Microseismic waveform arrival time pickup method, system, equipment and medium

Abstract

The invention provides a microseismic waveform arrival time pickup method, system and device and a medium, and relates to the technical field of signal processing, and the method comprises the steps: obtaining full waveform data comprising N original data points; determining the original data points meeting a preset maximum and minimum condition as local maximum and minimum points; determining the local maximum and minimum point meeting a preset screening condition as a target local maximum and minimum point; determining an AIC value of each target local extreme value point; determining a first target extreme value point from each target local extreme value point according to each AIC value, and determining longitudinal wave arrival time according to the first target extreme value point; according to the signal absolute value corresponding to each original data point, determining an absolute extreme value point; determining a target calculation interval according to the first target extreme value point and the absolute extreme value point; and determining a second target extreme value point according to the AIC value of each target local extreme value point in the target calculation interval, and determining the transverse wave arrival time according to the second target extreme value point. The pickup efficiency and the pickup precision of the longitudinal wave arrival time and the transverse wave arrival time are improved.

Description

Technical Field

[0001] The present invention relates to the field of signal processing technology, and in particular to a method, system, device and medium for picking up microseismic waveform arrival time. Background Art

[0002] Microseismic waveform arrival time picking includes picking longitudinal waves and shear waves. Existing methods for picking microseismic waveform arrival time use the Akaike Information Criterion (AIC) to calculate each data point in the full waveform, obtaining the AIC value corresponding to each data point. The time point corresponding to the data point with the smallest AIC value is then determined as the longitudinal wave arrival time. The shear wave arrival time is then determined based on the longitudinal wave arrival time. Existing methods for picking microseismic waveform arrival time have low picking accuracy, slow calculation speed, and high resource consumption. Summary of the Invention

[0003] In view of this, the purpose of the present invention is to overcome the deficiencies in the prior art and provide a method, system, device and medium for picking up microseismic waveform arrival times. The present invention provides the following technical solutions: In a first aspect, the present invention provides a method for picking microseismic waveform arrival times, the method comprising: Acquire full waveform data, the full waveform data including: N original data points, each of the original data points representing a wave signal value at a different moment; Determining at least one of the original data points that meets a preset maximum condition as a local maximum point; Determine at least one local maximum point that meets a preset screening condition as a target local maximum point; Determine the AIC value of each target local maximum point based on the Akaike Information Criterion; Determining a first target maximum point from each target local maximum point according to each AIC value, and determining a time corresponding to the first target maximum point as a longitudinal wave arrival time; Determine an absolute maximum point according to the absolute value of the signal corresponding to each of the original data points, wherein the absolute value of the signal is the absolute value of the wave signal value corresponding to the original data point; Determining a target calculation interval according to the first target maximum point and the absolute maximum point; According to the AIC values of the target local maximum points within the target calculation interval, the second target maximum point is determined, and the time corresponding to the second target maximum point is determined as the shear wave arrival time.

[0004] In an optional embodiment, determining at least one original data point that meets a preset maximum condition as a local maximum point includes: If the wave signal value of the i-th original data point is greater than the wave signal value of the (i - 1)-th original data point and greater than the wave signal value of the (i + 1)-th original data point, then the i-th original data point is determined as the local extreme value point; Alternatively, if the wave signal value of the i-th original data point is less than the wave signal value of the (i - 1)-th original data point and less than the wave signal value of the (i + 1)-th original data point, then the i-th original data point is determined as the local extreme value point, where 1 < i < N.

[0005] In an alternative embodiment, the number of local extreme value points is M and M < N. Determining at least one of the local extreme value points that meets a preset screening condition as the target local extreme value point includes: If the time interval between the j-th local extreme value point and the (j - 1)-th local extreme value point is greater than the minimum waveform period, then it is determined that the (j - 1)-th local extreme value point and the j-th local extreme value point meet the preset screening condition; The (j - 1)-th local extreme value point and the j-th local extreme value point are respectively determined as the target local extreme value points, where 1 < j ≤ M.

[0006] In an alternative embodiment, obtaining the minimum waveform period includes: Obtaining the maximum frequency of the full waveform data; Determining the minimum waveform period of the full waveform data according to the maximum frequency.

[0007] In an alternative embodiment, determining the first target extreme value point from the target local extreme value points according to the respective AIC values includes: Comparing the magnitudes of the respective AIC values, and determining the target local extreme value point with the smallest AIC value as the first target extreme value point.

