Seismic signal time-frequency spectrum generation method and device based on generalized tuning precise S transformation

Abstract

The embodiment of the invention provides a seismic signal time-frequency spectrum generation method and device based on generalized tuning precise S transformation. The method comprises the steps of obtaining an original seismic signal, generating an instantaneous frequency of the original seismic signal according to the original seismic signal and a Hilbert transform signal of the original seismic signal, carrying out differential on the instantaneous frequency of the original seismic signal to obtain a tuning rate of the original seismic signal, and carrying out time window control on the original seismic signal according to the tuning rate and preset N time window control parameters, the method comprises the steps of generating N S transformation time windows, generating N first time-frequency spectrums of an original seismic signal according to a tuning rate and the N S transformation time windows, combining the N first time-frequency spectrums into a second time-frequency spectrum of the original seismic signal, and simultaneously achieving a high-resolution time-frequency spectrum in a time domain and a frequency domain, thereby improving the information extraction capability of a strong unsteady-state seismic signal.

Description

Technical Field

[0001] The present application relates to the field of signal processing technology, and in particular to a method and device for generating a time-frequency spectrum of a seismic signal using a generalized tuned precise S transform. Background Art

[0002] Seismic signal processing and analysis is an important research topic in the fields of geophysics and oil exploration. Based on the time-frequency spectrum generated by seismic signals, the propagation of seismic waves can be monitored in real time, and earthquake warning information can be issued in a timely manner, providing strong support for reducing the losses caused by earthquake disasters.

[0003] In the prior art, the time-frequency spectrum of the seismic signal is obtained by using the precise S-transform method. The precise S-transform method constructs a time window function that is symmetrical about the instantaneous frequency of the seismic data, and utilizes the convolution between the time window function and the seismic signal to be analyzed to obtain a high-resolution time-frequency spectrum, thereby enhancing the extraction of low-frequency information in the seismic signal.

[0004] However, since the time window function of the precise S transform method is specific, the length of the time window function determines the trade-off between time and frequency resolution. The short window function provides high time resolution but low frequency resolution; the long window function provides high frequency resolution but low time resolution. Therefore, it is impossible to simultaneously obtain high-resolution time-frequency spectra in the time domain and frequency domain, and thus the ability to extract information from strong non-steady-state seismic signals is poor. Summary of the invention

[0005] The embodiments of the present application provide a method and device for generating a time-frequency spectrum of a seismic signal using a generalized tuned precise S transform, which is used to obtain a high-resolution time-frequency spectrum in the time domain and the frequency domain, thereby improving the ability to extract information from strong non-stationary seismic signals.

[0006] In a first aspect, an embodiment of the present application provides a method for generating a time-frequency spectrum of a seismic signal using a generalized tuned precise S transform, comprising:

[0007] Obtaining raw seismic signals;

[0008] generating an instantaneous frequency of the original seismic signal according to the original seismic signal and a Hilbert transform signal of the original seismic signal;

[0009] Differentiating the instantaneous frequency of the original seismic signal to obtain a tuning rate of the original seismic signal;

[0010] Generate N S transform time windows according to the tuning rate and preset N time window control parameters, wherein the N time window control parameters correspond to the N S transform time windows one by one, and N is a positive integer greater than or equal to 1;

[0011] Generate N first time-frequency spectra of the original seismic signal according to the tuning rate and the N S-transform time windows, wherein the N S-transform time windows correspond to the N first time-frequency spectra one by one;

[0012] The N first time-frequency spectra are combined into a second time-frequency spectra of the original seismic signal.

[0013] In a possible implementation, merging the N first time-frequency spectra into a second time-frequency spectra of the original seismic signal includes:

[0014] An average value of the N first time-frequency spectra is calculated as a second time-frequency spectra of the original seismic signal, wherein the average value includes at least one of the following: an arithmetic mean, a geometric mean, and a weighted mean.

[0015] In a possible implementation manner, generating N first time-frequency spectra of the original seismic signal according to the tuning rate and the N S-transform time windows includes:

[0016] Converting the original seismic signal into an original seismic matrix;

[0017] Converting each of the S-transform time windows into a time window coefficient matrix;

[0018] The original earthquake matrix and each of the time window coefficient matrices are matrix-multiplied to obtain the first time-frequency spectrum.

[0019] In a possible implementation manner, when there are one or more original seismic signals, after acquiring the original seismic signals, the method further includes:

[0020] Determine a corresponding computing unit for the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum of each of the original seismic signals, wherein the computing unit includes at least one of the following: a CPU core, a thread, a process, and a GPU, and different original seismic signals correspond to the same or different computing units;

[0021] The instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum corresponding to the original seismic signal are sent to the corresponding computing entity, and the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum correspond to the same or different computing units.

[0022] In a possible implementation, determining a corresponding calculation unit for the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum of each of the original seismic signals includes:

[0023] Obtaining historical calculation speeds corresponding to the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum respectively;

[0024] Get the historical computing performance and current status of multiple computing units;

[0025] According to the historical calculation speed, the historical calculation performance and the current state, corresponding calculation entities are allocated to the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum and the second time-frequency spectrum.

