Optimal parameter calculation method and device for synchronous extrusion transformation and medium

Abstract

The invention provides an optimal parameter calculation method and device for synchronous extrusion transformation and a medium, and belongs to the field of oil and gas geophysical exploration. The method comprises the following steps: inputting seismic data; constructing an analysis time window; and calculating an optimal parameter based on a time-frequency focusing criterion. According to the method, the optimal variance and the optimal time window length are obtained through iterative optimization calculation based on the time-frequency focusing criterion, manual experiments or experience-based giving are not needed, and the signal analysis precision is improved.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas geophysical exploration, and specifically relates to a method, apparatus and medium for calculating the optimal parameters of synchronous compression transformation. Background Technology

[0002] Time-frequency analysis is a signal processing method used to simultaneously study the time and frequency domain characteristics of a signal, providing detailed information about how the signal changes in time and frequency. Common time-frequency analysis methods for seismic signals include: 1) Short-Time Fourier Transform (STFT): STFT divides the signal into a series of short-time windows and then performs a Fourier transform on each window, thus obtaining the frequency components of the signal at different time intervals; 2) Wavelet Transform: Wavelet transform uses wavelet functions as the basic functions and has local properties in both the time and frequency domains, thus better describing the time-frequency characteristics of non-stationary signals; 3) Wigner-Ville Distribution (WVD): WVD directly applies the signal's autocorrelation and cross-correlation functions to the time-frequency domain, providing high-resolution time-frequency information; 4) Cohen's class distribution: Cohen's class distribution is an improvement and extension of WVD, which improves the cross-term problem in the signal by introducing different window functions and smoothing techniques.

[0003] In recent years, the squeeze transform method, a seismic signal analysis method with high time-frequency focusing capabilities, has been increasingly widely used. First, a basic window function, such as the Hanning window, is selected. Then, based on the signal's frequency distribution, the local bandwidth corresponding to each frequency point is calculated; higher frequencies correspond to smaller local bandwidths, while lower frequencies correspond to larger local bandwidths. Finally, a Fourier transform is performed on each adjusted window to obtain time-frequency information, and all results are then combined into a single time-frequency representation. The synchronous squeeze transform offers higher time and frequency resolution and, compared to the STFT, is better suited to signals with large frequency variations. However, compared to the traditional STFT, the synchronous squeeze transform has a higher computational load; therefore, in practical applications, a trade-off between computational complexity and the required time-frequency accuracy is necessary.

[0004] When using synchronous compression transform to analyze seismic signals, two important parameters are the selection of the Gaussian window function and the analysis time window parameter. Specific experiments are needed to determine these parameters during signal analysis. However, seismic data, especially pre-stack seismic data, is enormous, making it impractical to conduct such experiments for every trace. The conventional approach is to select any one seismic trace for experimentation to determine the optimal parameters, but such parameters may not be suitable for other traces. Therefore, it is necessary to study an adaptive method for selecting the optimal parameters of synchronous compression transform. Summary of the Invention

[0005] The purpose of this invention is to solve the problems existing in the prior art and provide a method, device and medium for calculating the optimal parameters of synchronous extrusion transformation, thereby improving the accuracy of signal analysis.

[0006] This invention is achieved through the following technical solution:

[0007] A first aspect of the present invention provides a method for calculating the optimal parameters of a synchronous extrusion transformation, comprising:

[0008] Input earthquake data;

[0009] Construct an analysis window;

[0010] Optimal parameters are calculated based on the time-frequency focusing criterion.

[0011] A further improvement of the present invention is that:

[0012] The specific operations for constructing the analysis window include:

[0013] Let the expression for the Gaussian function be:

[0014]

[0015] Let the length of the analysis window be h, then h = h + 1 - h%2, where % is the modulo operator.

[0016] The discretized time series is t = [-0.5:1 / h:0.5], and the discretized Gaussian window sequence is:

[0017]

[0018] Where, σ 2 The variance is t = n × Δt, where Δt is the discrete sampling interval, Δt = 1 / h.