[0008] In an alternative embodiment, determining the absolute extreme value point according to the absolute value of the signal corresponding to each original data point includes: Determining the original data point with the largest absolute value of the signal as the absolute extreme value point.

[0009] In an alternative embodiment, determining the second target extreme value point according to the AIC values of the target local extreme value points within the target calculation interval includes: Comparing the AIC values of the target local extreme value points within the target calculation interval; Determining the target local extreme value point with the smallest AIC value within the target calculation interval as the second target extreme value point.

[0010] Second aspect, the present invention provides a microseismic waveform arrival time picking system, the system comprising: A waveform acquisition module, configured to acquire full waveform data, the full waveform data including: N original data points, each of the original data points respectively representing wave signal values at different times; A first screening module, configured to determine at least one of the original data points that meet a preset maximum / minimum condition as a local maximum / minimum point; A second screening module, configured to determine at least one of the local maximum / minimum points that meet a preset screening condition as a target local maximum / minimum point; A calculation module, configured to respectively determine the AIC value of each of the target local maximum / minimum points based on the Akaike information criterion; A P-wave arrival time determination module, configured to determine a first target maximum / minimum point from each of the target local maximum / minimum points according to each of the AIC values, and determine the time corresponding to the first target maximum / minimum point as the P-wave arrival time; A first determination module, configured to determine an absolute maximum / minimum point according to the absolute value of the signal corresponding to each of the original data points, the absolute value of the signal being the absolute value of the wave signal value corresponding to the original data point; A second determination module, configured to determine a target calculation interval according to the first target maximum / minimum point and the absolute maximum / minimum point; An S-wave arrival time determination module, configured to determine a second target maximum / minimum point according to the AIC value of each of the target local maximum / minimum points within the target calculation interval, and determine the time corresponding to the second target maximum / minimum point as the S-wave arrival time.

[0011] Third aspect, the present invention provides an electronic device, comprising a memory and a processor, the memory storing a computer program, and when the computer program runs on the processor, it executes the microseismic waveform arrival time picking method described in the first aspect.

[0012] Fourth aspect, the present invention provides a computer-readable storage medium, the computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, it implements the microseismic waveform arrival time picking method described in the first aspect.

[0013] The microseismic waveform arrival time picking method, system, device and medium provided by this application optimize the picking processes of the longitudinal wave arrival time and the transverse wave arrival time, and improve the picking efficiency and accuracy of the longitudinal wave arrival time and the transverse wave arrival time. The method includes: obtaining full waveform data, where the full waveform data includes N original data points, and each original data point represents a wave signal value at a different moment; determining at least one of the original data points that meets the preset maximum and minimum conditions as local maximum and minimum points; determining at least one of the local maximum and minimum points that meets the preset screening conditions as target local maximum and minimum points; respectively determining the AIC values of each target local maximum and minimum point based on the Akaike information criterion; according to each AIC value, determining a first target maximum and minimum point from each target local maximum and minimum point, and determining the moment corresponding to the first target maximum and minimum point as the longitudinal wave arrival time; determining absolute maximum and minimum points according to the absolute values of the signals corresponding to each original data point, where the signal absolute value is the absolute value of the wave signal value corresponding to the original data point; determining a target calculation interval according to the first target maximum and minimum point and the absolute maximum and minimum points; determining a second target maximum and minimum point according to the AIC values of each target local maximum and minimum point within the target calculation interval, and determining the moment corresponding to the second target maximum and minimum point as the transverse wave arrival time.

[0014] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following specifically enumerates preferred embodiments and, in conjunction with the accompanying drawings, makes the following detailed description. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the drawings required in the embodiments. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as limiting the scope. For those of ordinary skill in the art, other related drawings can be obtained based on these drawings without creative efforts.

[0016] Figure 1 FIG. shows a flowchart of the microseismic waveform arrival time picking method provided by an embodiment of this application; Figure 2 FIG. shows an example diagram of the full waveform data provided by an embodiment of this application; Figure 3 FIG. shows another flowchart of the microseismic waveform arrival time picking method provided by an embodiment of this application; Figure 4 FIG. shows yet another flowchart of the microseismic waveform arrival time picking method provided by an embodiment of this application; Figure 5 FIG. shows an example diagram of the waveform picking result provided by an embodiment of this application; Figure 6 FIG. shows a comparison diagram of the time required for three different waveform picking methods provided by an embodiment of this application; Figure 7 Shows a schematic structural diagram of a microseismic waveform arrival time picking system provided by an embodiment of the present application; Figure 8 Shows a schematic structural diagram of an electronic device provided by an embodiment of the present application.