[0026] In a possible implementation manner, generating the instantaneous frequency of the original seismic signal according to the original seismic signal and the Hilbert transform signal of the original seismic signal includes:

[0027] The instantaneous frequency of the original seismic signal is calculated by the following formula:

[0028]

[0029] Among them, the f inst (τ) is the instantaneous frequency of the original seismic signal, x(t) is the original seismic signal, x′(t) is the differential of the original seismic signal, y(t) is the Hilbert transform signal of the original seismic signal, and y′(t) is the differential of the Hilbert transform signal.

[0030] In a possible implementation manner, generating N S transform time windows according to the tuning rate and preset N time window control parameters includes:

[0031] One of the S-transform time windows is calculated using the following formula:

[0032]

[0033] Among them, w(t,f;τ) is one of the S transform time windows, t is the time to be analyzed, f is the frequency to be analyzed, τ is the center time of one of the S transform time windows, and f inst (τ) is the instantaneous frequency of the original seismic signal at time τ, Δf(τ) is the difference between the frequency to be analyzed and the instantaneous frequency of the original seismic signal at time τ, k is the time window control parameter of one of the S transform time windows, and c(t) is the tuning rate of the original seismic signal at time t.

[0034] In a possible implementation manner, generating N first time-frequency spectra of the original seismic signal according to the tuning rate and the N S-transform time windows includes:

[0035] One of the first time-frequency spectra is calculated by the following formula:

[0036]

[0037] Among them, S(τ,f,c(t)) is one of the first time-frequency spectra, and w(t-τ,f; τ) is one of the S-transform time windows.

[0038] In a second aspect, an embodiment of the present application provides a seismic signal time-frequency spectrum generation device using a generalized tuned precise S transform, comprising:

[0039] An acquisition module, used for acquiring original seismic signals;

[0040] A processing module, configured to generate an instantaneous frequency of the original seismic signal according to the original seismic signal and a Hilbert transform signal of the original seismic signal;

[0041] The processing module is further used to differentiate the instantaneous frequency of the original seismic signal to obtain the tuning rate of the original seismic signal;

[0042] The processing module is further used to generate N S-transform time windows according to the tuning rate and preset N time window control parameters, wherein the N time window control parameters correspond to the N S-transform time windows one by one, and N is a positive integer greater than or equal to 1;

[0043] The processing module is further used to generate N first time-frequency spectra of the original seismic signal according to the tuning rate and the N S-transform time windows, and the N S-transform time windows correspond to the N first time-frequency spectra in one-to-one correspondence;

[0044] The processing module is further used to merge the N first time-frequency spectra into a second time-frequency spectra of the original seismic signal.

[0045] In the seismic signal time-frequency spectrum generation device of generalized tuned precise S transform provided in the present application:

[0046] The processing module is used to calculate the average value of the N first time-frequency spectra as the second time-frequency spectra of the original seismic signal, wherein the average value includes at least one of the following: arithmetic mean, geometric mean, and weighted mean.

[0047] In the seismic signal time-frequency spectrum generation device of generalized tuned precise S transform provided in the present application:

[0048] A processing module, used for converting the original seismic signal into an original seismic matrix;

[0049] The processing module is further used to convert each of the S-transform time windows into a time window coefficient matrix;

[0050] The processing module is further used to perform matrix multiplication on the original earthquake matrix and each of the time window coefficient matrices to obtain the first time-frequency spectrum.

[0051] In the seismic signal time-frequency spectrum generation device of generalized tuned precise S transform provided in the present application:

[0052] For each of the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum of the original seismic signal, a processing module is used to determine a corresponding computing unit, wherein the computing unit includes at least one of the following: a CPU core, a thread, a process, and a GPU, and different original seismic signals correspond to the same or different computing units;

[0053] A processing module is used to send the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum corresponding to the original seismic signal to the corresponding computing entity, and the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum correspond to the same or different computing units.

[0054] In the seismic signal time-frequency spectrum generation device of generalized tuned precise S transform provided in the present application:

[0055] An acquisition module, used to acquire historical calculation speeds corresponding to the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum respectively;

[0056] The acquisition module is also used to obtain the historical computing performance and current status of multiple computing units;

[0057] A processing module is used to allocate corresponding calculation entities to the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum according to the historical calculation speed, the historical calculation performance, and the current state.

[0058] In the seismic signal time-frequency spectrum generation device of generalized tuned precise S transform provided in the present application:

[0059] The processing module is used to calculate the instantaneous frequency of the original seismic signal by the following formula:

[0060]

[0061] Among them, the f inst (τ) is the instantaneous frequency of the original seismic signal, x(t) is the original seismic signal, x′(t) is the differential of the original seismic signal, y(t) is the Hilbert transform signal of the original seismic signal, and y′(t) is the differential of the Hilbert transform signal.

[0062] In the seismic signal time-frequency spectrum generation device of generalized tuned precise S transform provided in the present application:

[0063] The processing module is used to calculate one of the S-transform time windows using the following formula:

[0064]

[0065] Among them, w(t,f;τ) is one of the S transform time windows, t is the time to be analyzed, f is the frequency to be analyzed, τ is the center time of one of the S transform time windows, and f inst (τ) is the instantaneous frequency of the original seismic signal at time τ, Δf(τ) is the difference between the frequency to be analyzed and the instantaneous frequency of the original seismic signal at time τ, k is the time window control parameter of one of the S transform time windows, and c(t) is the tuning rate of the original seismic signal at time t.

