Earthquake first arrival signal picking method, device, equipment, storage medium and product

Abstract

This disclosure relates to the field of geophysical exploration technology, and particularly to a method, apparatus, device, storage medium, and product for acquiring first-arrival signals of earthquakes. The method includes: acquiring a first-arrival signal of an earthquake, performing time-frequency transformation processing on the first-arrival signal to obtain a time-frequency transformation result; calculating the instantaneous travel time based on the time-frequency transformation result; calculating the difference between the instantaneous travel time and the actual time, and acquiring the first-arrival event based on the difference. Therefore, the first-arrival signal acquisition method provided in the exemplary embodiments of this disclosure, through time-frequency transformation and instantaneous travel time calculation, can more accurately capture the dynamic characteristics of earthquake signals, thereby improving the accuracy of earthquake event acquisition. Furthermore, this method can reduce interference from human factors and decrease the dependence of the acquisition process on parameters, improving the objectivity and reliability of earthquake monitoring.

Description

Technical Field

[0001] This disclosure relates to the field of geophysical exploration technology, and in particular to a method, apparatus, device, storage medium, and product for picking up first arrival signals of earthquakes. Background Technology

[0002] Seismic data processing is a key technology in fields such as oil and gas exploration, geological structure analysis, and environmental monitoring. In seismic records, the first wave to arrive is called the "first arrival wave" or simply "first arrival," and accurately identifying this first arrival wave is crucial for obtaining the arrival time of seismic waves and for picking up seismic events.

[0003] In related technologies, coherence analysis, image processing techniques, or amplitude feature analysis are commonly used for seismic event picking. However, these picking methods require users to specify empirical parameters, such as window size and threshold. The selection of these parameters has a significant impact on the accuracy of the picking results, making the picking process highly dependent on these parameters and unable to achieve automatic picking of first arrival signals. Summary of the Invention

[0004] This disclosure provides a method, apparatus, device, storage medium, and product for picking up earthquake first arrival signals, thereby enabling accurate picking of events in earthquake signals without specifying empirical parameters.

[0005] In a first aspect, this disclosure provides a method for picking up earthquake first arrival signals, including:

[0006] The first arrival signal of the earthquake is acquired, and the first arrival signal of the earthquake is subjected to time-frequency transformation processing to obtain the time-frequency transformation result;

[0007] The instantaneous travel time is calculated based on the time-frequency transformation results;

[0008] Calculate the difference between the instantaneous travel time and the actual time, and pick the first arrival wave event based on the difference.

[0009] Secondly, this disclosure provides an earthquake first arrival signal acquisition device, comprising:

[0010] The data acquisition module is used to acquire the first arrival wave signal of the earthquake and perform time-frequency transformation processing on the first arrival wave signal of the earthquake to obtain the time-frequency transformation result;

[0011] The data processing module is used to calculate the instantaneous travel time based on the time-frequency transformation result;

[0012] The data processing module is also used to calculate the difference between the instantaneous travel time and the actual time, and to pick up the first arrival wave event based on the difference.

[0013] Thirdly, this disclosure provides a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the foregoing aspects.

[0014] Fourthly, this disclosure provides a computer-readable storage medium having a computer program stored thereon that, when executed by a processor, implements the steps of the methods described in the above aspects.

[0015] Fifthly, this disclosure provides a computer program product, including a computer program / instructions that, when executed by a processor, implement the steps of the methods described in the foregoing aspects.

[0016] This disclosure provides a method, apparatus, device, storage medium, and product for picking up earthquake first arrival signals. By acquiring earthquake first arrival signals and performing time-frequency transformation processing on the earthquake first arrival signals to obtain time-frequency transformation results; calculating instantaneous travel time based on the time-frequency transformation results; calculating the difference between instantaneous travel time and actual time; and picking up first arrival events based on the difference, thereby improving the accuracy of earthquake event picking.

[0017] Among its technical features, the first arrival wave signal of an earthquake undergoes time-frequency transformation processing, which can capture the non-stationary characteristics of the earthquake signal and provide basic data for subsequent instantaneous travel time calculation.

