above problems, the present invention is proposed to provide a method and device for suppressing multiple waves between land layers that overcome the above problems or at least partially solve the above problems.

[0005] In order to achieve the above object, the present invention provides a method for suppressing multiple waves between land layers, which is characterized by comprising:

[0006] Acquisition of seismic data requiring land-layer multiple suppression;

[0007] Perform long-path noise removal and random noise suppression on seismic data to obtain denoised data;

[0008] Based on the denoised data, an amplitude curve is fitted by removing the mid-to-far offset data using multiple waves, and a theoretical seismic data excluding multiple waves is approximately calculated according to the amplitude curve;

[0009] Calculating the normalized mutual correlation coefficient between the theoretical seismic data and the actual data;

[0010] Data reconstruction is performed according to the normalized mutual correlation coefficient to obtain seismic data after multiple wave suppression between land layers.

[0011] The seismic data that require land layer multiple wave suppression are time domain or depth domain common imaging point seismic data.

[0012] The long-path noise removal is to use double-path reflection travel time and offset distance data pairs to form a removal line, and remove the common imaging point seismic data outside.

[0013] The random noise suppression is performed on the basis of the external excision of the seismic data of the common imaging point. The random noise suppression method is adopted to remove noise without losing high-frequency information or reducing the lateral resolution, further suppressing random noise and improving the signal-to-noise ratio.

[0014] The relationship between the sampling value and the offset distance of the seismic signal at any time t in the common imaging point seismic data is represented by a polynomial;

[0015] The polynomial is:

[0016] Where x i is the offset distance of the ith track; A(x i ) is the amplitude value of the i-th channel at time t; a0, a1, …, a m is a constant coefficient; r(x i ) is the higher-order error.

[0017] The polynomial ignores the errors of higher-order terms and can be expressed by the vector matrix formula, specifically:

[0018]

[0019] Solving the coefficients of the polynomial using a damped least squares method;

[0020] Specifically: Construct the objective function, the vector matrix formula can also be written as

[0021] J=(A-Xa) T (A-Xa)+ε 2 a T a; (3)

[0022] At the minimum value of the objective function, that is, When , the least squares estimation formula of the coefficients of the polynomial is obtained:

[0023] Where W = (X T X+ε 2 I) -1 X T =Y -1 X T ;

[0024] The advantage of using damped least squares method to solve polynomial coefficients is that T X is a symmetric positive definite matrix, so it can be orthogonally decomposed into XT X=RVR T , where R is X T The eigenvector of X, V is the eigenvector of X T The diagonal matrix formula composed of the eigenvalues ​​of X is:

[0025]

[0026] Among them, λ i For X T X is the i-th eigenvalue, and r is the rank of the matrix. Therefore, the condition number of the matrix is ​​formula (6):

[0027]

[0028] (X T X+ε 2 I) becomes the diagonal matrix composed of the eigenvalues ​​of formula (7):

[0029]

[0030] The condition number of this matrix is ​​given by formula (8):

[0031]

[0032] cond(X T X+ε 2 I) <cond(X T X), it can be seen that after adding the damping factor, the condition number becomes smaller, the ill-conditioned degree of the matrix is ​​reduced, and the calculation accuracy is improved.

[0033] Select the mid-to-far offset traces with better multiple wave suppression to participate in the AVA amplitude fitting calculation, and get The fitting calculation formula is:

[0034]

[0035] The amplitude value of the seismic trace at time t is calculated based on the fitting calculation formula. The amplitude value of the seismic trace at time t can be approximately calculated by formula (10). The amplitude value formula is:

[0036]

[0037] Theoretical seismic data without multiple waves is obtained based on the amplitude value

[0038] The earthquake data obtained by the amplitude formula and Compared with the original seismic data S and the mean S 均值 Perform normalized mutual correlation coefficient analysis and define the normalized mutual correlation coefficient G as the formula:

[0039]

[0040] The calculated seismic data is accurately described by formula (11) Original seismic data S, mean S 均值 The correlation between the calculated seismic traces and the actual seismic traces is improved by increasing the normalized cross-correlation. The larger the calculated normalized cross-correlation value is, the higher the similarity between the calculated seismic traces and the actual seismic traces is.