[0017] Description of main element symbols: 700 - Microseismic waveform arrival time picking system; 710 - Waveform acquisition module; 720 - First screening module; 730 - Second screening module; 740 - Calculation module; 750 - P-wave arrival time determination module; 760 - First determination module; 770 - Second determination module; 780 - S-wave arrival time determination module; 800 - Electronic device; 801 - Transceiver; 802 - Processor; 803 - Memory. Specific embodiments

[0018] The embodiments of the present invention will be described in detail below. The examples of the embodiments are shown in the drawings, where the same or similar reference numerals denote the same or similar elements or elements with the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary only for explaining the present invention and should not be construed as limiting the present invention.

[0019] In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be construed as indicating or implying relative importance or implicitly indicating the quantity of the indicated technical features. Thus, the features defined with "first" and "second" may explicitly or implicitly include one or more of such features. In the description of the present invention, "a plurality" means two or more unless otherwise specifically defined.

[0020] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which this application belongs. The terms used in the specification of this template are only for the purpose of describing specific embodiments and are not intended to limit the present invention. The term "and / or" used herein includes any and all combinations of one or more of the related listed items.

[0021] Embodiment 1 The existing methods for picking arrival times of microseismic waveforms mainly include: calculating each data point in the full waveform based on the Akaike Information Criterion (AIC), obtaining the AIC value corresponding to each data point in the full waveform, and determining the time point corresponding to the data point with the minimum AIC value as the arrival time of the P-wave. After determining the arrival time of the P-wave, the arrival time of the S-wave is determined by any of the following methods: (1) determining the point with the minimum wave signal value or the signal inflection point after the arrival time of the P-wave as the arrival time of the S-wave; (2) for the waveform after the arrival time of the P-wave, recalculating the arrival time of the S-wave using the AIC algorithm; (3) using the Short-Term Average / Long-Term Average (STA / LTA) method to determine the S-wave interval according to a preset threshold, and then determining the point with the minimum AIC value within the S-wave interval as the arrival time of the S-wave. The methods for picking arrival times of microseismic waveforms in the prior art have low picking accuracy, slow calculation speed, and high resource consumption. For this, please refer to Figure 1 In the embodiments of the present application, a method for picking arrival times of microseismic waveforms is provided, including: steps S110 to S180.

[0022] Step S110, obtain full waveform data, where the full waveform data includes: N original data points, and each of the original data points represents the wave signal value at a different time.

[0023] The full waveform data is the waveform of the identified rock fracture signal. Please refer to Figure 2 , Figure 2 FIG. shows an example diagram of the full waveform data. In the figure, the horizontal axis represents the sampling time, and the vertical axis represents the signal amplitude, that is, the wave signal value described below.

[0024] Step S120, determine at least one of the original data points that meet the preset maximum / minimum value condition as a local maximum / minimum point.

[0025] Due to the noise and discreteness in the full waveform data, there are errors in the curve fitted therefrom. Therefore, it is inaccurate to determine the local maximum / minimum point based on the fitted curve by using the derivative method. The local maximum / minimum point is the data point where the peak or trough of the full waveform data is located. It can be understood that the peak is the data point with the largest wave signal value in the local area, and the trough is the data point with the smallest wave signal value in the local area.

[0026] In this embodiment, by comparing the signal value sizes between each original data point and its adjacent data points, the local maximum / minimum point is determined, avoiding the problem of low accuracy caused by the fitting error of the data in the derivative method and improving the determination accuracy of the local maximum / minimum point.

[0027] In one implementation manner, the determining at least one of the original data points that meet the preset maximum / minimum value condition as a local maximum / minimum point includes: If the wave signal value of the $i$-th original data point is greater than the wave signal value of the $(i - 1)$-th original data point and greater than the wave signal value of the $(i + 1)$-th original data point, then the $i$-th original data point is determined as the local extreme value point; Alternatively, if the wave signal value of the $i$-th original data point is less than the wave signal value of the $(i - 1)$-th original data point and less than the wave signal value of the $(i + 1)$-th original data point, then the $i$-th original data point is determined as the local extreme value point, where $1 < i < N$.

