Signal-noise separation method and device based on plane wave reconstruction operator

Abstract

The invention relates to the technical field of seismic signal processing in oil-gas exploration and development, and particularly discloses a signal-noise separation method and device based on a plane wave reconstruction operator, and the method comprises the steps: constructing a reconstruction operator based on a plane wave; obtaining a noisy seismic data model expression based on the plane wave reconstruction operator; and separating and removing random noise from the noisy seismic data based on the model expression. According to the signal-noise separation method based on the plane wave reconstruction operator provided by the invention, model expression is performed on the effective signal through the plane wave reconstruction operator, and efficient and accurate separation of the effective signal and random noise of the noisy seismic data is realized in combination with a least square inverse problem solving algorithm.

Description

Technical Field

[0001] The present invention relates to the technical field of seismic signal processing in oil and gas exploration and development, and in particular to a signal-noise separation method and device based on a plane wave reconstruction operator. Background Art

[0002] Seismic data signal-noise separation is a key technology in the field of geophysical exploration. Seismic exploration obtains geological information by recording underground seismic signals, but there are often various interferences and noises in seismic data, which bring challenges to seismic data processing and interpretation, affecting the accurate identification and interpretation of underground structures and lithology.

[0003] The goal of signal-noise separation is to separate the signal from the noise in the seismic data and extract clear seismic signals to obtain more accurate underground models and exploration interpretations. In the past few decades, the technology of signal-noise separation of seismic data has undergone great development, and signal-noise separation plays an important role in seismic exploration. With the continuous advancement of science and technology and the improvement of computer computing power, modern signal-noise separation technology has become more accurate and efficient. Signal-noise separation algorithms based on statistical analysis, frequency domain filtering, wavelet transform, machine learning and other methods continue to emerge, which can better extract and fit seismic signals and remove and suppress noise.

[0004] Traditional signal-to-noise separation methods such as filter design and frequency domain methods may produce errors when the signal and noise overlap, resulting in the inability to accurately separate the signal and noise. Traditional methods are usually based on prior knowledge and assumptions about the signal and noise. If the characteristics of the signal or noise do not match the prior assumptions, the effectiveness of traditional methods may be limited.

[0005] Based on this technical background, the present invention studies a signal-noise separation method and device based on a plane wave reconstruction operator. Summary of the invention

[0006] In view of the shortcomings of the prior art, the present invention provides a signal-to-noise separation method and device based on a plane wave reconstruction operator. The method uses a plane wave reconstruction operator to model the effective signal, and combines it with a least squares inverse problem solving algorithm to achieve efficient and accurate separation of the effective signal and random noise of noisy seismic data.

[0007] In order to achieve the above object, a first aspect of the present invention provides a signal-noise separation method based on a plane wave reconstruction operator, comprising:

[0008] Constructing reconstruction operators based on plane waves;

[0009] Obtaining a noisy seismic data model expression based on the plane wave reconstruction operator;

[0010] Random noise is separated from noisy seismic data based on the model expression.

[0011] A second aspect of the present invention provides a signal-noise separation device based on a plane wave reconstruction operator, comprising:

[0012] Operator construction module, used to construct reconstruction operators based on plane waves;

[0013] A model acquisition module, used for obtaining a noisy seismic data model expression based on the plane wave reconstruction operator;

[0014] The noise separation module is used to separate random noise from noisy seismic data based on the model expression.

[0015] A third aspect of the present invention provides an electronic device, the electronic device comprising:

[0016] A memory storing executable instructions;

[0017] A processor, wherein the processor runs the executable instructions in the memory to implement the signal-to-noise separation method based on the plane wave reconstruction operator described in the first aspect.

[0018] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the signal-to-noise separation method based on a plane wave reconstruction operator described in the first aspect.

[0019] The beneficial effects of the present invention include:

[0020] The signal-to-noise separation method based on the plane wave reconstruction operator proposed in the present invention realizes efficient and accurate separation of effective signals and random noise in noisy seismic data by using a plane wave reconstruction operator to express the effective signal model and combining it with a least squares inverse problem solving algorithm.

[0021] Other features and advantages of the present invention will be described in detail in the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention with reference to the accompanying drawings.

[0023] Figure 1 This is a flow chart of the signal-noise separation method based on the plane wave reconstruction operator proposed in the present invention.

[0024] Figure 2 The invention provides noisy seismic data in a specific implementation of the signal-to-noise separation method based on the plane wave reconstruction operator.