[0019] A further improvement of the present invention is that:

[0020] The time-frequency focusing criterion is as follows:

[0021]

[0022] Wherein, parameter α is 3, and p(t,f) is the result of synchronous extrusion transformation of the analysis signal.

[0023] A further improvement of the present invention is that:

[0024] The calculation of optimal parameters based on the time-frequency focusing criterion specifically includes the following steps:

[0025] Step 301: Set the analysis signal length of the seismic data, set the initial value of the variance and the variance search range, and set the initial value of the time window length and the time window length search range;

[0026] Step 302: Using the initial variance value as the input value and keeping it fixed, obtain the synchronous squeezing transformation result of the analysis signal within the search range of the analysis time window length, and substitute the synchronous squeezing transformation result of the analysis signal into formula (3) to calculate H. α (p), select H α (p) The analysis window length corresponding to the minimum is the optimal analysis window length;

[0027] Step 303: Using the optimal analysis window length obtained in step 302 as the input value and keeping it fixed, obtain the synchronous squeezing transformation result of the analysis signal within the variance search range, and substitute the synchronous squeezing transformation result of the analysis signal into formula (3) to calculate H. α (p), select H α The variance corresponding to the minimum of (p) is the optimal variance;

[0028] Step 304: Using the optimal variance obtained in step 322 as the input value and keeping it fixed, repeat steps 302 and 303 until the set number of iterations is reached.

[0029] A further improvement of the present invention is that:

[0030] The initial value of the variance is set to 0.3, and the variance search range is set to (0.1, 1).

[0031] A further improvement of the present invention is that:

[0032] The initial value of the analysis window length is set to 1 / 5 of the analysis signal length of the seismic data;

[0033] The search range of the analysis window is set to (1, 2N), where N is the number of sampling points of the seismic data.

[0034] A second aspect of the present invention provides an optimal parameter calculation device for synchronous extrusion transformation, comprising:

[0035] Input unit, used for inputting seismic data;

[0036] The time window building unit is used to build analysis time windows;

[0037] The optimal parameter calculation unit is used to calculate the optimal parameters based on the time-frequency focusing criterion.

[0038] A further improvement of the present invention is that:

[0039] The time-frequency focusing criterion is as follows:

[0040]

[0041] Wherein, parameter α is 3, and p(t,f) is the result of synchronous extrusion transformation of the analysis signal.

[0042] A further improvement of the present invention is that:

[0043] The optimal parameter calculation unit performs the following operations:

[0044] Step 301: Set the analysis signal length of the seismic data, set the initial value of the variance and the variance search range, and set the initial value of the time window length and the time window length search range;

[0045] Step 302: Using the initial variance value as the input value and keeping it fixed, obtain the synchronous squeezing transformation result of the analysis signal within the search range of the analysis time window length, and substitute the synchronous squeezing transformation result of the analysis signal into formula (3) to calculate H. α (p), select H α (p) The analysis window length corresponding to the minimum is the optimal analysis window length;

[0046] Step 303: Using the optimal analysis window length obtained in step 302 as the input value and keeping it fixed, obtain the synchronous squeezing transformation result of the analysis signal within the variance search range, and substitute the synchronous squeezing transformation result of the analysis signal into formula (3) to calculate H. α (p), select H α The variance corresponding to the minimum of (p) is the optimal variance;

[0047] Step 304: Using the optimal variance obtained in step 322 as the input value, repeat steps 302 and 303 until the set number of iterations is reached.

[0048] A third aspect of the present invention provides a computer-readable storage medium storing at least one computer-executable program, which, when executed by the computer, causes the computer to perform the steps in the method for calculating the optimal parameters of the synchronous extrusion transformation.