[0028] In this embodiment, the local extreme value points include: local maximum value points, and the determination condition is:

[0029] That is, the $i$-th original data point $x[i]$ is greater than its adjacent points $x[i - 1]$ and $x[i + 1]$ on the left and right. Specifically, the derivative is calculated by the first-order difference $diff(x)=x[i + 1]−x[i]$, and the peak value is detected by the sign change:

[0030]

[0031] The local extreme value points also include: local minimum value points, and the determination condition is:

[0032] That is, the $i$-th original data point $x[i]$ is less than its adjacent points $x[i - 1]$ and $x[i + 1]$ on the left and right. Similarly, the derivative is calculated by the first-order difference $diff(x)=x[i + 1]−x[i]$, and the peak value is detected by the sign change:

[0033] .

[0034] Step S130, determine at least one of the local extreme value points that meet the preset screening conditions as the target local extreme value points.

[0035] It can be understood that the local extreme value points are the data points where the wave peaks or wave valleys are located. Please refer to Figure 2 , Figure 2 which also shows multiple local extreme value points.

[0036] In this embodiment, to further reduce the calculation amount and improve the calculation efficiency, further screening is performed on multiple local extreme value points to eliminate the pseudo wave peaks and wave valleys generated by high-frequency noise or redundant fluctuations.

[0037] In one implementation manner, the number of the local extreme value points is $M$ and $M < N$. Please refer toFigure 3 , step S130 includes: steps S131 to S132.

[0038] In step S131, if the time interval between the j-th local extreme point and the (j - 1)-th local extreme point is greater than the minimum waveform period, it is determined that the (j - 1)-th local extreme point and the j-th local extreme point meet the preset screening condition.

[0039] In this embodiment, for the M local extreme points selected from N original data points, based on the physical characteristics of the microseismic signal: the time interval between real wave peaks or wave valleys is usually greater than the minimum period, and the fluctuations smaller than the minimum period may be high-frequency noise or invalid vibrations, the M local extreme points are screened. Specifically, the adjacent local extreme points with a time interval less than the minimum waveform period are screened out.

[0040] In step S132, the (j - 1)-th local extreme point and the j-th local extreme point are respectively determined as the target local extreme points, where 1 < j ≤ M.

[0041] In this embodiment, if the time interval between the j-th local extreme point and the (j - 1)-th local extreme point satisfies being greater than the minimum waveform period, these two points are respectively determined as the target local extreme points. In this way, the screened target local extreme points can effectively exclude high-frequency noise interference, retain the characteristic points reflecting the real rock fracture signal, such as key wave peaks or wave valleys, provide more reliable input for calculating the arrival time of the longitudinal wave and the arrival time of the transverse wave based on the AIC method subsequently, and at the same time reduce the redundant calculation amount and improve the waveform picking efficiency.

[0042] In one embodiment, obtaining the minimum waveform period includes: obtaining the maximum frequency of the full waveform data; determining the minimum waveform period of the full waveform data according to the maximum frequency.

[0043] In this embodiment, obtaining the maximum frequency of the full waveform data , the minimum waveform period .

[0044] In step S140, the AIC value of each target local extreme point is determined based on the Akaike information criterion.

[0045] In this embodiment, by calculating the AIC value of each target local extreme point, the possibility of each target local extreme point as the longitudinal wave is evaluated. Specifically, the calculation formula of the AIC of the k-th target local extreme point is as follows:

[0046]

[0047]

[0048]

[0049]

[0050] Among them, represents the AIC value of the k-th target local extreme point, represents the variance value of the 1st to k - 1st target local extreme points, represents the variance value of the (k + 1)-th to n-th target local extreme points, where n represents the total number of target local extreme points, represents the average value of the 1st to k - 1st target local extreme points, represents the wave signal value of the r-th target local extreme point; represents the average value of the (k + 1)-th to n-th target local extreme points.

[0051] Step S150: Determine the first target extreme point from each of the target local extreme points according to each of the AIC values, and determine the time corresponding to the first target extreme point as the arrival time of the longitudinal wave.

[0052] In this embodiment, the AIC value is used to measure the significance of the waveform change. The smaller the AIC value, the more significant the waveform. Determine the target local extreme point with the most significant waveform change as the first target extreme point, and determine the sampling time corresponding to the first target extreme point as the arrival time of the longitudinal wave.

[0053] In one implementation manner, the determining the first target extreme point from each of the target local extreme points according to each of the AIC values includes: comparing the magnitudes of each of the AIC values, and determining the target local extreme point with the smallest AIC value as the first target extreme point.