[0066] In the seismic signal time-frequency spectrum generation device of generalized tuned precise S transform provided in the present application:

[0067] The processing module is used to calculate one of the first time-frequency spectra using the following formula:

[0068]

[0069] Among them, S(τ,f,c(t)) is one of the first time-frequency spectra, and w(t-τ,f; τ) is one of the S-transform time windows.

[0070] In a third aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor;

[0071] The memory stores computer-executable instructions;

[0072] The processor executes the computer-executable instructions stored in the memory, so that the processor executes the above first aspect and / or various possible implementations of the first aspect.

[0073] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the first aspect above and / or various possible implementations of the first aspect.

[0074] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, which, when executed by a processor, implements the above first aspect and / or various possible implementation methods of the first aspect.

[0075] The embodiment of the present application provides a method and device for generating a time-frequency spectrum of a seismic signal using a generalized tuned precise S transform. By acquiring an original seismic signal, the instantaneous frequency of the original seismic signal is generated according to the original seismic signal and the Hilbert transform signal of the original seismic signal, and then the instantaneous frequency of the original seismic signal is differentiated to obtain a tuning rate of the original seismic signal. According to the tuning rate and N preset time window control parameters, N S transform time windows are generated. According to the tuning rate and the N S transform time windows, N first time-frequency spectra of the original seismic signal are generated. Finally, the N first time-frequency spectra are merged into a second time-frequency spectrum of the original seismic signal. Compared with the prior art, when the precise S transform method acquires the time-frequency spectrum of the seismic signal, since the time window function used by the precise S transform method is specific, it is impossible to simultaneously obtain high-resolution time-frequency spectra in the time domain and the frequency domain, thereby solving the problem of poor information extraction capability for strong non-steady-state seismic signals. The present application generates multiple transformation time windows by setting multiple time window control parameters, performs time-frequency spectrum calculation on the same original seismic signal through multiple transformation time windows, and finally merges the multiple time-frequency spectra obtained. The final time-frequency spectrum generated is a high-resolution time-frequency spectrum in both the time domain and the frequency domain, thereby improving the information extraction capability of strong non-steady-state seismic signals. BRIEF DESCRIPTION OF THE DRAWINGS

[0076] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0077] Figure 1 A schematic diagram of a scenario of a method for generating a time-frequency spectrum of a seismic signal based on a generalized tuned precise S transform provided in this application;

[0078] Figure 2 Schematic diagram of the process of generating time-frequency spectrum of seismic signals based on generalized tuned precise S transform provided in this application Figure 1 ;

[0079] Figure 3 It is a schematic diagram of the rotation of the video window in the time-frequency plane;

[0080] Figure 4 It is a schematic diagram of the generalized tuned precise S transform;

[0081] Figure 5 Schematic diagram of the process of generating time-frequency spectrum of seismic signals based on generalized tuned precise S transform provided in this application Figure 2 ;

[0082] Figure 6 Schematic diagram of the process of generating time-frequency spectrum of seismic signals based on generalized tuned precise S transform provided in this application Figure 3 ;

[0083] Figure 7Schematic diagram of the process of generating time-frequency spectrum of seismic signals based on generalized tuned precise S transform provided in this application Figure 4 ;

[0084] Figure 8 A time-frequency spectrum generating device for seismic signals with tuned precise S-transform provided in this application;

[0085] Fig. 9 A schematic diagram of the structure of the electronic device provided in this application.

[0086] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0087] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0088] In the prior art, the time window function of the precise S transform method is specific. Since the short window function provides high time resolution but low frequency resolution, and the long window function provides high frequency resolution but low time resolution, the time-frequency spectrum obtained by the special time window function cannot achieve high resolution in both the time domain and the frequency domain, and thus the ability to extract information from strong non-steady-state seismic signals is poor.

[0089] Based on this, the inventive concept of this application is how to provide a method for generating a time-frequency spectrum of a seismic signal based on a generalized tuned precise S transform, and how to achieve high resolution in both the time domain and the frequency domain of the time-frequency spectrum. Based on this, by increasing the time window control parameter to generate multiple transformation time windows, calculating the same seismic signal through multiple transformation time windows, and merging the time-frequency spectrum obtained from each transformation time window to obtain the final time-frequency spectrum, it is possible to achieve a time-frequency spectrum that can achieve high resolution in both the time domain and the frequency domain, thereby enhancing the ability to extract information from strong non-steady-state seismic signals.

[0090] Figure 1 A schematic diagram of a scenario of a method for generating a time-frequency spectrum of a seismic signal based on a generalized tuned precise S transform provided in this application. Figure 1As shown in Figure 1, the time-frequency spectrum generation process of multiple original seismic signals is assigned to different CPU cores and different GPU cores for parallel operation, which improves the computing efficiency. Figure 1 As shown, after receiving multiple original seismic signals, for example, P original seismic signals are received, they are divided into Q seismic record groups, and the Q seismic record groups correspond to Q CPU cores respectively, and each seismic record group includes P / Q original seismic signals. Then, for each CPU, the CPU sends the P / Q original seismic signals included in the seismic record group corresponding to it to the GPU corresponding to the CPU for tuning precision S transformation, and the CPU calculates the P / Q seismic records included in this seismic record group to obtain the tuning precision S transformation results of the P / Q seismic records, and then the corresponding CPU calculates the local time-frequency spectrum according to the tuning precision S transformation results, and finally obtains a multi-channel time-frequency spectrum, that is, the time-frequency spectrum corresponding to each original seismic signal, by allocating multiple original seismic signals to different CPU cores and different GPU operations, and parallel operations are performed to improve the computing efficiency.

