A method for enhancing ground microseismic event signals

Abstract

The application discloses a ground microseismic event signal enhancement method, comprising the following steps: 1) obtaining a ground microseismic signal after dynamic correction containing noise according to a ground microseismic event signal; 2) obtaining time slice data at a given time point t1; 3) constructing a hankel matrix of each trace for the time slice data; 4) performing random singular value decomposition on the rearranged Hankel matrix of each time slice; 5) adding a damping operator to suppress the random noise of the residual error; 6) using Hankel matrix inverse transformation to transform the reconstructed matrix after truncation of singular values back to time slice data, and obtaining signal data after noise suppression; 7) repeating steps 2) to 6) until all time slices are processed, and obtaining an enhanced signal of the original ground microseismic event signal. The application can highlight the effective signal energy of the ground microseismic event, suppress noise interference, improve the ground microseismic event signal energy ratio, and enhance the effective signal identification capability.

Description

TECHNICAL FIELD

[0001] The present application relates to oil exploration and development technology, and particularly to a ground microseismic event signal enhancement method. BACKGROUND

[0002] Microseismic fracture monitoring technology has now become a commonly used monitoring technology in unconventional oil and gas field development, and its most important application is the monitoring of hydraulic fracture distribution. The spatio-temporal distribution characteristics of microseismic event group are the key to the spatial distribution characteristics and fracture network development process interpretation of subsequent fracture network, so microseismic event picking is crucial.

[0003] In the existing workflow, the identification of effective signal events adopts a long-short time window characteristic value ratio method, and under the condition of high signal-to-noise ratio, the effective microseismic events can be automatically identified by setting a suitable threshold value. The ground microseismic data has the characteristics of low signal-to-noise ratio, and the long-short time window characteristic ratio method has a high misidentification rate. The signal enhancement method can enhance the energy ratio of effective events, and the noise invalid events remain basically unchanged. Through signal enhancement, the identification capability of the long-short time window characteristic value ratio method can be improved. It can also be used for screening and marking of ground microseismic event samples for deep learning to prevent false labels. SUMMARY

[0004] The technical problem to be solved by the present application is to provide a ground microseismic event signal enhancement method in view of the defects in the prior art.

[0005] The technical solution adopted by the present application to solve its technical problem is: a ground microseismic event signal enhancement method, comprising the following steps:

[0006] 1) According to the ground microseismic event signal, the dynamic corrected ground microseismic signal containing noise is obtained, and the signal data is denoted as S(x,y,t);

[0007] Wherein, x=1,2,3,…,Mx, is the number of geophones on each geophone line; y=1,2,3…Ny is the number of geophone lines; t=1,2,3,…,Ti is the sampling time point;

[0008] 2) Obtain the time slice data S(x,y,t1) at a given time point t1 in the time window for the ground microseismic signal;

[0009]

[0010] 3) Construct the hankel matrix of each trace for the time slice data;

[0011]

[0012] In the formula, Ri is a Hankel matrix with size h x v, where

[0013]

[0014] For each Hankel matrix R, construct a Hankel block matrix H S , as shown in the following formula:

[0015]

[0016] where the block Hankel matrix H S is a (I x h) x (J x v) order block Hankel matrix, where

[0017] 4) For each time slice of the rearranged Hankel matrix H s , perform a random singular value decomposition;

[0018]

[0019] are diagonal matrices, respectively corresponding to the part with large eigenvalues and the part with small eigenvalues;

[0020] 5) Select part of the singular values as the eigenvalues of the signal reconstruction part, and add a damping operator to suppress the random noise of the residual;

[0021] The damping operator is as follows:

[0022]

[0023] where Γ represents the damping operator operation, I is the unit matrix, γ represents the maximum element of , and d represents the damping operator;

[0024] The matrix reconstructed after truncating the singular values is as follows:

[0025]

[0026] 6) Use the Hankel matrix inverse transformation to transform the matrix reconstructed after truncating the singular values back to the time slice data S(x, y, t1), so as to further suppress the residual noise and obtain the noise-suppressed signal data.