[0049] Compared with the prior art, the beneficial effects of the present invention are:

[0050] Since the optimal time-frequency focusing corresponds to the two optimal parameters, namely variance and time window length, this invention obtains the optimal variance and time window length through iterative optimization calculation based on the time-frequency focusing criterion, without the need for manual experiments or relying on experience, thus improving the accuracy of signal analysis. Attached Figure Description

[0051] Figure 1 This is a flowchart of an optimal parameter calculation method for synchronous extrusion transformation in an embodiment of the present invention;

[0052] Figure 2 It is a Gaussian function with a variance of 0.3;

[0053] Figure 3 It is a Gaussian function with a variance of 0.1;

[0054] Figure 4 These are the time-frequency analysis results corresponding to the optimal parameters calculated using the method of this invention;

[0055] Figure 5 It is the time-frequency analysis result corresponding to the parameters given by existing methods. Detailed Implementation

[0056] The present invention will now be described in further detail with reference to the accompanying drawings:

[0057] When using synchronous compression transform to analyze seismic signals, there are two important parameters: the selection of the Gaussian window function and the analysis time window parameter. These two parameters need to be determined by specific experiments when analyzing the signal. The conventional approach is to select any one seismic trace to conduct experiments and obtain the optimal parameters. However, such parameters may not be suitable for other seismic traces. Therefore, it is necessary to develop an adaptive synchronous compression transform optimal parameter selection method.

[0058]

Example 1

[0059] This invention provides a method for calculating the optimal parameters of synchronous extrusion transformation, such as... Figure 1 As shown, it specifically includes:

[0060] Step 100: Input earthquake data;

[0061] Step 200: Construct the analysis window;

[0062] Step 300: Calculate the optimal parameters based on the time-frequency focusing criterion.

[0063] Since the optimal time-frequency focusing corresponds to the two optimal parameters, namely variance and time window length, this invention obtains the optimal variance and time window length through iterative optimization calculation based on the time-frequency focusing criterion, without the need for manual experiments or relying on experience, thus improving the accuracy of signal analysis.

[0064]

Example 2

[0065] Step 200 involves constructing the analysis window, specifically including the following operations:

[0066] Let the expression for the Gaussian function be:

[0067]

[0068] Let the length of the analysis window be h, then h = h + 1 - h%2, where % is the modulo operator.

[0069] The discretized time series is t = [-0.5:1 / h:0.5]; the discretized Gaussian window sequence is:

[0070]

[0071] Where, σ 2 Let t be the variance, t = n × Δt, where Δt is the discrete sampling interval, Δt = 1 / h.

[0072] At this point, once the length h of the analysis window is determined, the sequence values ​​of the Gaussian function are also determined. From formula (1) or (2), it can be seen that the other parameter of the Gaussian function is the variance parameter, such as... Figure 2 It is a Gaussian function with a variance of 0.3; Figure 3 It is a Gaussian function with a variance of 0.1.

[0073]

Example 3

[0074] In step 300, the optimal parameters are calculated based on the time-frequency focusing criterion, where:

[0075] This invention introduces a time-frequency focusing criterion:

[0076]

[0077] Wherein, parameter α is 3, and p(t,f) is the result of synchronous squeezing transformation of the analysis signal. In this invention, the synchronous squeezing transformation adopts the existing method, which will not be described in detail here.

[0078] The smaller the value of p(t,f), the better the time-frequency focusing, which transforms the problem of adaptive parameter selection into an optimization problem.

[0079] It should be understood that there are two parameters (variance and analysis window length) that can be selected in the extrusion transformation. By choosing any pair of parameters, a synchronous extrusion transformation result p(t,f) can be obtained. Theoretically, there are infinitely many p(t,f). Substituting p(t,f) into formula (3), H is calculated. α (p), where the calculated H α (p) The smaller the value, the better the time-frequency focusing performance. At this point, the two parameters (variance and analysis window length) are considered to be optimal.

[0080] The specific operations include:

[0081] Step 301: Set the analysis signal length of the seismic data, set the initial value of the variance and the variance search range, and set the initial value of the time window length and the time window length search range;

[0082] In this embodiment, preferably, the initial value of the variance is set to 0.3, and the variance search range is set to (0.1, 1);

[0083] In this embodiment, preferably, the initial value of the analysis window length is set to 1 / 5 of the analysis signal length of the seismic data, and the search range of the analysis window is set to (1, 2N). The analysis signal length of the seismic data is a discrete integer variable, and its range is set to (1, 2N), where N is the number of sampling points of the seismic data, and the interval is an integer of 1.