[0091] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes may not be repeated in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0092] Figure 2 Schematic diagram of the process of generating time-frequency spectrum of seismic signals based on generalized tuned precise S transform provided in this application Figure 1 ,like Figure 2 As shown, the method includes:

[0093] S201: Acquire original seismic signals.

[0094] In an embodiment of the present application, the original seismic signal is acquired by a seismic monitoring device, such as a seismograph.

[0095] In practical applications, the original seismic signal is a real-valued function that represents the change of seismic waves over time. The original seismic signal contains various characteristics of seismic waves, such as amplitude, frequency and phase, but these characteristics are often mixed together in the original signal and are difficult to separate directly.

[0096] In order to analyze the seismic signal more accurately, it is converted into a form that is easier to process, namely the complex seismic trace, also known as the analytical signal. The complex seismic trace is a complex function, which consists of the real part of the original seismic data signal and the imaginary part obtained by Hilbert transform. The complex seismic trace representation allows us to more conveniently access and process the phase information of the signal. The complex seismic trace of the original seismic signal in this application is:

[0097]

[0098] in, represents the complex seismic trace of the original seismic signal, x(t) represents the original seismic signal, y(t) represents the Hilbert transform signal of the original seismic signal, and i here represents an imaginary number.

[0099] S202: Generate the instantaneous frequency of the original seismic signal according to the original seismic signal and the Hilbert transform signal of the original seismic signal.

[0100] In the embodiment of the present application, in order to obtain the instantaneous frequency of the original seismic signal, it is first necessary to calculate the Hilbert transform signal of the original seismic signal based on the original seismic signal. The Hilbert transform is a linear operator that generates a function y(t) with the same domain as the function x(t), that is, the original seismic signal and the Hilbert transform signal of the original seismic signal have the same domain. The calculation formula of the Hilbert transform signal of the original seismic signal is:

[0101] y(t)=H[x(t)]

[0102] Wherein, x(t) represents the original seismic signal, H represents the Hilbert transform, and y(t) represents the Hilbert transform signal of the original seismic signal.

[0103] Then, the specific implementation method of generating the instantaneous frequency of the original seismic signal according to the original seismic signal and the Hilbert transform signal of the original seismic signal is:

[0104]

[0105] Among them, f inst (τ) represents the instantaneous frequency of the original seismic signal, x(t) represents the original seismic signal, x′(t) represents the differential of the original seismic signal, y(t) represents the Hilbert transform signal of the original seismic signal, and y′(t) represents the differential of the Hilbert transform signal.

[0106] S203: Differentiate the instantaneous frequency of the original seismic signal to obtain the tuning rate of the original seismic signal.

[0107] In the embodiment of the present application, the instantaneous frequency f of the original seismic signal inst (τ) is differentiated to obtain the tuning rate of the original seismic signal, and its specific calculation formula is:

[0108]

[0109] Where c(t) is the tuning rate of the original seismic signal, f inst (t) is the instantaneous frequency of the original seismic signal, and t represents time.

[0110] S204: Generate N S transform time windows according to the tuning rate and preset N time window control parameters, the N time window control parameters correspond to the N S transform time windows one by one, and N is a positive integer greater than or equal to 1.

[0111] In an embodiment of the present application, the time window control parameter is used to adjust the shape and size of the S transform time window. First, N time window control parameters are preset according to the N S transform time windows, and then N S transform time windows are generated according to the obtained tuning rate and the preset N time window control parameters. Among them, each S transform time window corresponds to a different time window control parameter, and the N S transform time windows correspond one to one with the N time window control parameters. Each time window control parameter corresponds to a unique S transform time window, so by adjusting the time window control parameter, S transform time windows of different shapes and sizes can be obtained to adapt to the different characteristics of the original seismic signal. The one-to-one correspondence between the time window control parameter and the S transform time window enables the S transform to process non-steady-state seismic signals more flexibly.

[0112] Specifically, according to the tuning rate and the preset time window control parameters, the specific implementation method of generating the S transform time window is:

[0113]

[0114] Among them, w(t,f;τ) represents the S transform time window, t represents the time to be analyzed, f represents the frequency to be analyzed, τ represents the center time of the S transform time window, and f inst (τ) represents the instantaneous frequency of the original seismic signal, Δf(τ) represents the difference between the frequency to be analyzed and the instantaneous frequency of the original seismic signal at time τ, k represents the time window control parameter of the S transform time window and is positively correlated with the time window length, and c(t) represents the tuning rate of the original seismic signal at time t.

[0115] The detailed explanation is: first, N different time window control parameters k are preset. For each preset time window control parameter k, an S-transform time window is calculated by combining the tuning rate of the original seismic signal at time t and the instantaneous frequency of the original seismic signal. This is repeated N times, using different time window control parameters each time, to obtain N different S-transform time windows.

[0116] Optionally, N is a positive integer greater than or equal to 1. When the original seismic signal changes relatively smoothly, a smaller N value can be selected. For example, if N is 2, the two S transform time windows correspond to low-frequency seismic signals, medium-frequency seismic signals, and high-frequency seismic signals, respectively. When the original seismic signal changes dramatically, N needs to be set to a larger value to capture more detailed information. For example, if N is 10, each S transform time window corresponds to a specific time period and frequency range of the original seismic signal.