[0027] 7) Repeat steps 2) to 6) until all time slices are processed, and obtain the enhanced signal of the ground microseismic event signal.

[0028] The present application has the beneficial effects that:

[0029] Through the method, signal enhancement can be realized, effective signals can be highlighted, and energy ratio of signals can be improved. BRIEF DESCRIPTION OF DRAWINGS

[0030] The application will be further described below in connection with the drawings and examples, in which:

[0031] Figure 1 is a method flowchart of an embodiment of the application;

[0032] Figure 2 is a microseismic event signal data graph before signal enhancement of an embodiment of the application;

[0033] Figure 3 is a microseismic event signal data graph after signal enhancement of an embodiment of the application. DETAILED DESCRIPTION

[0034] In order to make the objectives, technical solutions and advantages of the application clearer, the application will be further described below in connection with examples. It should be understood that the specific examples described herein are only used to explain the application and do not limit the application.

[0035] As shown in FIG. 1, a ground microseismic event signal enhancement method, the implementation process of the method includes: Figure 1

[0036] Step S1, obtaining a dynamic-corrected ground microseismic signal containing noise, and constructing a hankel matrix for the dynamic-corrected ground microseismic signal. The signal data is S(x, y, t), wherein x = 1, 2, 3, …, Mx, which is the number of geophones on each geophone line. y = 1, 2, 3, …, Ny, which is the number of geophone lines. t = 1, 2, 3, …, Ti, which is the sampling time point. The size of the ground microseismic data is Mx × Ny × Ti.

[0037] Step S2, given the sampling time t1, the data slice of the microseismic signal record is shown as follows:

[0038]

[0039] Step S3, given the time point t1, there is a matrix S(x, y, t1), and each row of the matrix is arranged into a hankel matrix. The data of the slice is shown as follows:

[0040]

[0041] For each hankel matrix R i , a hankel block matrix H S is constructed as shown in the following formula:​

[0042]

[0043] R in formula (2) i is a Hankel matrix of size h x v, where h and v are positive integers,

[0044]

[0045] H in formula (3) is a block Hankel matrix of size (I x h) x (J x v), where I and J are positive integers, S

[0046] Step S4, for each time slice, the rearranged Hankel matrix H s is subjected to a random singular value decomposition;

[0047]

[0048] Generally, a signal is represented as S = D + N, where S represents a signal containing noise, D represents an effective signal of a ground microseismic event, and N represents noise. The matrix S and the matrix N are full rank, rank(S) = rank(N) = J, and the matrix D is not full rank, rank(D) = k < J. are diagonal matrices, respectively corresponding to a part with large eigenvalues and a part with small eigenvalues.

[0049] Step S5, selecting and truncating singular values is a key step for denoising, and the singular values are selected part of the singular values are selected as eigenvalues of a signal reconstruction part, and a damping operator is added to suppress random noise of a residual error.

[0050] The damping operator amplifies or reduces the (N+1)th singular value, then subtracts the first N singular values therefrom, and sets the singular values after the N+1th singular value to 0.

[0051] The damping operator is shown in formula (4).

[0052]

[0053]

[0054] In formula (4), Γ represents a damping operator operation, I is a unit matrix, γ represents the maximum element of the matrix, and d represents a damping operator.

[0055] Step S6, using a Hankel matrix inverse transformation, a matrix ​Transforming back to the time slice data S(x, y, t1), further suppression of residual noise is achieved, and noise-suppressed signal data is obtained.

[0056] Step S7: Steps S2 to S6 are repeated until all time slices are processed, thereby achieving signal enhancement, highlighting effective signals, and improving the energy ratio of the signals.