[0025] Figure 3 This is denoised seismic data in a specific implementation of the signal-noise separation method based on the plane wave reconstruction operator proposed in the present invention.

[0026] Figure 4 The random noise is removed in a specific implementation of the signal-to-noise separation method based on the plane wave reconstruction operator proposed in the present invention. DETAILED DESCRIPTION

[0027] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0028] The present invention provides a signal-noise separation method based on a plane wave reconstruction operator, such as Figure 1 As shown, including:

[0029] Constructing reconstruction operators based on plane waves;

[0030] Based on the plane wave reconstruction operator, the model expression of noisy seismic data is obtained;

[0031] Separate random noise from noisy seismic data based on model expression.

[0032] In the present invention, the effective signal is modeled by a plane wave reconstruction operator and combined with a least squares inverse problem solving algorithm to achieve efficient and accurate separation of effective signals and random noise in noisy seismic data.

[0033] According to the present invention, the formula used to construct the reconstruction operator based on the plane wave is:

[0034] Ax = p;

[0035] Among them, A is a complex coefficient matrix, x is m-channel plane wave seismic data, and p is n-channel seismic data.

[0036] According to the present invention, the recursive formula used to reconstruct n-channel seismic data based on m-channel plane wave seismic data is:

[0037] p n+1 =a 1 p n +a 2 p n-1 +…a m p n-m+1 ;

[0038] Among them, P n+1 is the n+1th seismic data of m plane waves, a 1 ,a 2 ,…a m are m complex coefficients respectively.

[0039] According to the present invention, the frequency domain expression of adjacent traces of a single plane wave in m-trace plane wave seismic data is:

[0040] p(x n+1 ,ω)=p(x n ,ω)e -iωσdx ;

[0041] Among them, p(x n+1 ,ω) is the n+1th seismic data of a single plane wave, p(x n ,ω) nth channel seismic data of a single plane wave, e -iωσdx is the phase shift operator, σ is the spatial slope of the plane wave, ω is the frequency, and dx is the track spacing.

[0042] Preferably, the matrix expression of the complex coefficient matrix is:

[0043]

[0044] The matrix expression of X is:

[0045] X=(x 1 ,x 2 ,…,x m ) T ;

[0046] The matrix expression of p is:

[0047] p=(p 1 ,p 2 ,…,p m ) T .

[0048] Preferably, the noisy seismic data model expression is:

[0049]

[0050] Where d is the noisy seismic data, is the fitting result.

[0051] According to the present invention, the expression of noisy seismic data is:

[0052] d=p+n;

[0053] Among them, p is the effective signal and n is the random noise;

[0054] Separating random noise from noisy seismic data based on model expressions includes:

[0055] By inversion calculation After using the formula Get the denoising result, and then use the formula Get random noise.

[0056] The present invention will be described in more detail below by way of examples.

[0057] Embodiment 1:

[0058] This embodiment provides a signal-noise separation method based on a plane wave reconstruction operator, and the specific steps are as follows:

[0059] 1) Construction of plane wave reconstruction operator:

[0060] For a single plane wave, adjacent channels can be expressed in the frequency domain as:

[0061] p(x n+1 ,ω)=p(x n ,ω)e -iωσdx (1)

[0062] Among them, p(x n+1 ,ω) represents the n+1th seismic data, p(x n ,ω) represents the nth seismic data, e -iωσdx represents the phase shift operator, σ represents the spatial slope of the plane wave, ω represents the frequency, and dx represents the track spacing;

[0063] For m plane waves, the n+1th trace can be expressed as:

[0064] p n+1 =a 1 p n +a 2 p n-1 +…a m p n-m+1 (2)

[0065] Among them, p n =p(x n ,ω),a 1 ,a 2 ,…a m represents m complex coefficients;

[0066] By recursively calling formula (2), we can get the m-channel seismic data (x 1 ,x 2 ,…,x m ) reconstructs all n data, which can be expressed as a matrix as follows:

[0067]

[0068] It can be simply expressed as:

[0069] Ax=p (4)

[0070] Where p=(p 1 ,p 2 ,…,p m ) T Rebuild all n channels of data.

[0071] 2) Signal-to-noise separation based on plane wave reconstruction operator:

[0072] Noisy seismic data can be expressed as:

[0073] d=p+n (5)

[0074] Among them, d represents noisy seismic data, p represents effective signal, and n represents random noise.