[0117] like Figure 3The figure shows the rotation of the video window in the time-frequency plane. The video window refers to the time-frequency window used to capture and analyze the signal. It refers to the window function used to represent the local characteristics of the signal in the time-frequency plane, that is, the time window function in the S transform. Since the tuning precision S transform introduces the tuning rate, the tuning rate c(t) appears in the form of a phase correction factor. In the figure, the tuning rate c(t) adjusts the phase of the time window function, thereby changing the direction of the time window function in the time-frequency plane. As the tuning rate c(t) changes, the inclination angle of the S transform time window in the time-frequency plane will also change. Compared with the traditional S transform, the transform time window is static and cannot reflect the dynamic characteristics of the original seismic signal. The S transform time window in the generalized tuned precise S transform can dynamically integrate the original seismic signal into the S transform time window by introducing the tuning rate, and can adjust the direction and shape as the original seismic signal changes. Therefore, it can more accurately capture the local characteristics of the original seismic signal and improve the accuracy of time-frequency analysis.

[0118] S205: Generate N first time-frequency spectra of the original seismic signal according to the tuning rate and the N S-transform time windows, where the N S-transform time windows correspond to the N first time-frequency spectra one by one.

[0119] In the embodiment of the present application, N first time-frequency spectra of the original seismic signal are generated according to the tuning rate and the obtained N S-transform time windows, wherein the N S-transform time windows correspond to the N first time-frequency spectra one by one.

[0120] Specifically, the calculation formula of the first time-frequency spectrum is:

[0121]

[0122] Among them, S(τ,f,c(t)) represents one of the first time-frequency spectra, w(t-τ,f; τ) is one of the S-transform time windows, x(t) represents the original seismic signal, f represents any frequency to be analyzed in the frequency axis, and τ represents the central time point of the time window function.

[0123] S206: Merge the N first time-frequency spectra into a second time-frequency spectra of the original seismic signal.

[0124] In the embodiment of the present application, when N first time-frequency spectra corresponding to N S-transform time windows are obtained, the N first time-frequency spectra are combined into a second time-frequency spectra of the original seismic signal.

[0125] Figure 4 is a schematic diagram of the generalized tuned precise S transform, as shown in Figure 4As shown, the left side is an example signal of the original seismic signal, the right side is the time-frequency spectrum corresponding to the original seismic signal, and the black rectangular box is the scope of the S transform time window. By adjusting the size of the time window control parameter K of the S transform time window, the resolution of the time-frequency spectrum in the time domain and the frequency domain can be adjusted at the same time. By obtaining the common area of ​​the two S transform time windows, the resolution of the time-frequency spectrum in the time domain and the frequency domain can be improved at the same time.

[0126] In an embodiment of the present application, an original seismic signal is obtained, and the instantaneous frequency of the original seismic signal is generated according to the original seismic signal and the Hilbert transform signal of the original seismic signal. Then, the instantaneous frequency of the original seismic signal is differentiated to obtain the tuning rate of the original seismic signal. According to the tuning rate and preset N time window control parameters, N S transform time windows are generated. According to the tuning rate and the N S transform time windows, N first time-frequency spectra of the original seismic signal are generated. Finally, the N first time-frequency spectra are merged into the second time-frequency spectra of the original seismic signal. Compared with the prior art, when the precise S transform method obtains the time-frequency spectrum of the seismic signal, since the time window function used by the precise S transform method is specific, it is impossible to simultaneously obtain high-resolution time-frequency spectra in the time domain and the frequency domain, and thus the problem of poor information extraction capability for strong non-steady-state seismic signals is solved. The present application generates multiple transformation time windows by setting multiple time window control parameters, performs time-frequency spectrum calculation on the same original seismic signal through multiple transformation time windows, and finally merges the multiple time-frequency spectra obtained. The final time-frequency spectrum generated is a high-resolution time-frequency spectrum in both the time domain and the frequency domain, thereby improving the information extraction capability of strong non-steady-state seismic signals.

[0127] Figure 5 Schematic diagram of the process of generating time-frequency spectrum of seismic signals based on generalized tuned precise S transform provided in this application Figure 2 , in the above Figure 2 Based on the illustrated embodiment, a specific implementation of step S206 is as follows:

[0128] S501: Calculate an average value of N first time-frequency spectra as a second time-frequency spectra of the original seismic signal, where the average value includes at least one of the following: an arithmetic mean, a geometric mean, and a weighted mean.

[0129] In an embodiment of the present application, a method for calculating the second time-frequency spectrum of the original seismic signal by merging N first time-frequency spectra is to calculate the average value of the N first time-frequency spectra as the second time-frequency spectrum of the original seismic signal. Optionally, the average value includes at least one of the following: arithmetic mean, geometric mean, weighted mean.

[0130] For example, when the average value is a geometric mean, the specific calculation formula for merging N first time-frequency spectra into the second time-frequency spectra of the original seismic signal is:

[0131]

[0132] Among them, S opt (τ, f) represents the second time-frequency spectrum of the original seismic signal, S(τ, f, c(t), k i ), represents the first time-frequency spectrum, N represents the number of S-transform time windows, c(t) represents the tuning rate, k i represents the control parameter of the i-th S-transform time window, f represents the frequency to be analyzed, and τ represents the center moment of the S-transform time window.