[0057] In summary, the method for ground microseismic signal enhancement according to the present application in the embodiment utilizes the fact that, after dynamic correction, the ground microseismic event signal is flattened and approximately has a horizontal event. The Hankel block matrix is constructed from the signal, the random singular value decomposition method is used to improve the running speed of the algorithm, the singular values of the matrix are obtained through random singular value decomposition, the appropriate singular values are selected to separate the noise space from the signal space. The residual noise in the separated signal space is suppressed by the damping operator, and finally the reconstructed Hankel block matrix is inversely transformed into the noise-suppressed signal, highlighting the effective signal, achieving signal enhancement, and improving the signal-to-noise ratio. Compared with other signal enhancement methods, the ground microseismic event effective signal can be highlighted, the noise signal can be suppressed, the energy ratio of the ground microseismic event can be enhanced, and the method can be used for traditional long-short time window recognition and deep learning ground microseismic event recognition. Figure 2 Yes, the microseismic event signal data graph before signal enhancement, Figure 3 is the microseismic event signal data graph after signal enhancement.

[0058] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, and are not intended to limit the scope of protection of the present application. Although the present application has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present application can be modified or replaced by equivalents without departing from the essence and scope of the technical solutions of the present application.

[0059] The present application also provides a computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., an SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application store, etc., having a computer program stored thereon, the program being executed by a processor to implement the method for identifying the effectiveness of a ground microseismic pickup event in the method embodiment.

[0060] It should be noted that, according to the needs of implementation, each step / component described in the present application can be split into more steps / components, or two or more steps / components or part of the operations of the steps / components can be combined into a new step / component to achieve the purpose of the present application.

[0061] It is to be understood that the above description is intended to be illustrative and not restrictive. Many other embodiments will be apparent to those of skill in the art upon reviewing the above description. The scope of the application should, therefore, be determined not with reference to the above description, but instead with reference to the appended claims, along with their full scope of equivalents.

Claims

1. A method of ground microseismic event signal enhancement, characterized by, The method comprises the following steps: 1) According to the ground microseismic event signal, the ground microseismic signal after dynamic correction containing noise is obtained, and the signal data is recorded as ; wherein, is the number of detection points on each detection line; is the number of detection lines; is the sampling time point; 2) obtaining time-slice data of the surface microseismic signal at a given time point tl within a time window ; 3) constructing a Hankel matrix of each trace for the time slice data; where R i is a Hankel matrix of size wherein ； for each Hankel matrix R i is constructed as a Hankel block matrix as follows: where the block Hankel matrix is then Hankel block matrix of order n, where ; 4) For each time slice, perform a randomized singular value decomposition on the reordered Hankel block matrix . 5) selecting a part of singular values with large eigenvalues in singular value decomposition as eigenvalues of the signal reconstruction part, and adding a damping operator to suppress random noise of the residual error; 6) using Hankel matrix inversion, reconstruct the post-matrix transform back to time-slice data , obtain noise-suppressed signal data; 7) repeating steps 2) to 6) until all time slices are processed to obtain an enhanced signal of the original ground microseismic event signal.

2. The method of ground microseismic event signal enhancement of claim 1, wherein, In the step 4), the random singular value decomposition is specifically as follows: , are diagonal matrices, respectively corresponding to the large eigenvalue part and the small eigenvalue part.

3. The method of ground microseismic event signal enhancement of claim 1, wherein, In the step 5), the damping operator is added to suppress the random noise of the residual error, which is specifically as follows: The damping operator is as follows: ； wherein denotes the damping operator operation, is the identity matrix, denotes the largest element of denotes the damping operator; Truncated singular value reconstructed post-matrix As follows: 。 4. A computer device comprising a memory and a processor, the memory storing a computer program, characterized in that, The processor executes the computer program to realize the steps of the ground microseismic event signal enhancement method in any one of claims 1 to 3.

5. A computer-readable storage medium having stored thereon a computer program, characterized in that, The computer program is executed by the processor to realize the ground microseismic event signal enhancement method in any one of claims 1 to 3.

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