[0054] It can be understood that according to the physical propagation law of the microseismic waveform, the arrival time of the longitudinal wave is significantly earlier than that of the transverse wave, and the AIC value of the data point corresponding to the arrival time of the longitudinal wave is smaller than the AIC value of the data point corresponding to the arrival time of the transverse wave. Therefore, by comparing the AIC values of each target local extreme point, the arrival time of the longitudinal wave can be determined first.

[0055] Step S160: Determine the absolute extreme point according to the absolute value of the signal corresponding to each of the original data points, where the absolute value of the signal is the absolute value of the wave signal value corresponding to the original data point.

[0056] In this embodiment, by comparing the absolute values of the signals of all the original data points, the point with the largest absolute value is determined as the absolute extreme value point. The absolute extreme value point reflects the position with the maximum vibration intensity in the waveform. Combining with the propagation laws of the longitudinal wave and the transverse wave, it can be used to determine the arrival time of the transverse wave in the interval between the first target extreme value point and this absolute extreme value point subsequently.

[0057] In one embodiment, determining the absolute extreme value point according to the absolute values of the signals respectively corresponding to each of the original data points includes: determining the original data point with the largest absolute value of the signal as the absolute extreme value point.

[0058] In this embodiment, calculate the absolute values of the wave signal values respectively corresponding to each of the original data points, and determine the original data point with the largest absolute value of the wave signal as the absolute extreme value point. According to the superposition characteristics of the longitudinal wave and the transverse wave, the arrival time of the transverse wave will be in the interval between the absolute extreme value point and the first target extreme value point.

[0059] Step S170, determine the target calculation interval according to the first target extreme value point and the absolute extreme value point.

[0060] Since the propagation speed of the longitudinal wave is faster than that of the transverse wave, and the superposition of the longitudinal wave and the transverse wave will form the maximum value of the waveform, the arrival time of the longitudinal wave must be between the arrival time of the transverse wave and the absolute extreme value point. Therefore, the interval between the first target extreme value point (the arrival time of the longitudinal wave) and the absolute extreme value point is determined as the target calculation interval, which is used to determine the arrival time of the transverse wave subsequently.

[0061] Step S180, determine the second target extreme value point according to the AIC values of each of the target local extreme value points in the target calculation interval, and determine the moment corresponding to the second target extreme value point as the arrival time of the transverse wave.

[0062] In this embodiment, for each of the target local extreme value points in the target calculation interval, collect their AIC values respectively. By comparing the magnitudes of these AIC values, determine the target local extreme value point with the smallest AIC value as the second target extreme value point, and the moment corresponding to this point is the arrival time of the transverse wave.

[0063] It can be understood that according to the physical wave laws of the microseismic waveform, determining the target calculation interval and determining the arrival time of the transverse wave within the target calculation interval greatly reduces the search range of the arrival time of the transverse wave. While reducing the calculation amount, it further improves the accuracy of the picking result.

[0064] In one embodiment, please refer to Figure 4 , determining the second target extreme value point according to the AIC values of each of the target local extreme value points in the target calculation interval includes: steps S181 - S182.

[0065] S181, compare the AIC values of each of the target local extreme value points in the target calculation interval.

[0066] In this embodiment, the arrival time of the shear wave is after the first target extreme value point and before the absolute extreme value point. After the arrival of the shear wave, it will also cause significant fluctuations in the waveform. Therefore, by comparing the AIC values of each target extreme value point within the target calculation interval, the target local extreme value point with the most significant fluctuation within the target calculation interval can be determined.

[0067] S182. Determine the target local extreme value point with the smallest AIC value within the target calculation interval as the second target extreme value point.

[0068] Based on the characteristics of the waveform energy or frequency change when the shear wave arrives, the AIC value of the data point corresponding to the arrival time of the shear wave presents a minimum value within the target local interval, and thus this is used as the basis for judging the arrival time of the shear wave. Please refer to Figure 5 , Figure 5 which shows an example diagram of the waveform picking result provided by the embodiment of the present application.