[0133] In an embodiment of the present application, by calculating the average value of N first time-frequency spectra as the second time-frequency spectra of the original seismic signal, the resolution of the second time-frequency spectra can be improved, making the weak components in the seismic signal easier to identify, and calculating the average value of multiple first time-frequency spectra can enhance the robustness of the prediction model, so that it can maintain stable prediction performance when facing original seismic signals in different situations.

[0134] Figure 6 Schematic diagram of the process of generating time-frequency spectrum of seismic signals based on generalized tuned precise S transform provided in this application Figure 3 , in the above Figure 2 Based on the illustrated embodiment, a specific implementation of step S205 is as follows:

[0135] S601: Convert the original seismic signal into an original seismic matrix.

[0136] In the embodiment of the present application, the original seismic signal is converted from a time series form into a matrix form, that is, into an original seismic matrix. Optionally, each row or column of the original seismic matrix represents the sampling value of the original seismic signal at different time points or different seismographs.

[0137] S602: Convert each S-transform time window into a time window coefficient matrix.

[0138] In the embodiment of the present application, each S-transform time window is converted into a matrix form, that is, a time window coefficient matrix.

[0139] S603: Perform matrix multiplication on the original earthquake matrix and each time window coefficient matrix to obtain a first time-frequency spectrum.

[0140] In the embodiment of the present application, the converted original seismic matrix and each time window coefficient matrix are matrix-multiplied to obtain a first time-frequency spectrum, and the calculation formula is as follows:

[0141] S(t,f,τ)=Kd

[0142] Where d is the vector of original seismic data x(t), K is the time window coefficient matrix corresponding to the discrete tuned precise S transform, K = w(t,f; τ)e-2πift , S(t,f,τ) is the matrix form of the first time-frequency spectrum.

[0143] In an embodiment of the present application, in order to speed up the calculation speed of the first time-frequency spectrum, the idea of ​​discrete Fourier transform is borrowed to decompose the calculation of the first time-frequency spectrum into the product between the matrix and the vector, that is, the original seismic signal is converted into the original seismic matrix, and each S-transform time window is converted into a time window coefficient matrix, which can speed up the calculation speed of the first time-frequency spectrum.

[0144] Figure 7 Schematic diagram of the process of generating time-frequency spectrum of seismic signals based on generalized tuned precise S transform provided in this application Figure 4 , in the above Figure 2 , Figure 5 or Figure 6 Based on any of the embodiments shown, when there are one or more original seismic signals, after obtaining the original seismic signals, the method further includes:

[0145] S701: Determine the corresponding computing unit for the instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum, and second time-frequency spectrum of each original seismic signal. The computing unit includes at least one of the following: CPU core, thread, process, GPU. Different original seismic signals correspond to the same or different computing units.

[0146] In an embodiment of the present application, for each original seismic signal, the corresponding computing unit is determined according to its specific computing requirements, for example, the calculation of instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum and second time-frequency spectrum. Different original seismic signals may correspond to the same computing unit or to different computing units. Optionally, the computing unit includes a CPU core, a thread, a process, or a GPU.

[0147] S702: Send the instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum, and second time-frequency spectrum corresponding to the original seismic signal to the corresponding computing unit, and the instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum, and second time-frequency spectrum correspond to the same or different computing units.

[0148] In an embodiment of the present application, after determining the computing unit corresponding to the instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum, and second time-frequency spectrum of each original seismic signal, the instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum, and second time-frequency spectrum corresponding to the original seismic signal are sent to the corresponding computing unit.

[0149] Then, for each original seismic signal's instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum, and second time-frequency spectrum, the specific implementation steps for determining the corresponding calculation unit are:

[0150] Get the historical calculation speeds corresponding to the instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum, and second time-frequency spectrum respectively.

[0151] In the embodiment of the present application, the calculation speed of each calculation parameter such as instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum, second time-frequency spectrum, etc. during past execution is obtained. The faster the calculation speed, the lower the calculation complexity.

[0152] Get historical computing performance and current status of multiple computing units.

[0153] In an embodiment of the present application, historical computing performance and current status of multiple computing units are obtained. Optionally, the historical computing performance of the computing units includes indicators such as average computing speed, maximum computing power, memory usage efficiency, etc. when similar tasks were performed in the past. The current status of the computing units includes current computing unit load, available memory, temperature, etc., to ensure that when allocating computing tasks, the processing capacity of the computing units is not exceeded or problems such as overheating of the computing units are caused.

[0154] According to the historical calculation speed, the historical calculation performance and the current state, corresponding calculation units are allocated to the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum and the second time-frequency spectrum.

[0155] In the embodiment of the present application, the most suitable computing unit is allocated to each computing parameter according to the historical computing speed, the historical computing performance and the current state, that is, the corresponding computing unit is allocated to the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum and the second time-frequency spectrum. For example, for computing parameters with lower computational complexity, that is, computing parameters with faster historical computing speed, they are preferentially allocated to computing units with high historical computing performance and currently idle, or to computing units with lower load, so as to ensure that the computing task can be completed efficiently while avoiding the waste of computing resources.