[0018] Technical features: Instantaneous travel time is calculated based on time-frequency transformation results, which can more accurately capture the dynamic characteristics of seismic signals, thereby improving the accuracy of seismic event picking.

[0019] Technical features: Based on the difference picking of first arrival events, it can reduce the interference of human factors and reduce the dependence of the picking process on parameters, thereby improving the objectivity and reliability of earthquake monitoring. Attached Figure Description

[0020] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0021] Figure 1 A flowchart illustrating an exemplary method for acquiring earthquake first arrival signals provided in this disclosure;

[0022] Figure 2 This is a flowchart illustrating an automatic seismic first arrival event picking method based on instantaneous travel time, provided as an example of this disclosure.

[0023] Figure 3 This is an exemplary schematic diagram of the effect of picking up weak first arrival signals at sea provided in this disclosure;

[0024] Figure 4This is a schematic block diagram of the functional modules of an earthquake first arrival signal acquisition device provided as an example of this disclosure. Detailed Implementation

[0025] To enable those skilled in the art to better understand the technical solutions of this disclosure, and to fully understand and implement the process of how this disclosure applies technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, not all embodiments. The embodiments of this disclosure and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort should fall within the protection scope of this disclosure.

[0026] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0027] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0028] Example 1

[0029] Figure 1 This is a flowchart illustrating an exemplary method for picking up earthquake first arrival signals. By mapping the earthquake signal to the time-frequency domain and back-mapping it to the time domain to calculate the instantaneous travel time, the method achieves automatic picking of earthquake events. This method can accurately pick up events in earthquake signals without specifying empirical parameters.

[0030] like Figure 1 As shown, a method for picking up earthquake first arrival signals may include the following steps:

[0031] Step S110: Obtain the first arrival signal of the earthquake and perform time-frequency transformation processing on the first arrival signal of the earthquake to obtain the time-frequency transformation result.

[0032] In the embodiment, the first wave to arrive on the seismic record is called the "first arrival wave", or simply "first arrival".

[0033] Methods for obtaining the first arrival signal may include:

[0034] Energy ratio method: By calculating the energy ratio of different time windows in seismic data, regions with significant energy increases can be identified, which usually correspond to the occurrence of the first arrival wave. When the energy ratio is greater than a preset threshold, the time series following that time point can be determined as the time range of the first arrival wave.

[0035] Point cloud time series conversion: Seismic waveform data is converted into point cloud time series, and then a persistence graph is constructed based on the point cloud time series. By analyzing the persistence graph, the location of the first arrival wave can be identified. This method utilizes topological data analysis to improve the picking speed and accuracy.

[0036] Time window energy ratio method: The time series is divided into multiple time windows. For each time point, the energy ratio of seismic data from subsequent time windows to the seismic data from all preceding time windows is calculated. When the energy ratio is greater than a preset threshold, the time series following that time point can be determined as the time range of the first arrival wave of the earthquake.

[0037] Automatic picking algorithm: By analyzing seismic waveform data, the arrival time of the first arrival wave is determined using the bisection method or other automatic picking algorithms.

[0038] Topological data analysis: Topological data analysis methods, such as persistent homology, are used to extract the topological features of seismic waveform data. By measuring the differences of these features from one window to the next, a first arrival detector can be constructed to identify the first arrival wave of the earthquake.

[0039] Adaptive energy threshold constraint processing: The seismic wave data undergoes adaptive energy threshold constraint processing and denoising, and then the first arrival wave peak is determined. By performing local linear fitting on the wave peak, the first arrival wave peak can be determined more accurately, and the first arrival time can be picked.

[0040] The above methods can be used individually or in combination to improve the accuracy and efficiency of initial wave pickup.

[0041] In this embodiment, time-frequency transformation is the process of converting a one-dimensional time-series signal into a two-dimensional time-frequency domain representation.

[0042] Step S120: Calculate the instantaneous travel time based on the time-frequency transformation results.