[0069] To further illustrate the improvement effect of the waveform picking efficiency, please refer to Figure 6 , Figure 6 which shows the comparison of the time required for three different waveform picking methods. Among them, the first picking method is the time required to directly calculate the arrival time of the longitudinal wave using the AIC value, the second picking method is the time required to screen the wave peaks and wave valleys to calculate the arrival time of the longitudinal wave, and the third is the time required for the picking method of the arrival time of the longitudinal wave proposed by the solution of the present application. From the perspective of time, the calculation efficiency of the solution of the present application is improved by more than 8 times, and only 4000 sampling points are calculated. Usually, the acquisition instrument samples 6000 points per second, and the trigger signal is at least 1 s or more. Therefore, for only the longitudinal wave picking, the calculation efficiency is improved by nearly 9 times. And in the subsequent shear wave calculation, a small calculation range is screened, and there is no need to recalculate the wave peaks and wave valleys again, which will reduce more calculation time on the basis of improving the picking accuracy.

[0070] The microseismic waveform arrival time extraction method provided by the embodiment of the present application obtains full waveform data, where the full waveform data includes: N original data points, and each of the original data points represents the wave signal value at different times; determines at least one of the original data points that meets the preset maximum or minimum condition as a local maximum or minimum point; determines at least one of the local maximum or minimum points that meets the preset screening condition as a target local maximum or minimum point; respectively determines the AIC value of each of the target local maximum or minimum points based on the Akaike information criterion; determines a first target maximum or minimum point from each of the target local maximum or minimum points according to each of the AIC values, and determines the time corresponding to the first target maximum or minimum point as the arrival time of the P wave; determines an absolute maximum or minimum point according to the absolute value of the signal corresponding to each of the original data points, where the absolute value of the signal is the absolute value of the wave signal value corresponding to the original data point; determines a target calculation interval according to the first target maximum or minimum point and the absolute maximum or minimum point; determines a second target maximum or minimum point according to the AIC values of each of the target local maximum or minimum points within the target calculation interval, and determines the time corresponding to the second target maximum or minimum point as the arrival time of the S wave, which optimizes the picking process of the arrival time of the P wave and the arrival time of the S wave, and improves the picking efficiency and picking accuracy of the arrival time of the P wave and the arrival time of the S wave.

[0071] Embodiment 2 In addition, please refer to Figure 7 , the embodiment of the present application also provides a microseismic waveform arrival time picking system 700, including: A waveform acquisition module 710, configured to acquire full waveform data, where the full waveform data includes: N original data points, and each of the original data points represents the wave signal value at different times; A first screening module 720, configured to determine at least one of the original data points that meets the preset maximum or minimum condition as a local maximum or minimum point; A second screening module 730, configured to determine at least one of the local maximum or minimum points that meets the preset screening condition as a target local maximum or minimum point; A calculation module 740, configured to respectively determine the AIC value of each of the target local maximum or minimum points based on the Akaike information criterion; A P-wave arrival time determination module 750, configured to determine a first target maximum or minimum point from each of the target local maximum or minimum points according to each of the AIC values, and determine the time corresponding to the first target maximum or minimum point as the arrival time of the P wave; A first determination module 760, configured to determine an absolute maximum or minimum point according to the absolute value of the signal corresponding to each of the original data points, where the absolute value of the signal is the absolute value of the wave signal value corresponding to the original data point; A second determination module 770, configured to determine a target calculation interval according to the first target maximum or minimum point and the absolute maximum or minimum point; The shear wave arrival time determination module 780 is configured to determine a second target extreme value point according to the AIC values of the target local extreme value points within the target calculation interval, and determine the time corresponding to the second target extreme value point as the shear wave arrival time.

[0072] The microseismic waveform arrival time picking system 700 provided by the embodiments of the present invention can execute the microseismic waveform arrival time picking method provided in Embodiment 1 of the above method. To avoid repetition, it will not be elaborated here.

[0073] The microseismic waveform arrival time extraction system provided by the embodiments of the present application obtains full waveform data through a waveform acquisition module. The full waveform data includes: N original data points, and each of the original data points represents a wave signal value at a different time; a first screening module determines at least one of the original data points that meets a preset extreme value condition as a local extreme value point; a second screening module determines at least one of the local extreme value points that meets a preset screening condition as a target local extreme value point; a calculation module respectively determines the AIC values of the target local extreme value points based on the Akaike information criterion; a P-wave arrival time determination module determines a first target extreme value point from the target local extreme value points according to the AIC values, and determines the time corresponding to the first target extreme value point as the P-wave arrival time; a first determination module determines an absolute extreme value point according to the absolute value of the signal corresponding to each of the original data points, where the absolute value of the signal is the absolute value of the wave signal value corresponding to the original data point; a second determination module determines a target calculation interval according to the first target extreme value point and the absolute extreme value point; a shear wave arrival time determination module determines a second target extreme value point according to the AIC values of the target local extreme value points within the target calculation interval, and determines the time corresponding to the second target extreme value point as the shear wave arrival time, which optimizes the picking process of the P-wave arrival time and the shear wave arrival time, and improves the picking efficiency and picking accuracy of the P-wave arrival time and the shear wave arrival time.