[0156] In an embodiment of the present application, when there are one or more original seismic signals, after obtaining the original seismic signals, the corresponding computing unit is determined for the instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum, and second time-frequency spectrum of each original seismic signal, and the instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum, and second time-frequency spectrum corresponding to the original seismic signal are sent to the corresponding computing unit, and according to the historical computing performance and current status of the computing unit, the corresponding computing unit is allocated to the instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum, and second time-frequency spectrum, and the instantaneous frequency, tuning rate, transformation time window, first time-frequency spectrum, and second time-frequency spectrum with a faster historical computing speed are preferentially allocated to the computing unit with a high historical computing performance and is currently idle, so as to ensure that the computing task can be completed efficiently, shorten the computing time, and optimize resource utilization.

[0157] Figure 8 The present application provides a device for generating a time-frequency spectrum of a seismic signal using a tuned precise S transform. The present application provides a device for generating a time-frequency spectrum of a seismic signal using a tuned precise S transform, comprising: an acquisition module 801 and a processing module 802; wherein:

[0158] The acquisition module 801 is used to acquire the original seismic signal; the processing module 802 is used to generate the instantaneous frequency of the original seismic signal according to the original seismic signal and the Hilbert transform signal of the original seismic signal; the processing module 802 is also used to differentiate the instantaneous frequency of the original seismic signal to obtain the tuning rate of the original seismic signal; the processing module 802 is also used to generate N S-transform time windows according to the tuning rate and preset N time window control parameters, the N time window control parameters correspond to the N S-transform time windows one by one, and N is a positive integer greater than or equal to 1; the processing module 902 is also used to generate N first time-frequency spectra of the original seismic signal according to the tuning rate and the N S-transform time windows, the N S-transform time windows correspond to the N first time-frequency spectra one by one; the processing module is also used to merge the N first time-frequency spectra into a second time-frequency spectra of the original seismic signal.

[0159] The seismic signal time-frequency spectrum generating device of tuned precise S transform provided in this embodiment can execute the method provided in the above method embodiment, and its implementation principle and technical effect are similar, which will not be described in detail in this embodiment.

[0160] Fig. 9 This is a schematic diagram of the structure of the electronic device provided in this application. Fig. 9 As shown, the electronic device 9 provided in this embodiment includes: at least one processor 901 and a memory 902. Optionally, the device 90 further includes a communication component 903. The processor 901, the memory 902 and the communication component 903 are connected via a bus 904.

[0161] In a specific implementation process, at least one processor 901 executes the computer execution instructions stored in the memory 902, so that at least one processor 901 executes the above method.

[0162] The specific implementation process of the processor 901 can be found in the above method embodiment, and its implementation principle and technical effect are similar, so this embodiment will not be repeated here.

[0163] In the above embodiments, it should be understood that the processor may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), etc. A general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the invention may be directly implemented as being executed by a hardware processor, or may be executed by a combination of hardware and software modules in the processor.

[0164] The memory may include a high-speed memory (Random Access Memory, RAM), and may also include a non-volatile memory (Non-volatile Memory, NVM), such as at least one disk memory.

[0165] The bus may be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus may be divided into an address bus, a data bus, a control bus, etc. For ease of representation, the bus in the drawings of the present application is not limited to only one bus or one type of bus.

[0166] The present application also provides a computer-readable storage medium having computer execution instructions stored thereon. When a processor executes the computer execution instructions, a method for generating a time-frequency spectrum of a seismic signal by tuning a precise S transform as described above is implemented.

[0167] The computer-readable storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk. The computer-readable storage medium may be any available medium that can be accessed by a general or special purpose computer.

[0168] An exemplary readable storage medium is coupled to a processor so that the processor can read information from the readable storage medium and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (Application Specific Integrated Circuits, referred to as: ASIC). Of course, the processor and the readable storage medium can also exist in the device as discrete components.

[0169] The division of units is only a logical function division, and there may be other divisions in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be an indirect coupling or communication connection through some interface, device or unit, which can be electrical, mechanical or other forms.

[0170] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0171] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0172] If the function is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or the part of the technical solution, can be embodied in the form of a software product. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods of each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM, Read-Only Memory), random access memory (RAM, Random Access Memory), disk or optical disk, etc. Various media that can store program codes.

[0173] The present application also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, it is used to implement the above-mentioned method for generating a time-frequency spectrum of a seismic signal by tuning a precise S transform.

[0174] It should be noted that, for the aforementioned method embodiments, for the sake of simplicity, they are all expressed as a series of action combinations, but those skilled in the art should be aware that the present application is not limited by the described order of actions, because according to the present application, certain steps can be performed in other orders or simultaneously. Secondly, those skilled in the art should also be aware that the embodiments described in the specification are all optional embodiments, and the actions and modules involved are not necessarily required by the present application.

[0175] It should be further noted that, although the various steps in the flowchart are displayed in sequence according to the indication of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless there is a clear description in this article, the execution of these steps is not strictly limited in order, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowchart may include multiple sub-steps or multiple stages, and these sub-steps or stages are not necessarily executed at the same time, but can be executed at different times, and the execution order of these sub-steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of the sub-steps or stages of other steps.

[0176] It should be understood that the above-mentioned device embodiments are only illustrative, and the device of the present application can also be implemented in other ways. For example, the division of units / modules in the above-mentioned embodiments is only a logical function division, and there may be other division methods in actual implementation. For example, multiple units, modules or components can be combined, or can be integrated into another system, or some features can be ignored or not executed.

