A method for extracting seismic signal features

Abstract

The present application provides a method for extracting seismic signal features, which relates to the field of seismic signal processing. The method includes obtaining a seismic signal, performing source location based on the seismic signal to determine multiple stations that receive the seismic signal, determining the component information of the seismic signals received by each station, dividing the seismic signals received by each station based on the component information of the seismic signals received by each station, the first preset velocity interval, and the second preset velocity interval, performing Fourier transform on the divided seismic signals to obtain a first amplitude-frequency curve and a second amplitude-frequency curve, and obtaining a ratio eigenvalue based on the first amplitude-frequency curve and the second amplitude-frequency curve. In this way, the signal-to-noise ratio of the seismic signal can be improved by principal component extraction, and the seismic signal can be identified by extracting the ratio eigenvalue of the seismic signal with the improved signal-to-noise ratio, so that the feature extraction effect of the seismic signal with low signal-to-noise ratio can be improved, and the identification effect of the seismic signal can be improved.

Description

Technical Field

[0001] The present invention belongs to the field of seismic signal processing and relates to a method for extracting seismic signal features. Background Art

[0002] Since the 1950s, people have started to identify seismic and artificial blasting signals. Compared with seismic signals, artificial blasting signals have characteristics such as weak energy and susceptibility to interference, resulting in complex signal waveforms and unclear seismic phases. Currently, the time-domain characteristics of earthquakes are usually obtained through P / S spectral ratio feature extraction. For example, the amplitude ratio of P wave to S wave, the ratio of the initial motion amplitude of P wave to the maximum displacement amplitude of P wave, and the initial motion of P wave. Then, the time-domain characteristics are composed into feature vectors, placed in a hyperplane or a feature space, and classified and recognized by a classifier.

[0003] However, the P / S spectral ratio feature extraction method has a poor effect on the feature extraction of seismic signals with low signal-to-noise ratio. As such, the recognition effect of seismic signals will be poor. Summary of the Invention

[0004] The present invention proposes a method for extracting seismic signal features, which can determine the component information of seismic signals through principal component extraction to improve the signal-to-noise ratio of seismic signals. Then, by extracting the waveform feature values of the seismic signals with improved signal-to-noise ratio, the seismic signals are recognized. In this way, the feature extraction effect of low signal-to-noise ratio seismic signals can be improved, and the recognition effect of seismic signals can be improved.

[0005] A method for extracting seismic signal features includes:

[0006] Obtain a seismic signal, and perform seismic source location based on the seismic signal to determine multiple stations that receive the seismic signal;

[0007] Determine the component information of the seismic signal received by each station;

[0008] Based on the component information of the seismic signal received by each station, as well as a first preset speed interval and a second preset speed interval, divide the seismic signal received by each station;

[0009] Perform Fourier transform on the divided seismic signal to obtain a first amplitude-frequency curve and a second amplitude-frequency curve;

[0010] Based on the first amplitude-frequency curve and the second amplitude-frequency curve, obtain a ratio feature value.

[0011] In the above solution, the performing seismic source location based on the seismic signal to determine multiple stations that receive the seismic signal includes:

[0012] Locate the earthquake source according to the shear waves and compressional waves in the earthquake signal, and determine the multiple stations that receive the earthquake signal.

[0013] In the above solution, the multiple stations that receive the earthquake signal are determined by the following formula:

[0014] [ x 1 − x 2 y 1 − y 2 z 1 − z 2 x 1 − x 3 y 1 − y 3 z 1 − z 3 ⋮ ⋮ ⋮ ] [ x 0 y 0 z 0 ] = [ 1 2 ( r 1 2 − r 2 2 + R 2 2 − R 1 2 ) 1 2 ( r 1 2 − r 3 2 + R 3 2 − R 1 2 ) ⋮ ]

[0015] Wherein, is the source coordinate of the earthquake signal; is the coordinate of station , ; , is the radius of the earthquake signal received by station ; , is the diameter of the earthquake signal received by station .

[0016] In the above solution, the determining of the component information of the earthquake signal received by each station includes:

[0017] Based on the earthquake signals received by each station, determine the data matrix corresponding to the earthquake signals received by each station;

[0018] Filter the data matrix corresponding to the earthquake signals received by each station to obtain a filtered data matrix;

[0019] Extract the principal components of the filtered data matrix to determine the component information corresponding to the earthquake signals received by each station.