[0041] After obtaining the normalized correlation coefficient between the calculated seismic trace and the actual seismic trace, the seismic data after suppressing the interlayer multiple waves are reconstructed using the formula S*(t) to achieve the purpose of removing the interlayer multiple waves of the land near-trace with amplitude preservation:

[0042]

[0043] Furthermore, a device for suppressing multiple waves between land layers is provided, comprising:

[0044] An acquisition module, used to acquire seismic data requiring land layer multiple wave suppression;

[0045] Data processing module, used for removing long-channel noise and suppressing random noise on seismic data;

[0046] The fitting module is used to fit the amplitude curve using the multiple wave removal medium and far offset data;

[0047] The calculation module is used to calculate theoretical seismic data, normalized cross-correlation coefficients between theoretical seismic data and actual data, and reconstruct data according to the normalized cross-correlation coefficients to obtain seismic data after multiple wave suppression between land layers.

[0048] Furthermore, an electronic device is provided, comprising: a processor and a memory, wherein the processor is used to execute a land layer multiple wave suppression program stored in the memory to implement the land layer multiple wave suppression method described above.

[0049] Furthermore, a storage medium is provided, comprising: the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the land layer multiple wave suppression method described above.

[0050] Compared with the prior art, the present invention has the following advantages and positive effects:

[0051] The invention provides a land interlayer multiple wave suppression method. The method utilizes AVA fitting and normalized cross-correlation coefficients to reconstruct data, suppresses land seismic near-track interlayer multiple waves, and the amplitude of the event axis after suppressing the interlayer multiple waves has an AVO trend, which is beneficial to the use of pre-stack near-track information by the AVO technology. When performing data calculation, the data is denoised, and the denoising does not affect the lateral resolution, does not reduce the lateral resolution of seismic waves, and does not lose high-frequency information, so as to achieve the purpose of removing near-track interlayer multiple waves with amplitude preservation and improving the signal-to-noise ratio of seismic data. The damped least square method is used to solve the coefficients of the polynomial, so that the morbidity of the matrix is ​​reduced and the calculation accuracy is improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0053] Figure 1 A schematic flow chart of a method for suppressing multiple waves between land layers provided by an embodiment of the present invention;

[0054] Figure 2 The data of interlayer multiple waves existing in the near track of land earthquake in the embodiment of the present invention;

[0055] Figure 3 This is the effect of applying the land layer multiple wave suppression method in the embodiment of the present invention;

[0056] Figure 4 is the near-path interlayer multiple wave suppressed in the embodiment of the present invention;

[0057] Figure 5 A land layer multiple wave suppression device in an embodiment of the present invention;

[0058] Figure 6 The figure is a schematic diagram of the structure of an electronic device in an embodiment of the present invention. DETAILED DESCRIPTION

[0059] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. 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 creative work are within the scope of protection of the present invention.

[0060] To facilitate understanding of the embodiments of the present invention, specific embodiments will be further explained below in conjunction with the accompanying drawings. The embodiments do not constitute a limitation on the embodiments of the present invention.

[0061] Embodiment 1:

[0062] See also Figure 1-Figure 4 The present invention provides a method for suppressing multiple waves between land layers, which is characterized by comprising:

[0063] S11, obtaining seismic data requiring land layer multiple wave suppression;

[0064] S12, performing long-channel noise removal and random noise suppression on the seismic data to obtain denoised data;

[0065] S13, based on the denoised data, using multiple waves to remove the mid- and long-offset data to fit an amplitude curve, and approximately calculating theoretical seismic data that does not contain multiple waves according to the amplitude curve;

[0066] S14, calculating the normalized correlation coefficient between the theoretical seismic data and the actual data;

[0067] S15. Reconstruct data according to the normalized mutual correlation coefficient to obtain seismic data after multiple wave suppression between land layers.