[0043] In this embodiment, the instantaneous travel time describes the phase characteristics of a seismic wave at a specific moment and is the ratio of the derivative of the seismic signal's phase to its frequency. The instantaneous travel time can be calculated based on the time-frequency representation of the signal; in the time-frequency domain, it can be calculated by analyzing the signal's phase. For a given seismic signal, its instantaneous travel time is equal to the signal's travel time at all frequencies. By analyzing the difference between the instantaneous travel time and the actual time, the arrival time of the seismic event can be identified.

[0044] Step S130: Calculate the difference between instantaneous travel time and actual time, and pick the first arrival wave event based on the difference.

[0045] The arrival time of a seismic first wave event can be identified by analyzing the difference between the instantaneous travel time and the actual time. The zero-crossing point where the difference changes from a positive to a negative value is the actual arrival time of the seismic first wave event.

[0046] Based on this, by calculating time-frequency transformation and instantaneous travel time, the dynamic characteristics of seismic signals can be captured more accurately, thereby improving the accuracy of seismic event picking. Furthermore, this method can reduce interference from human factors and decrease the dependence of the picking process on parameters, thus improving the objectivity and reliability of seismic monitoring.

[0047] Example 2

[0048] Based on the above embodiments, in another embodiment provided in this disclosure, step S110 may include:

[0049] The time-frequency transformation of the first arrival wave signal is performed by Fourier transform to obtain the time-frequency transformation result of the first arrival wave signal; Fourier transform includes any one of the following: short-time Fourier transform, wavelet transform and local Fourier transform.

[0050] In this embodiment, any one of the short-time Fourier transform, wavelet transform, and local Fourier transform can be used to perform a time-frequency transformation on the preprocessed first-arrival signal s(t), mapping it to the time-frequency domain S(t, w). The time-frequency transformation can reveal the non-stationary characteristics of the first-arrival signal, that is, the characteristic of the frequency of the first-arrival signal changing with time. The frequency domain representation of the first-arrival signal is S(w), and the time-frequency transformation result is represented as S(t, w).

[0051] Based on this, by using time-frequency transformation, the non-stationary characteristics of seismic signals can be captured, providing basic data for subsequent instantaneous travel time calculations.

[0052] Example 3

[0053] Based on the above embodiments, in another embodiment provided in this disclosure, step S120 may include:

[0054] The instantaneous travel time of the seismic signal at each time point is calculated.

[0055] Instantaneous travel time describes the phase characteristics of a seismic wave at a specific moment. It is the ratio of the derivative of the phase of the seismic signal to its frequency, and can be expressed as τ(t).

[0056] For example, for an ideal pulse signal, its instantaneous travel time τ(w) is equal to the signal travel time at all frequencies.

[0057] For an initial arrival signal s(t), the instantaneous travel time τ(w) at a specific frequency can be defined as:

[0058]

[0059] Where Im represents the imaginary part; It is the derivative of S(w) with respect to frequency w.

[0060] Instantaneous travel time can be calculated based on the time-frequency representation of a signal. In the time-frequency domain, instantaneous travel time can be calculated by analyzing the phase of the signal. For a given seismic signal, its instantaneous travel time is equal to the signal's travel time at all frequencies. By analyzing the difference between the instantaneous travel time and the actual time, the arrival time of the seismic event can be identified.

[0061] For example, for a real signal with a finite frequency band, the instantaneous travel time τ(t) can be defined as:

[0062]

[0063] Where S(t, w) represents the time-frequency transformation result of the first arrival wave signal; This represents the partial derivative with respect to frequency.

[0064] Based on this, by calculating the instantaneous travel time of the seismic signal at each time point, the non-stationary characteristics of the seismic signal can be captured more accurately, and the first arrival characteristics of the seismic wave can be better identified.

[0065] Example 4

[0066] Based on the above embodiments, in another embodiment provided in this disclosure, step S130 may include:

[0067] Obtain the actual time when the seismic wave arrives at the detector;

[0068] Calculate the difference between instantaneous travel time and actual time;

[0069] Pick the first arrival wave event at the zero crossover point where the difference changes from positive to negative.

[0070] In this embodiment, the moment when the seismic wave arrives at the detector can be obtained as the actual time, and the instantaneous travel time can be calculated based on the time-frequency representation of the signal. For a given seismic signal, its instantaneous travel time is equal to the signal's travel time at all frequencies; therefore, the instantaneous travel time can be calculated by analyzing the phase of the signal.