[0074] Embodiment ③ In addition, the embodiments of the present invention provide an electronic device, including a memory and a processor. The memory stores a computer program, and when the computer program runs on the processor, it executes the microseismic waveform arrival time picking method provided in Embodiment 1.

[0075] Specifically, please refer to Figure 8, the electronic device 800 includes: a transceiver 801, a bus interface, and a processor 802. The processor 802 is configured to obtain full waveform data, where the full waveform data includes: N original data points, and each of the original data points represents a wave signal value at a different moment; determine at least one of the original data points that meets a preset maximum / minimum condition as a local maximum / minimum point; determine at least one of the local maximum / minimum points that meets a preset screening condition as a target local maximum / minimum point; respectively determine the AIC value of each of the target local maximum / minimum points based on the Akaike information criterion; according to each of the AIC values, determine a first target maximum / minimum point from each of the target local maximum / minimum points, and determine the moment corresponding to the first target maximum / minimum point as the arrival time of the longitudinal wave; determine an absolute maximum / minimum point according to the absolute value of the signal corresponding to each of the original data points, where the absolute value of the signal is the absolute value of the wave signal value corresponding to the original data point; determine a target calculation interval according to the first target maximum / minimum point and the absolute maximum / minimum point; determine a second target maximum / minimum point according to the AIC values of each of the target local maximum / minimum points within the target calculation interval, and determine the moment corresponding to the second target maximum / minimum point as the arrival time of the shear wave.

[0076] In an embodiment of the present invention, the electronic device 800 further includes: a memory 803. In Figure 8 , the bus architecture may include any number of interconnected buses and bridges. Specifically, various circuits of one or more processors represented by the processor 802 and the memory represented by the memory 803 are linked together. The bus architecture may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art. Therefore, they will not be further described herein. The bus interface provides an interface. The transceiver 801 may be multiple components, that is, including a transmitter and a receiver, and provides a unit for communicating with various other devices on a transmission medium. The processor 802 is responsible for managing the bus architecture and general processing, and the memory 803 may store data used by the processor 802 when executing operations.

[0077] The electronic device 800 provided by the embodiment of the present invention can execute the microseismic waveform arrival time picking method provided by the above method embodiment 1. To avoid repetition, it will not be elaborated herein.

[0078] Embodiment 4 In addition, an embodiment of the present invention provides a computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the microseismic waveform arrival time picking method provided by Embodiment 1.

[0079] In this embodiment, the computer-readable storage medium may be a read-only memory (ROM for short), a random access memory (RAM for short), a magnetic disk, an optical disk, or the like.

[0080] The computer-readable storage medium provided in this embodiment can implement the microseismic waveform arrival time picking method provided in Embodiment 1. To avoid repetition, it will not be elaborated here.

[0081] In all the examples shown and described here, any specific value should be construed as merely exemplary and not as a limitation. Therefore, other examples of the exemplary embodiments may have different values.

[0082] It should be noted that like reference numerals and letters denote like items in the following figures. Therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures.

[0083] The above-described embodiments merely represent several implementation manners of the present invention. The description is relatively specific and detailed, but it should not be construed as a limitation on the scope of the present invention. It should be pointed out that for those of ordinary skill in the art, without departing from the concept of the present invention, several modifications and improvements can be made, and these all belong to the protection scope of the present invention.

Claims

1. A method for picking the arrival time of microseismic waveforms, characterized in that The method includes: Obtaining full waveform data, where the full waveform data includes: N original data points, and each of the original data points represents a wave signal value at a different moment; Determining at least one of the original data points that meets a preset maximum / minimum condition as a local maximum / minimum point; Determining at least one of the local maximum / minimum points that meets a preset screening condition as a target local maximum / minimum point; Respectively determining the AIC value of each of the target local maximum / minimum points based on the Akaike information criterion; According to each of the AIC values, determining a first target maximum / minimum point from each of the target local maximum / minimum points, and determining the moment corresponding to the first target maximum / minimum point as the arrival time of the longitudinal wave; Determining an absolute maximum / minimum point according to the absolute value of the signal corresponding to each of the original data points, where the absolute value of the signal is the absolute value of the wave signal value corresponding to the original data point; Determining a target calculation interval according to the first target maximum / minimum point and the absolute maximum / minimum point; According to the AIC values of each of the target local maximum / minimum points within the target calculation interval, determining a second target maximum / minimum point, and determining the moment corresponding to the second target maximum / minimum point as the arrival time of the transverse wave.