[0068] The seismic data that require land layer multiple wave suppression are time domain or depth domain common imaging point seismic data.

[0069] The long-path noise removal is to use double-path reflection travel time and offset distance data pairs to form a removal line, and remove the common imaging point seismic data outside.

[0070] The random noise suppression is performed on the basis of the external excision of the seismic data of the common imaging point. The random noise suppression method is adopted to remove noise without losing high-frequency information or reducing the lateral resolution, further suppressing random noise and improving the signal-to-noise ratio.

[0071] The relationship between the sampling value and the offset distance of the seismic signal at any time t in the common imaging point seismic data is represented by a polynomial;

[0072] The polynomial is:

[0073] Where x i is the offset distance of the ith track; A(x i ) is the amplitude value of the i-th channel at time t; a0, a1, …, a m is a constant coefficient; r(x i ) is the higher-order error.

[0074] The polynomial ignores the errors of higher-order terms and can be expressed by the vector matrix formula, specifically:

[0075]

[0076] Solving the coefficients of the polynomial using a damped least squares method;

[0077] Specifically: Construct the objective function, the vector matrix formula can also be written as

[0078] J=(A-Xa) T (A-Xa)+ε 2 a T a; (3)

[0079] At the minimum value of the objective function, that is, When , the least squares estimation formula of the coefficients of the polynomial is obtained:

[0080] Where W = (X T X+ε 2 I) -1 X T =Y -1 X T ;

[0081] The advantage of using damped least squares method to solve polynomial coefficients is that T X is a symmetric positive definite matrix, so it can be orthogonally decomposed into X T X=RVR T , where R is X T The eigenvector of X, V is the eigenvector of X T The diagonal matrix formula composed of the eigenvalues ​​of X is:

[0082]

[0083] Among them, λ i For X T X is the i-th eigenvalue, and r is the rank of the matrix. Therefore, the condition number of the matrix is ​​formula (6):

[0084]

[0085] (X T X+ε 2 I) becomes the diagonal matrix composed of the eigenvalues ​​of formula (7):

[0086]

[0087] The condition number of this matrix is ​​given by formula (8):

[0088]

[0089] cond(X T X+ε 2 I) <cond(X T X), it can be seen that after adding the damping factor, the condition number becomes smaller, the ill-conditioned degree of the matrix is ​​reduced, and the calculation accuracy is improved.

[0090] Select the mid-to-far offset traces with better multiple wave suppression to participate in the AVA amplitude fitting calculation, and get The fitting calculation formula is:

[0091]

[0092] The amplitude value of the seismic trace at time t is calculated based on the fitting calculation formula. The amplitude value of the seismic trace at time t can be approximately calculated by formula (10). The amplitude value formula is:

[0093]

[0094] Theoretical seismic data without multiple waves is obtained based on the amplitude value

[0095] The earthquake data obtained by the amplitude formula and Compared with the original seismic data S and the mean S 均值 Perform normalized mutual correlation coefficient analysis and define the normalized mutual correlation coefficient G as the formula:

[0096]

[0097] The calculated seismic data is accurately described by formula (11) Original seismic data S, mean S 均值 The correlation between the calculated seismic traces and the actual seismic traces is improved by increasing the normalized cross-correlation. The larger the calculated normalized cross-correlation value is, the higher the similarity between the calculated seismic traces and the actual seismic traces is.

[0098] After obtaining the normalized correlation coefficient between the calculated seismic trace and the actual seismic trace, the seismic data after suppressing the interlayer multiple waves are reconstructed using the formula S*(t) to achieve the purpose of removing the interlayer multiple waves of the land near-trace with amplitude preservation:

[0099]

[0100] Specific embodiment: Figure 2 It is the data of the existence of interlayer multiple waves in the land near track; Figure 3 This is the effect of applying the land layer multiple wave suppression method of the present invention. Figure 3 It can be seen that the pre-stack near-interlayer multiple waves are effectively suppressed. Figure 4 It is the suppressed near-channel interlayer multiple wave. Figure 4 It can be seen that there is no effective near-track seismic information in the suppressed residual interlayer multiple waves, and the amplitude preservation is good.