[0071] After obtaining the instantaneous travel time and the actual time, the arrival time of the first arrival wave event can be identified by analyzing the difference between the instantaneous travel time τ(t) and the actual time t. The zero-crossing point where the difference changes from a positive value to a negative value is the actual arrival time of the first arrival wave event.

[0072] Based on this, by calculating the instantaneous travel time and comparing it with the actual time, the arrival time of seismic waves can be identified more accurately, enhancing the accuracy and reliability of the picking process and reducing the dependence of the picking process on parameters.

[0073] Example 5

[0074] Based on the above embodiments, in another embodiment provided in this disclosure, the above-mentioned earthquake first arrival signal acquisition method may further include:

[0075] Calculate the weighted frequency average and variance of the time-frequency coefficients to estimate the effective frequency bandwidth of the earthquake first arrival signal.

[0076] In this embodiment, frequency bandwidth estimation refers to the process of quantifying the range of effective frequency components in the first arrival signal of an earthquake. This is crucial for understanding the frequency content of the first arrival signal and improving the accuracy of event picking. Frequency bandwidth estimation can be achieved by calculating the weighted frequency average and variance of the time-frequency coefficients.

[0077] Specifically, the analog signal of the first arrival wave of the earthquake can be converted into a digital signal first, and then spectral analysis can be performed using Discrete Fourier Transform or Fast Fourier Transform to obtain the spectral characteristics corresponding to different waveforms, i.e., the frequency components of different seismic waves. The frequency corresponding to the spectral maximum is the frequency point where the energy in the signal is most concentrated. The amplitude spectrum is the width between two frequency values ​​that are 0.707 times the maximum value, which represents the main frequency range of the signal.

[0078] Furthermore, in seismic signal processing, frequency bandwidth can be achieved by calculating the weighted frequency average and variance of the time-frequency coefficients. The weighted frequency average, also known as the centroid frequency (FC), refers to the weighted average frequency of the signal power spectrum, while the frequency variance (VF) is the weighted average of the squared deviations of frequencies in the signal power spectrum relative to the centroid frequency.

[0079] Based on this, frequency bandwidth estimation of seismic signals can provide important frequency information for seismic event picking, thereby improving the accuracy and efficiency of picking.

[0080] Example 6

[0081] Based on the above embodiments, in another embodiment provided in this disclosure, the above-mentioned earthquake first arrival signal acquisition method may further include:

[0082] The picked-up first arrival event is filtered to remove high-frequency noise from the first arrival signal;

[0083] The picked-up first arrival events are smoothed to reduce random fluctuations in the first arrival signal.

[0084] In the embodiments, the above-mentioned earthquake first-arrival signal picking method may further include processing the first-arrival events that have been identified by the earthquake event picking method to improve the stability and accuracy of the picking results.

[0085] Specifically, various filters (such as low-pass filters, high-pass filters, or band-pass filters) can be used to remove unwanted frequency components, reduce noise, or enhance specific frequency components in a signal.

[0086] Smoothing techniques (such as moving average or Gaussian smoothing) can also be applied to reduce random fluctuations in the signal, making the characteristics of the first arrival event more obvious and stable.

[0087] In addition, the amplitude of the first arrival event can be corrected to eliminate amplitude variations caused by geological structures or instrument responses.

[0088] In addition, the phase of the first arrival event can be corrected to ensure the accuracy of the phase information.

[0089] In addition, linear or nonlinear trends in the signal can be removed to highlight the characteristics of seismic events.

[0090] Therefore, the above processing method helps to improve the accuracy and reliability of picking first arrival events of earthquakes.

[0091] One or more technical solutions provided in the exemplary embodiments of this disclosure calculate instantaneous travel time by mapping seismic signals to the time-frequency domain and back-mapping them to the time domain, thereby enabling automatic picking of seismic events.

[0092] Therefore, the earthquake first arrival signal picking method provided in the exemplary embodiments of this disclosure can automatically pick up events in earthquake signals without specifying empirical parameters.