2. The microseismic waveform arrival time picking method according to claim 1, characterized in that The determining at least one of the original data points that meets a preset maximum / minimum condition as a local maximum / minimum point includes: If the wave signal value of the i-th original data point is greater than the wave signal value of the (i - 1)-th original data point and greater than the wave signal value of the (i + 1)-th original data point, then determining the i-th original data point as the local maximum / minimum point; Or, if the wave signal value of the i-th original data point is less than the wave signal value of the (i - 1)-th original data point and less than the wave signal value of the (i + 1)-th original data point, then determining the i-th original data point as the local maximum / minimum point, where 1 < i < N.

3. The microseismic waveform arrival time picking method according to claim 2, wherein The number of the local maximum / minimum points is M and M < N. The determining at least one of the local maximum / minimum points that meets a preset screening condition as a target local maximum / minimum point includes: If the time interval between the j-th local maximum / minimum point and the (j - 1)-th local maximum / minimum point is greater than the minimum waveform period, then determining that the (j - 1)-th local maximum / minimum point and the j-th local maximum / minimum point meet the preset screening condition; Respectively determining the (j - 1)-th local maximum / minimum point and the j-th local maximum / minimum point as the target local maximum / minimum points, where 1 < j ≤ M.

4. The microseismic waveform arrival time picking method according to claim 3, characterized in that, Obtaining the minimum waveform period includes: Obtaining the maximum frequency of the full waveform data; Determining the minimum waveform period of the full waveform data according to the maximum frequency.

5. The microseismic waveform arrival time picking method according to claim 1, characterized in that, The determining a first target maximum / minimum point from each of the target local maximum / minimum points according to each of the AIC values includes: Comparing the magnitudes of each of the AIC values, and determining the target local maximum / minimum point with the smallest AIC value as the first target maximum / minimum point.

6. The microseismic waveform arrival time picking method according to claim 1, characterized in that, The determining an absolute maximum / minimum point according to the absolute value of the signal corresponding to each of the original data points includes: Determining the original data point with the largest absolute value of the signal as the absolute maximum / minimum point.

7. The microseismic waveform arrival time picking method according to claim 1, wherein The determining a second target maximum / minimum point according to the AIC values of each of the target local maximum / minimum points within the target calculation interval includes: Comparing the AIC values of each of the target local maximum / minimum points within the target calculation interval; Within the target calculation interval, the target local extreme point with the minimum AIC value is determined as the second target extreme point.

8. A microseismic waveform arrival time picking system, characterized in that, The system includes: A waveform acquisition module for acquiring full waveform data, where the full waveform data includes: N original data points, and each of the original data points represents a wave signal value at a different moment; A first screening module for determining at least one of the original data points that meets a preset extreme value condition as a local extreme point; A second screening module for determining at least one of the local extreme points that meets a preset screening condition as a target local extreme point; A calculation module for respectively determining the AIC value of each of the target local extreme points based on the Akaike information criterion; A P-wave arrival time determination module for determining a first target extreme point from each of the target local extreme points according to each of the AIC values, and determining the moment corresponding to the first target extreme point as the P-wave arrival time; A first determination module for determining an absolute extreme point according to the absolute value of the signal corresponding to each of the original data points, where the absolute value of the signal is the absolute value of the wave signal value corresponding to the original data point; A second determination module for determining a target calculation interval according to the first target extreme point and the absolute extreme point; An S-wave arrival time determination module for determining a second target extreme point according to the AIC values of each of the target local extreme points within the target calculation interval, and determining the moment corresponding to the second target extreme point as the S-wave arrival time.

9. An electronic device, characterized in that, It includes a memory and a processor, where the memory stores a computer program, and when the computer program runs on the processor, it executes the microseismic waveform arrival time picking method according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, it implements the microseismic waveform arrival time picking method according to any one of claims 1-7.

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