[0101] This method uses AVA fitting and normalized cross-correlation coefficients to reconstruct data and suppress interlayer multiple waves of land seismic near-track. The amplitude of the event axis after suppressing the interlayer multiple waves has an AVO trend, which is conducive to the use of pre-stack near-track information by AVO technology. The data is denoised during data calculation without affecting the lateral resolution, reducing the lateral resolution of seismic waves, or losing high-frequency information, thereby achieving the purpose of removing near-track interlayer multiple waves with amplitude preservation and improving the signal-to-noise ratio of seismic data. The damped least squares method is used to solve the coefficients of the polynomial, which reduces the morbidity of the matrix and improves the calculation accuracy.

[0102] Embodiment 2:

[0103] See also Figure 5 On the basis of the first embodiment, a device for suppressing multiple waves between land layers is provided, which can complete the method for suppressing multiple waves between land layers in the first embodiment, and includes:

[0104] An acquisition module 701 is used to acquire seismic data that requires land layer multiple wave suppression;

[0105] Data processing module 702, used for performing long-channel noise removal and random noise suppression on seismic data;

[0106] A fitting module 703 is used to fit the amplitude curve using the multiple wave removal medium and far offset data;

[0107] The calculation module 704 is used to calculate theoretical seismic data, normalized cross-correlation coefficients between theoretical seismic data and actual data, and reconstruct data according to the normalized cross-correlation coefficients to obtain seismic data after multiple wave suppression between land layers.

[0108] Embodiment three:

[0109] An electronic device is also provided, comprising: a processor and a memory, wherein the processor is used to execute a land layer multiple wave suppression program stored in the memory to implement the land layer multiple wave suppression method described in the first embodiment. Figure 6 The electronic device 800 shown includes: at least one processor 801, a memory 802, at least one network interface 804 and other user interfaces 803. The various components in the electronic device 800 are coupled together via a bus system 805. It is understood that the bus system 805 is used to achieve connection and communication between these components. In addition to the data bus, the bus system 805 also includes a power bus, a control bus and a status signal bus. However, for the sake of clarity, the bus system 805 is not described in detail. Figure 6 Various buses are labeled as bus system 805 .

[0110] The user interface 803 may include a display, a keyboard, or a pointing device (eg, a mouse, a trackball, a touch pad, or a touch screen).

[0111] It is understood that the memory 802 in the embodiment of the present invention can be a volatile memory or a non-volatile memory, or can include both volatile and non-volatile memories. Among them, the non-volatile memory can be a read-only memory, a programmable read-only memory, an erasable programmable read-only memory, an electrically erasable programmable read-only memory or a flash memory. The volatile memory can be a random access memory, which is used as an external cache. By way of example but not limitation, many forms of RAM are available, such as static random access memory, dynamic random access memory, synchronous dynamic random access memory, double data rate synchronous dynamic random access memory, enhanced synchronous dynamic random access memory, synchronous connection dynamic random access memory and direct memory bus random access memory. The memory 802 described herein is intended to include but is not limited to these and any other suitable types of memory.

[0112] In some implementations, the memory 802 stores the following elements, executable units or data structures, or a subset thereof, or an extended set thereof: an operating system 8021 and an application program 8022 .

[0113] The operating system 8021 includes various system programs, such as a framework layer, a core library layer, a driver layer, etc., which are used to implement various basic services and process hardware-based tasks. The application program 8022 includes various application programs, such as a media player, a browser, etc., which are used to implement various application services. The program for implementing the method of the embodiment of the present invention can be included in the application program 8022.

[0114] In the embodiment of the present invention, by calling the program or instruction stored in the memory 802, specifically, the program or instruction stored in the application 8022, the processor 801 is used to execute the method steps provided in each method embodiment 1.