[0093] Example 7

[0094] Based on the above embodiments, this embodiment provides an application example.

[0095] Seismic data processing is a key technology in fields such as oil and gas exploration, geological structure analysis, and environmental monitoring. In seismic records, the first wave to arrive is called the "first arrival wave" or simply "first arrival," and accurately identifying this first arrival wave is crucial for obtaining the arrival time of seismic waves and for picking up seismic events.

[0096] In related technologies, coherence analysis, image processing techniques, or amplitude feature analysis are commonly used for seismic event picking. However, these picking methods require users to specify empirical parameters, such as window size and threshold. The selection of these parameters has a significant impact on the accuracy of the picking results, making the picking process highly dependent on these parameters and unable to achieve automatic picking of first arrival signals.

[0097] To address the aforementioned issues, this embodiment proposes an automatic seismic first-arrival event picking method based on instantaneous travel time. By mapping the seismic signal to the time-frequency domain and then back-mapping it to the time domain to calculate the instantaneous travel time, automatic seismic event picking is achieved. This method can accurately pick events from seismic signals without specifying empirical parameters.

[0098] For example, Figure 2 This is a flowchart illustrating an exemplary method for automatic seismic first-arrival event picking based on instantaneous travel time, as provided in this disclosure. Figure 2 As shown, the method may include the following steps:

[0099] Step S210: Preprocess the first arrival wave signal of the earthquake.

[0100] The first wave to arrive in an earthquake record is called the "first arrival wave," or simply "first arrival."

[0101] Methods for obtaining the first arrival signal may include:

[0102] Energy ratio method: By calculating the energy ratio of different time windows in seismic data, regions with significant energy increases can be identified, which usually correspond to the occurrence of the first arrival wave. When the energy ratio is greater than a preset threshold, the time series following that time point can be determined as the time range of the first arrival wave.

[0103] Point cloud time series conversion: Seismic waveform data is converted into point cloud time series, and then a persistence graph is constructed based on the point cloud time series. By analyzing the persistence graph, the location of the first arrival wave can be identified. This method utilizes topological data analysis to improve the picking speed and accuracy.

[0104] Time window energy ratio method: The time series is divided into multiple time windows. For each time point, the energy ratio of seismic data from subsequent time windows to the seismic data from all preceding time windows is calculated. When the energy ratio is greater than a preset threshold, the time series following that time point can be determined as the time range of the first arrival wave of the earthquake.

[0105] Automatic picking algorithm: By analyzing seismic waveform data, the arrival time of the first arrival wave is determined using the bisection method or other automatic picking algorithms.

[0106] Topological data analysis: Topological data analysis methods, such as persistent homology, are used to extract the topological features of seismic waveform data. By measuring the differences of these features from one window to the next, a first arrival detector can be constructed to identify the first arrival wave of the earthquake.

[0107] Adaptive energy threshold constraint processing: The seismic wave data undergoes adaptive energy threshold constraint processing and denoising, and then the first arrival wave peak is determined. By performing local linear fitting on the wave peak, the first arrival wave peak can be determined more accurately, and the first arrival time can be picked.

[0108] The above methods can be used individually or in combination to improve the accuracy and efficiency of initial wave pickup.

[0109] After obtaining the first arrival signal of the earthquake, it needs to be preprocessed to improve data quality and prepare for subsequent analysis. Preprocessing may include denoising and normalization.

[0110] One approach is to use a bandpass filter for denoising, removing high-frequency noise and low-frequency drift. The denoised signal is then normalized to ensure uniform amplitude, thereby improving the accuracy of the time-frequency conversion.

[0111] Step S220: Perform time-frequency transformation on the preprocessed first arrival signal.

[0112] Time-frequency transformation is the process of converting a one-dimensional time-series signal into a two-dimensional time-frequency domain representation.

[0113] For example, any of the short-time Fourier transform, wavelet transform, and local Fourier transform can be used to perform a time-frequency transformation on the preprocessed first-arrival signal s(t), mapping it to the time-frequency domain S(t, w). The time-frequency transformation can reveal the non-stationary characteristics of the first-arrival signal, that is, the frequency variation of the first-arrival signal over time. Here, the frequency domain representation of the first-arrival signal is S(w), and the time-frequency transformation result is represented as S(t, w).