[0075] In order to suppress random noise, the model parameters of the effective signal can be expressed by formula (4):

[0076] d=Ax+n (6)

[0077] Therefore, the denoising problem is transformed into the problem of estimating the signal model. The signal model is estimated by solving the following inverse problem:

[0078]

[0079] Inversion calculation Can be Get the denoising result. The noise can be obtained by Get.

[0080] Figure 2 is noisy seismic data, with 256 time sampling points, 128 channels and a sampling interval of 4ms. Figure 2 , Figure 3 and Figure 4 It can be seen from the comparison that the method of this embodiment achieves efficient and accurate separation of effective signals and random noise in noisy seismic data.

[0081] Embodiment 2:

[0082] This embodiment provides a signal-noise separation method based on a plane wave reconstruction operator. Figure 1 As shown, including:

[0083] Constructing reconstruction operators based on plane waves;

[0084] Based on the plane wave reconstruction operator, the model expression of noisy seismic data is obtained;

[0085] Separate random noise from noisy seismic data based on model expressions;

[0086] The formula used to construct the reconstruction operator based on plane waves is:

[0087] Ax = p;

[0088] Where A is a complex coefficient matrix, x is m-channel plane wave seismic data, and p is n-channel seismic data. The recursive formula used to reconstruct n-channel seismic data based on m-channel plane wave seismic data is:

[0089] p n+1 =a 1 p n +a 2 p n-1 +…a m p n-m+1 ;

[0090] Among them, P n+1 is the n+1th seismic data of m plane waves, a 1 ,a 2 ,…a m are m complex coefficients respectively;

[0091] The frequency domain expression of the adjacent traces of a single plane wave in m-channel plane wave seismic data is:

[0092] p(x n+1 ,ω)=p(x n ,ω)e -iωσdx ;

[0093] Among them, p(x n+1 ,ω) is the n+1th seismic data of a single plane wave, p(x n ,ω) nth channel seismic data of a single plane wave, e -iωσdx is the phase shift operator, σ is the spatial slope of the plane wave, ω is the frequency, and dx is the track spacing;

[0094] The matrix expression of the complex coefficient matrix is:

[0095]

[0096] The matrix expression of X is:

[0097] X=(x 1 ,x 2 ,…,x m ) T ;

[0098] The matrix expression of p is:

[0099] p=(p 1 ,p 2 ,…,p m ) T ;

[0100] The model expression of noisy seismic data is:

[0101]

[0102] Where d is the noisy seismic data, is the fitting result;

[0103] The expression for noisy seismic data is:

[0104] d=p+n;

[0105] Among them, p is the effective signal and n is the random noise;

[0106] Separating random noise from noisy seismic data based on model expressions includes:

[0107] By inversion calculation After using the formula Get the denoising result, and then use the formula Get random noise.

[0108] Embodiment three:

[0109] This embodiment provides a signal-noise separation device based on a plane wave reconstruction operator, comprising:

[0110] Operator construction module, used to construct reconstruction operators based on plane waves;

[0111] A model acquisition module, used to obtain a model expression of noisy seismic data based on a plane wave reconstruction operator;

[0112] Noise separation module, used to separate random noise from noisy seismic data based on model expressions. ;

[0113] The formula used to construct the reconstruction operator based on plane waves is:

[0114] Ax = p;

[0115] Where A is a complex coefficient matrix, x is m-channel plane wave seismic data, and p is n-channel seismic data. The recursive formula used to reconstruct n-channel seismic data based on m-channel plane wave seismic data is:

[0116] p n+1 =a 1 p n +a 2 p n-1 +…a m p n-m+1 ;

[0117] Among them, P n+1 is the n+1th seismic data of m plane waves, a 1 ,a 2 ,…a m are m complex coefficients respectively;

[0118] The frequency domain expression of the adjacent traces of a single plane wave in m-channel plane wave seismic data is:

[0119] p(x n+1 ,ω)=p(x n ,ω)e -iωσdx ;

[0120] Among them, p(x n+1 ,ω) is the n+1th seismic data of a single plane wave, p(x n ,ω) nth channel seismic data of a single plane wave, e -iωσdx is the phase shift operator, σ is the spatial slope of the plane wave, ω is the frequency, and dx is the track spacing;

[0121] The matrix expression of the complex coefficient matrix is:

[0122]

[0123] The matrix expression of X is:

[0124] X=(x 1 ,x 2 ,…,x m ) T ;

[0125] The matrix expression of p is:

[0126] p=(p 1 ,p 2 ,…,p m ) T ;

[0127] The model expression of noisy seismic data is:

[0128]

[0129] Where d is the noisy seismic data, is the fitting result;

[0130] The expression for noisy seismic data is:

[0131] d=p+n;

[0132] Among them, p is the effective signal and n is the random noise;

[0133] Separating random noise from noisy seismic data based on model expressions includes:

[0134] By inversion calculation After using the formula Get the denoising result, and then use the formula Get random noise.