[0084] Step 302: Using the initial variance value as the input value and keeping it fixed, obtain the synchronous squeezing transformation result of the analysis signal within the search range of the analysis time window length, and substitute the synchronous squeezing transformation result of the analysis signal into formula (3) to calculate H. α (p), select H α (p) The analysis window length corresponding to the minimum is the optimal analysis window length;

[0085] Step 303: Using the optimal analysis window length obtained in step 302 as the input value and keeping it fixed, obtain the synchronous squeezing transformation result of the analysis signal within the variance search range, and substitute the synchronous squeezing transformation result of the analysis signal into formula (3) to calculate H. α (p), select H α The variance corresponding to the minimum of (p) is the optimal variance;

[0086] Step 304: Using the optimal variance obtained in step 322 as the input value, repeat steps 302 and 303 until the set number of iterations is reached.

[0087] Figure 4 These are the time-frequency analysis results corresponding to the optimal parameters calculated using the method of this invention; Figure 5This is the time-frequency analysis result corresponding to the parameters given by existing methods. Two parameter values ​​were obtained through manual experiments: variance of 0.2 and analysis signal length of 25. Figure 4 and Figure 5 The comparison shows that the time-frequency analysis results corresponding to the optimal parameters calculated by the method of this invention have better time-frequency focusing and higher signal analysis accuracy.

[0088]

Example 4

[0089] This invention provides an optimal parameter calculation device for synchronous extrusion transformation, comprising:

[0090] Input unit, used for inputting seismic data;

[0091] The time window construction unit is used to construct analysis time windows, and specifically performs the following operations:

[0092] Let the expression for the Gaussian function be:

[0093]

[0094] Let the length of the analysis window be h, then h = h + 1 - h%2, where % is the modulo operator.

[0095] The discretized time series is t = [-0.5:1 / h:0.5]; the discretized Gaussian window sequence is:

[0096]

[0097] Where, σ 2 Let t be the variance, t = n × Δt, where Δt is the discrete sampling interval, Δt = 1 / h.

[0098] The optimal parameter calculation unit is used to calculate the optimal parameters based on the time-frequency focusing criterion.

[0099] The time-frequency focusing criterion is as follows:

[0100]

[0101] Wherein, parameter α is 3, and p(t,f) is the result of synchronous extrusion transformation of the analysis signal.

[0102] The optimal parameter calculation unit performs the following operations:

[0103] Step 301: Set the analysis signal length of the seismic data, set the initial value of the variance and the variance search range, and set the initial value of the time window length and the time window length search range;

[0104] Step 302: Using the initial variance value as the input value and keeping it fixed, obtain the synchronous squeezing transformation result of the analysis signal within the search range of the analysis time window length, and substitute the synchronous squeezing transformation result of the analysis signal into formula (3) to calculate H. α (p), select H α (p) The analysis window length corresponding to the minimum is the optimal analysis window length;

[0105] Step 303: Using the optimal analysis window length obtained in step 302 as the input value and keeping it fixed, obtain the synchronous squeezing transformation result of the analysis signal within the variance search range, and substitute the synchronous squeezing transformation result of the analysis signal into formula (3) to calculate H. α (p), select H α The variance corresponding to the minimum of (p) is the optimal variance;

[0106] Step 304: Using the optimal variance obtained in step 322 as the input value, repeat steps 302 and 303 until the set number of iterations is reached.

[0107]

Example 5

[0108] This invention provides a computer-readable storage medium storing at least one computer-executable program, which, when executed by the computer, causes the computer to perform steps in the calculation of optimal parameters for the synchronous extrusion transformation.

[0109] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods. Any references to memory, storage, databases, or other media used in the embodiments provided in this application can include non-volatile and / or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically programmable ROM (EPROM), electrically erasable programmable ROM (EEPROM), or flash memory. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in various forms, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), dual data rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous link DRAM (SLDRAM), Rambus direct RAM (RDRAM), direct memory bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM), etc.

[0110] The above technical solution is only one embodiment of the present invention. For those skilled in the art, based on the principles disclosed in the present invention, it is easy to make various types of improvements or modifications, and not limited to the technical solutions described in the specific embodiments of the present invention. Therefore, the foregoing description is only a preferred option and is not restrictive.