[0114] By using time-frequency transformation, the non-stationary characteristics of seismic signals can be captured, providing basic data for subsequent instantaneous travel time calculations.

[0115] Step S230: Calculate the instantaneous travel time for the seismic signal at each time point.

[0116] Instantaneous travel time describes the phase characteristics of a seismic wave at a specific moment. It is the ratio of the derivative of the phase of the seismic signal to its frequency, and can be expressed as τ(t).

[0117] For example, for an ideal pulse signal, its instantaneous travel time τ(w) is equal to the signal travel time at all frequencies.

[0118] For an initial arrival signal s(t), the instantaneous travel time τ(w) at a specific frequency can be defined as:

[0119]

[0120] Where Im represents the imaginary part; It is the derivative of S(w) with respect to frequency w.

[0121] Instantaneous travel time can be calculated based on the time-frequency representation of a signal. In the time-frequency domain, instantaneous travel time can be calculated by analyzing the phase of the signal. For a given seismic signal, its instantaneous travel time is equal to the signal's travel time at all frequencies. By analyzing the difference between the instantaneous travel time and the actual time, the arrival time of the seismic event can be identified.

[0122] For example, for a real signal with a finite frequency band, the instantaneous travel time τ(t) can be defined as:

[0123]

[0124] Where S(t,w) represents the time-frequency transformation result of the first arrival wave signal; This represents the partial derivative with respect to frequency.

[0125] Step S240: Estimate the effective frequency bandwidth of the first arrival wave signal.

[0126] Frequency bandwidth estimation refers to the process of quantifying the range of effective frequency components in a seismic first-arrival signal. This is crucial for understanding the frequency content of the first-arrival signal and improving the accuracy of event picking. Frequency bandwidth estimation can be achieved by calculating the weighted frequency average and variance of the time-frequency coefficients.

[0127] Specifically, the analog signal of the first arrival wave of the earthquake can be converted into a digital signal first, and then spectral analysis can be performed using Discrete Fourier Transform or Fast Fourier Transform to obtain the spectral characteristics corresponding to different waveforms, i.e., the frequency components of different seismic waves. The frequency corresponding to the spectral maximum is the frequency point where the energy in the signal is most concentrated. The amplitude spectrum is the width between two frequency values ​​that are 0.707 times the maximum value, which represents the main frequency range of the signal.

[0128] Furthermore, in seismic signal processing, frequency bandwidth can be achieved by calculating the weighted frequency average and variance of the time-frequency coefficients. The weighted frequency average, also known as the centroid frequency (FC), refers to the weighted average frequency of the signal power spectrum, while the frequency variance (VF) is the weighted average of the squared deviations of frequencies in the signal power spectrum relative to the centroid frequency.

[0129] Based on this, frequency bandwidth estimation of seismic signals can provide important frequency information for seismic event picking, thereby improving the accuracy and efficiency of picking.

[0130] Step S250: Identify earthquake events.

[0131] For example, the arrival time of a seismic first wave event can be identified by analyzing the difference between the instantaneous travel time τ(t) and the actual time t. The zero-crossing point where the difference changes from a positive to a negative value is the actual arrival time of the seismic first wave event.

[0132] Step S260: Post-process the first arrival event of the earthquake.

[0133] Post-processing can include filtering and smoothing the acquired first-arrival events to improve the stability and accuracy of the acquisition results. Specifically, a low-pass filter can be used to remove high-frequency noise, or a smoothing algorithm can be used to reduce signal fluctuations.

[0134] Step S270: Result verification.

[0135] The results of automatic picking are compared with those of known seismic events or those picked manually to verify the effectiveness and accuracy of the automatic picking method. This can include the following steps:

[0136] First, collect both automatically picked and manually picked results for the same seismic event. This data can come from seismic network records, with manually picked results typically obtained by seismologists through careful analysis of waveform data, serving as a reference standard.