[0115] Embodiment 4:

[0116] A storage medium is also provided, including: the storage medium stores one or more programs, and the one or more programs can be executed by one or more processors to implement the land layer multiple wave suppression method described in Example 1.

[0117] The steps of the method or algorithm described in conjunction with the embodiments disclosed herein may be implemented using hardware, a software module executed by a processor, or a combination of the two. The software module may be placed in a random access memory, a memory, a read-only memory, an electrically programmable, an electrically erasable programmable, a register, a hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art.

[0118] The above specific implementation methods further illustrate the objectives, technical solutions and beneficial effects of the present invention in detail. It should be understood that the above are only specific implementation methods of the present invention and are not intended to limit the scope of protection of the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the scope of protection of the present invention.

Claims

1. A method for suppressing multiple waves between land layers, characterized in that: include: Acquisition of seismic data requiring land-layer multiple suppression; Perform long-path noise removal and random noise suppression on seismic data to obtain denoised data; Based on the denoised data, an amplitude curve is fitted by removing the mid-to-far offset data using multiple waves, and a theoretical seismic data excluding multiple waves is approximately calculated according to the amplitude curve; Calculating the normalized mutual correlation coefficient between the theoretical seismic data and the actual data; Data reconstruction is performed according to the normalized mutual correlation coefficient to obtain seismic data after multiple wave suppression between land layers.

2. The method for suppressing multiple waves between land layers according to claim 1, characterized in that: The seismic data that require land layer multiple wave suppression are time domain or depth domain common imaging point seismic data.

3. The method for suppressing multiple waves between land layers according to claim 1 or 2, characterized in that: The long-path noise removal is to use double-path reflection travel time and offset distance data pairs to form a removal line, and remove the common imaging point seismic data outside.

4. The method for suppressing multiple waves between land layers according to claim 3, characterized in that: The random noise suppression is performed on the basis of the external excision of the seismic data of the common imaging points.

5. The method for suppressing multiple waves between land layers according to claim 2, characterized in that: The relationship between the sampling value and the offset distance of the seismic signal at any time t in the common imaging point seismic data is represented by a polynomial; The polynomial is: Where x i is the offset distance of the ith track; A(x i ) is the amplitude value of the i-th channel at time t; a0, a1, …, a m is a constant coefficient; r(x i ) is the higher-order error.

6. The method for suppressing multiple waves between land layers according to claim 5, characterized in that: Solving the coefficients of the polynomial using a damped least squares method; Specifically, the objective function is constructed; at the minimum value of the objective function, the least squares estimation formula of the coefficients of the polynomial is obtained:

7. The method for suppressing multiple waves between land layers according to claim 6, characterized in that: The mid-to-far offset traces with better multiple wave suppression are selected to participate in the amplitude fitting calculation. The fitting calculation formula is:

8. The method for suppressing multiple waves between land layers according to claim 7, characterized in that: The amplitude value of the seismic trace at time t is calculated based on the fitting calculation formula. The amplitude value formula is: Theoretical seismic data without multiple waves is obtained based on the amplitude value 9. The method for suppressing multiple waves between land layers according to claim 8, characterized in that: The earthquake data obtained by the amplitude formula and Compared with the original seismic data S and the mean S 均值 Perform normalized mutual correlation coefficient analysis and define the normalized mutual correlation coefficient G as the formula: Using formula S * (t) Reconstruction of seismic data after suppressing interlayer multiple waves:

10. A land layer multiple wave suppression device, characterized in that: include: An acquisition module, used to acquire seismic data requiring land layer multiple wave suppression; Data processing module, used for removing long-channel noise and suppressing random noise on seismic data; The fitting module is used to fit the amplitude curve using the multiple wave removal medium and far offset data; The calculation module is used to calculate theoretical seismic data, normalized cross-correlation coefficients between theoretical seismic data and actual data, and reconstruct data according to the normalized cross-correlation coefficients to obtain seismic data after multiple wave suppression between land layers.

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