Claims

1. A method for calculating the optimal parameters of synchronous extrusion transformation, characterized in that, include: Input earthquake data; Construct an analysis window; Optimal parameters are calculated based on the time-frequency focusing criterion.

2. The method according to claim 1, characterized in that, The specific operations for constructing the analysis window include: Let the expression for the Gaussian function be: Let the length of the analysis window be h, then h = h + 1 - h%2, where % is the modulo operator. The discretized time series is t = [-0.5:1 / h:0.5], and the discretized Gaussian window sequence is: Where, σ 2 The variance is t = n × Δt, where Δt is the discrete sampling interval, Δt = 1 / h.

3. The method according to claim 1, characterized in that, The time-frequency focusing criterion is as follows: Wherein, parameter α is 3, and p(t,f) is the result of synchronous extrusion transformation of the analysis signal.

4. The method according to claim 4, characterized in that, The calculation of optimal parameters based on the time-frequency focusing criterion specifically includes the following steps: Step 301: Set the analysis signal length of the seismic data, set the initial value of the variance and the variance search range, and set the initial value of the time window length and the time window length search range; Step 302: Using the initial variance value as the input value and keeping it fixed, obtain the synchronous squeezing transformation result of the analysis signal within the search range of the analysis time window length, and substitute the synchronous squeezing transformation result of the analysis signal into formula (3) to calculate H. α (p), select H α (p) The analysis window length corresponding to the minimum is the optimal analysis window length; Step 303: Using the optimal analysis window length obtained in step 302 as the input value and keeping it fixed, obtain the synchronous squeezing transformation result of the analysis signal within the variance search range, and substitute the synchronous squeezing transformation result of the analysis signal into formula (3) to calculate H. α (p), select H α The variance corresponding to the minimum of (p) is the optimal variance; Step 304: Using the optimal variance obtained in step 322 as the input value and keeping it fixed, repeat steps 302 and 303 until the set number of iterations is reached.

5. The method according to claim 4, characterized in that, The initial value of the variance is set to 0.3, and the variance search range is set to (0.1, 1).

6. The method according to claim 4, characterized in that, The initial value of the analysis window length is set to 1 / 5 of the analysis signal length of the seismic data; The search range of the analysis window is set to (1, 2N), where N is the number of sampling points of the seismic data.

7. An optimal parameter calculation device for synchronous extrusion transformation, characterized in that, include: Input unit, used for inputting seismic data; The time window building unit is used to build analysis time windows; The optimal parameter calculation unit is used to calculate the optimal parameters based on the time-frequency focusing criterion.

8. The apparatus according to claim 7, characterized in that, The time-frequency focusing criterion is as follows: Wherein, parameter α is 3, and p(t,f) is the result of synchronous extrusion transformation of the analysis signal.

9. The apparatus according to claim 8, characterized in that, The optimal parameter calculation unit specifically performs the following operations: Step 301: Set the analysis signal length of the seismic data, set the initial value of the variance and the variance search range, and set the initial value of the time window length and the time window length search range; Step 302: Using the initial variance value as the input value and keeping it fixed, obtain the synchronous squeezing transformation result of the analysis signal within the search range of the analysis time window length, and substitute the synchronous squeezing transformation result of the analysis signal into formula (3) to calculate H. α (p), select H α (p) The analysis window length corresponding to the minimum is the optimal analysis window length; Step 303: Using the optimal analysis window length obtained in step 302 as the input value and keeping it fixed, obtain the synchronous squeezing transformation result of the analysis signal within the variance search range, and substitute the synchronous squeezing transformation result of the analysis signal into formula (3) to calculate H. α (p), select H α The variance corresponding to the minimum of (p) is the optimal variance; Step 304: Using the optimal variance obtained in step 322 as the input value, repeat steps 302 and 303 until the set number of iterations is reached.

10. A computer-readable storage medium storing at least one computer-executable program, which, when executed by the computer, causes the computer to perform the steps of the optimal parameter calculation method for synchronous extrusion transformation as described in any one of claims 1-6.

Images