[0137] Then, the arrival times of automatically acquired seismic waves are compared with those acquired manually. This comparison can be quantitative, i.e., calculating the time difference between the two, or qualitative, i.e., assessing the consistency between the automatically acquired and manually acquired results.

[0138] After obtaining the comparison results, statistical analysis is performed to calculate the deviation between the automatically picked results and the manually picked results. For example, statistical measures such as the mean, standard deviation, maximum, and minimum of the deviation can be calculated to evaluate the accuracy of the automatic picking method.

[0139] The accuracy of the automatic picking method can also be evaluated based on statistical results. For example, a time threshold (such as 0.1 seconds) can be set, and then the proportion of automatic picking results that match manual picking results within that threshold can be calculated to measure the accuracy of the automatic picking method.

[0140] Finally, for errors exceeding the threshold, error analysis is performed to identify potential sources of error, such as noise interference and limitations of the automatic picking algorithm, and to explore improvement methods. Based on the comparison results and error analysis, the automatic picking method is improved and optimized to enhance its effectiveness and accuracy.

[0141] For example, Figure 3 This is an exemplary schematic diagram of the effect of weak first arrival signal acquisition at sea provided in this disclosure, such as... Figure 3 As shown, the automatic first arrival event picking method based on instantaneous travel time provided in this embodiment can effectively pick up weak first arrivals for different types of seismic data.

[0142] One or more technical solutions provided in the exemplary embodiments of this disclosure calculate instantaneous travel time by mapping seismic signals to the time-frequency domain and back-mapping them to the time domain, thereby enabling automatic picking of seismic events.

[0143] Therefore, the earthquake first arrival signal picking method provided in the exemplary embodiments of this disclosure can automatically pick up events in earthquake signals without specifying empirical parameters.

[0144] Example 8

[0145] Based on the above embodiments, this embodiment provides an electronic device. In the case of dividing each functional module according to its corresponding functions, the exemplary embodiment of this disclosure provides an earthquake first arrival signal acquisition device, which can be a server or a chip applied to a server. Figure 4 This is a schematic block diagram illustrating the functional modules of an exemplary earthquake first-arrival signal acquisition device provided in this disclosure. Figure 4 As shown, the earthquake initial arrival signal acquisition device 400 includes:

[0146] The data acquisition module 410 is used to acquire the first arrival wave signal of the earthquake and perform time-frequency transformation processing on the first arrival wave signal of the earthquake to obtain the time-frequency transformation result;

[0147] Data processing module 420 is used to calculate instantaneous travel time based on the time-frequency transformation result;

[0148] The data processing module 420 is also used to calculate the difference between the instantaneous travel time and the actual time, and to pick up the first arrival wave event based on the difference.

[0149] In another embodiment provided in this disclosure, the data processing module 420 is further configured to perform time-frequency transformation processing on the earthquake first arrival signal through Fourier transform to obtain the time-frequency transformation result of the earthquake first arrival signal; the Fourier transform includes: short-time Fourier transform, wavelet transform or local Fourier transform.

[0150] In another embodiment provided in this disclosure, the data processing module 420 is further configured to define the instantaneous travel time τ(w) at a specific frequency for the earthquake first arrival signal s(t) as:

[0151]

[0152] Where Im represents the imaginary part; It is the derivative of S(w) with respect to frequency w;

[0153] For a real signal with a finite frequency band, the instantaneous travel time τ(t) is defined as:

[0154]

[0155] Where S(t,w) represents the time-frequency transformation result of the first arrival wave signal; This represents the partial derivative with respect to frequency.

[0156] In another embodiment provided in this disclosure, the data processing module 420 is further configured to acquire the actual time of the seismic wave arrival at the detector; calculate the difference between the instantaneous travel time and the actual time; and pick up the first arrival event at the zero crossover point where the difference changes from a positive value to a negative value.

[0157] In another embodiment provided in this disclosure, the data processing module 420 is further configured to calculate the weighted frequency average and variance of the time-frequency coefficients and estimate the effective frequency bandwidth of the earthquake first arrival signal.