[0177] In addition, unless otherwise specified, each functional unit / module in each embodiment of the present application may be integrated into one unit / module, each unit / module may exist physically separately, or two or more units / modules may be integrated together. The above-mentioned integrated unit / module may be implemented in the form of hardware or in the form of a software program module.

Claims

1. A method for generating time-frequency spectrum of seismic signals by generalized tuned precise S transform, characterized in that: include: Obtaining raw seismic signals; generating an instantaneous frequency of the original seismic signal according to the original seismic signal and a Hilbert transform signal of the original seismic signal; Differentiating the instantaneous frequency of the original seismic signal to obtain a tuning rate of the original seismic signal; Generate N S transform time windows according to the tuning rate and preset N time window control parameters, wherein the N time window control parameters correspond to the N S transform time windows one by one, and N is a positive integer greater than or equal to 1; Generate N first time-frequency spectra of the original seismic signal according to the tuning rate and the N S-transform time windows, wherein the N S-transform time windows correspond to the N first time-frequency spectra one by one; The N first time-frequency spectra are combined into a second time-frequency spectra of the original seismic signal.

2. The method according to claim 1, characterized in that The step of merging the N first time-frequency spectra into a second time-frequency spectra of the original seismic signal comprises: An average value of the N first time-frequency spectra is calculated as a second time-frequency spectra of the original seismic signal, wherein the average value includes at least one of the following: an arithmetic mean, a geometric mean, and a weighted mean.

3. The method according to claim 1, characterized in that The step of generating N first time-frequency spectra of the original seismic signal according to the tuning rate and the N S-transform time windows comprises: Converting the original seismic signal into an original seismic matrix; Converting each of the S-transform time windows into a time window coefficient matrix; The original earthquake matrix and each of the time window coefficient matrices are matrix-multiplied to obtain the first time-frequency spectrum.

4. The method according to claim 3, characterized in that When the original seismic signal is one or more, after acquiring the original seismic signal, the method further includes: Determine a corresponding computing unit for the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum of each of the original seismic signals, wherein the computing unit includes at least one of the following: a CPU core, a thread, a process, and a GPU, and different original seismic signals correspond to the same or different computing units; The instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum corresponding to the original seismic signal are sent to the corresponding computing units, and the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum correspond to the same or different computing units.

5. The method according to claim 4, characterized in that The step of determining a corresponding calculation unit for the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum of each of the original seismic signals comprises: Obtaining historical calculation speeds corresponding to the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum, and the second time-frequency spectrum respectively; Get the historical computing performance and current status of multiple computing units; According to the historical calculation speed, the historical calculation performance and the current state, corresponding calculation units are allocated to the instantaneous frequency, the tuning rate, the transformation time window, the first time-frequency spectrum and the second time-frequency spectrum.

6. The method according to any one of claims 1 to 5, characterized in that The step of generating the instantaneous frequency of the original seismic signal according to the original seismic signal and the Hilbert transform signal of the original seismic signal comprises: The instantaneous frequency of the original seismic signal is calculated by the following formula: Among them, the f inst (τ) is the instantaneous frequency of the original seismic signal, x(t) is the original seismic signal, x ′ (t) is the differential of the original seismic signal, y(t) is the Hilbert transform signal of the original seismic signal, and y ′ (t) is the differential of the Hilbert transformed signal.

7. The method according to claim 6, characterized in that The generating N S-transform time windows according to the tuning rate and the preset N time window control parameters comprises: One of the S-transform time windows is calculated using the following formula: Among them, w(t,f;τ) is one of the S transform time windows, t is the time to be analyzed, f is the frequency to be analyzed, τ is the center time of one of the S transform time windows, and f inst (τ) is the instantaneous frequency of the original seismic signal at time τ, Δf(τ) is the difference between the frequency to be analyzed and the instantaneous frequency of the original seismic signal at time τ, k is the time window control parameter of one of the S transform time windows, and c(t) is the tuning rate of the original seismic signal at time t.

8. The method according to claim 7, characterized in that The step of generating N first time-frequency spectra of the original seismic signal according to the tuning rate and the N S-transform time windows comprises: One of the first time-frequency spectra is calculated by the following formula: Among them, S(τ,f,c(t)) is one of the first time-frequency spectra, and w(t-τ,f; τ) is one of the S-transform time windows.

9. A time-frequency spectrum generating device for seismic signals with tuned precise S-transform, characterized in that: include: An acquisition module, used for acquiring original seismic signals; A processing module, configured to generate an instantaneous frequency of the original seismic signal according to the original seismic signal and a Hilbert transform signal of the original seismic signal; The processing module is further used to differentiate the instantaneous frequency of the original seismic signal to obtain the tuning rate of the original seismic signal; The processing module is further used to generate N S-transform time windows according to the tuning rate and preset N time window control parameters, wherein the N time window control parameters correspond to the N S-transform time windows one by one, and N is a positive integer greater than or equal to 1; The processing module is further used to generate N first time-frequency spectra of the original seismic signal according to the tuning rate and the N S-transform time windows, and the N S-transform time windows correspond to the N first time-frequency spectra in one-to-one correspondence; The processing module is further used to merge the N first time-frequency spectra into a second time-frequency spectra of the original seismic signal.

10. An electronic device, characterized in that: include: Memory, processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory, so that the processor performs the method according to any one of claims 1 to 8.

11. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, which are used to implement the method according to any one of claims 1 to 8 when executed by a processor.

12. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 8 when being executed by a processor.

Images