[0135] Embodiment 4:

[0136] An embodiment of the present invention provides an electronic device including a memory and a processor.

[0137] A memory storing executable instructions;

[0138] The processor runs the executable instructions in the memory to implement a signal-noise separation method based on a plane wave reconstruction operator.

[0139] The memory is used to store non-temporary computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0140] The processor may be a central processing unit (CPU) or other forms of processing units with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the present invention, the processor is used to run the computer-readable instructions stored in the memory.

[0141] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present invention.

[0142] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0143] Embodiment five:

[0144] An embodiment of the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, a signal-noise separation method based on a plane wave reconstruction operator is implemented.

[0145] The computer-readable storage medium according to the embodiment of the present invention stores non-transitory computer-readable instructions, and when the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the above-mentioned methods of the embodiments of the present invention are executed.

[0146] The above-mentioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0147] The signal-to-noise separation method based on the plane wave reconstruction operator proposed in the embodiment of the present invention expresses the effective signal by modeling through the plane wave reconstruction operator and combines it with the least squares inverse problem solving algorithm to achieve efficient and accurate separation of the effective signal and random noise of noisy seismic data.

[0148] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A signal-noise separation method based on plane wave reconstruction operator, It is characterized in that include: Constructing reconstruction operators based on plane waves; Obtaining a noisy seismic data model expression based on the plane wave reconstruction operator; Random noise is separated from noisy seismic data based on the model expression.

2. The method according to claim 1, It is characterized in that The formula used to construct the reconstruction operator based on plane waves is: Ax = p; Among them, A is a complex coefficient matrix, x is m-channel plane wave seismic data, and p is n-channel seismic data.

3. The method according to claim 2, It is characterized in that The recursive formula used to reconstruct n-channel seismic data based on m-channel plane wave seismic data is: p n+1 =a 1 p n +a 2 p n-1 +…a m p n-m+1 ; Among them, P n+1 is the n+1th seismic data of m plane waves, a 1 ,a 2 ,…a m are m complex coefficients respectively.

4. The method according to claim 3, It is characterized in that The frequency domain expression of the adjacent traces of a single plane wave in m-channel plane wave seismic data is: p(x n+1 ,ω)=p(x n ,ω)e -iωσdx ; Among them, p(x n+1 ,ω) is the n+1th seismic data of a single plane wave, p(x n ,ω) nth channel seismic data of a single plane wave, e -iωσdx is the phase shift operator, σ is the spatial slope of the plane wave, ω is the frequency, and dx is the track spacing.

5. The method according to claim 4, It is characterized in that The matrix expression of the complex coefficient matrix is: The matrix expression of X is: X=(x 1 ,x 2 ,…,x m ) T ; The matrix expression of p is: p=(p 1 ,p 2 ,…,p m ) T 。 6. The method according to claim 5, It is characterized in that The noisy seismic data model expression is: Where d is the noisy seismic data, is the fitting result.

7. The method according to claim 6, It is characterized in that The expression for noisy seismic data is: d=p+n; Among them, p is the effective signal and n is the random noise; Separating random noise from noisy seismic data based on the model expression includes: By inversion calculation After using the formula Get the denoising result, and then use the formula Get random noise.

8. A signal-noise separation device based on plane wave reconstruction operator, It is characterized in that include: Operator construction module, used to construct reconstruction operators based on plane waves; A model acquisition module, used for obtaining a noisy seismic data model expression based on the plane wave reconstruction operator; The noise separation module is used to separate random noise from noisy seismic data based on the model expression.

9. An electronic device, It is characterized in that The electronic device comprises: A memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement the signal-to-noise separation method based on a plane wave reconstruction operator according to any one of claims 1 to 7.

10. A computer-readable storage medium, It is characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the signal-to-noise separation method based on a plane wave reconstruction operator according to any one of claims 1 to 7 is implemented.

Images