[0158] In another embodiment provided in this disclosure, the data processing module 420 is further configured to filter the picked-up first arrival event to remove high-frequency noise from the first arrival signal; and to smooth the picked-up first arrival event to reduce random fluctuations in the first arrival signal.

[0159] Based on the above embodiments, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method described in the above embodiments.

[0160] In some embodiments of this example, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the steps of the method described in the above embodiments.

[0161] In some embodiments of this example, a computer program product is provided, including a computer program / instructions, which, when executed by a processor, implements the steps of the method described in the above embodiments.

[0162] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component, for executing the methods in the above embodiments.

[0163] Computer-readable storage media can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Computer-readable storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, and computer storage media (e.g., hard disks, floppy disks, solid-state drives, removable disks, CD-ROMs, DVD-ROMs, Blu-ray discs, etc.).

[0164] Computer-readable storage media may also store at least one computer-executable program / instruction, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.

[0165] In addition, the computer device may include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., keyboard, mouse, speakers, etc.).

[0166] The processor can communicate with external devices via the I / O bus through wired or wireless networks.

[0167] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product / computer program product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.

[0168] In the embodiments provided in this disclosure, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0169] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0170] While the embodiments disclosed herein are as described above, the foregoing content is merely for the purpose of facilitating understanding of this disclosure and is not intended to limit this disclosure. Any person skilled in the art to which this disclosure pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope of this disclosure; however, the scope of patent protection of this disclosure shall still be determined by the scope defined in the appended claims.

Claims

1. A method for acquiring first-arrival signals of an earthquake, characterized in that, include: The first arrival signal of the earthquake is acquired, and the first arrival signal of the earthquake is subjected to time-frequency transformation processing to obtain the time-frequency transformation result; The instantaneous travel time is calculated based on the time-frequency transformation results; Calculate the difference between the instantaneous travel time and the actual time, and pick the first arrival wave event based on the difference.

2. The method according to claim 1, characterized in that, The step of performing time-frequency transformation processing on the first arrival wave signal of the earthquake to obtain the time-frequency transformation result includes: The earthquake first arrival signal is processed by time-frequency transformation using Fourier transform to obtain the time-frequency transformation result of the earthquake first arrival signal; the Fourier transform includes any one of short-time Fourier transform, wavelet transform and local Fourier transform.

3. The method according to claim 2, characterized in that, The calculation of instantaneous travel time based on the time-frequency transformation result includes: For the first arrival signal s(t) of an earthquake, the instantaneous travel time τ(w) at a specific frequency is defined as: Where Im represents the imaginary part; It is the derivative of S(w) with respect to frequency w; For a real signal with a finite frequency band, the instantaneous travel time τ(t) is defined as: Where S(t, w) represents the time-frequency transformation result of the first arrival wave signal; This represents the partial derivative with respect to frequency.

4. The method according to claim 1, characterized in that, The calculation of the difference between the instantaneous travel time and the actual time, and the picking of the first arrival wave event based on the difference, includes: Obtain the actual time when the seismic wave arrives at the detector; Calculate the difference between the instantaneous travel time and the actual time; At the zero-crossing point where the difference changes from a positive value to a negative value, the first arrival wave event is picked up.

5. The method according to claim 1, characterized in that, The method further includes: Calculate the weighted frequency average and variance of the time-frequency coefficients to estimate the effective frequency bandwidth of the earthquake first arrival signal.

6. The method according to claim 1, characterized in that, The method further includes: The picked-up first arrival event is filtered to remove high-frequency noise from the first arrival signal; The picked-up first arrival events are smoothed to reduce random fluctuations in the first arrival signal.

7. A device for acquiring earthquake first arrival signals, characterized in that, include: The data acquisition module is used to acquire the first arrival wave signal of the earthquake and perform time-frequency transformation processing on the first arrival wave signal of the earthquake to obtain the time-frequency transformation result; The data processing module is used to calculate the instantaneous travel time based on the time-frequency transformation result; The data processing module is also used to calculate the difference between the instantaneous travel time and the actual time, and to pick up the first arrival wave event based on the difference.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When executed by a processor, the computer program implements the steps of the method according to any one of claims 1 to 6.

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