[0020] In the above solution, the principal component extraction of the filtered data matrix can be performed by the following formula:

[0021] { w ( t + 1 ) = w ( t ) + η [ z ( t ) y ( t ) − z 2 ( t ) w ( t ) ] z ( t ) = y ( t ) w T ( t )

[0022] Wherein, represents the weight value of the earthquake signal at time, represents the signal vector of the earthquake signal at time, represents the component information at time, is a preset learning factor.

[0023] In the above solution, the obtaining of the ratio eigenvalue based on the first amplitude-frequency curve and the second amplitude-frequency curve includes:

[0024] Filter the first amplitude-frequency curve and the second amplitude-frequency curve through a median filter to obtain a filtered first amplitude-frequency curve and a filtered second amplitude-frequency curve;

[0025] Based on the first amplitude-frequency value at a first preset frequency point in the filtered first amplitude-frequency curve and the second amplitude-frequency value at a second preset frequency point in the filtered second amplitude-frequency curve, obtain the ratio eigenvalue.

[0026] In the above solution, the ratio eigenvalue is obtained through the following formula:

[0027]

[0028] where, represents the amplitude-frequency value of the first amplitude-frequency curve, represents the amplitude-frequency value of the second amplitude-frequency curve.

[0029] In the above solution, the seismic signal includes an east-west direction seismic signal, a north-south direction seismic signal, and a vertical direction seismic signal.

[0030] An embodiment of the present application provides a method for extracting seismic signal features, including obtaining a seismic signal, performing seismic source positioning according to the seismic signal, and determining a plurality of stations that receive the seismic signal; determining the component information of the seismic signal received by each station; based on the component information of the seismic signal received by each station, and a first preset speed interval and a second preset speed interval, dividing the seismic signal received by each station; performing Fourier transform on the divided seismic signal to obtain a first amplitude-frequency curve and a second amplitude-frequency curve; based on the first amplitude-frequency curve and the second amplitude-frequency curve, obtaining a ratio eigenvalue; being able to determine the component information of the seismic signal through principal component extraction to improve the signal-to-noise ratio of the seismic signal; then, by extracting the waveform eigenvalue (ratio eigenvalue) of the seismic signal with an improved signal-to-noise ratio, identifying the seismic signal; in this way, the feature extraction effect of low signal-to-noise ratio seismic signals can be improved, and the identification effect of seismic signals can be improved. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following will briefly introduce the drawings required for the description of the embodiments. Obviously, the following drawings are some embodiments of the present application. For those of ordinary skill in the art, without creative efforts, other drawings can also be obtained based on these drawings.

[0032] Figure 1 It is one of the flowcharts of a method for extracting seismic signal features provided by an embodiment of the present application;

[0033] Figure 2Flowchart Two of a Method for Extracting Seismic Signal Features Provided by an Embodiment of This Application;

[0034] Figure 3 Flowchart Three of a Method for Extracting Seismic Signal Features Provided by an Embodiment of This Application;

[0035] Figure 4 Flowchart Four of a Method for Extracting Seismic Signal Features Provided by an Embodiment of This Application. Detailed Implementation Manner

[0036] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions in the embodiments of this application will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of this application. Obviously, the described embodiments are some, but not all, of the embodiments of this application. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in this application without making creative efforts fall within the scope of protection of this application.

[0037] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the technical field to which this application belongs; the terms used in the specification of this application are only for the purpose of describing specific embodiments and are not intended to limit this application; the terms "including" and "having" and any variations thereof in the specification, claims, and drawings of this application are intended to cover non-exclusive inclusion.

[0038] Referring to "embodiment" herein means that a specific feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of this application. The phrase "embodiment" appearing in various positions in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment mutually exclusive with other embodiments. Those skilled in the art explicitly and implicitly understand that the embodiments described herein can be combined with other embodiments.

[0039] The term "and / or" herein is merely a description of the association relationship of associated objects, indicating that three relationships can exist. For example, A and / or B can represent: the existence of A, the simultaneous existence of A and B, and the existence of B. In addition, the character " / " herein generally represents an "or" relationship between the associated objects before and after.

[0040] In addition, the terms "first", "second", etc. in the specification, claims, or the above-mentioned drawings of this application are used to distinguish different objects and are not used to describe a specific order, and may explicitly or implicitly include one or more of such features.

[0041] In the description of the present application, unless otherwise specified, "a plurality of" means two or more (including two). Similarly, "a plurality of groups" means two or more groups (including two groups).

[0042] To enable those skilled in the art to better understand the solution of the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings.

[0043] As Figure 1 shown, an embodiment of the present application provides a method for extracting seismic signal features, including:

[0044] S101. Obtain a seismic signal, and perform earthquake source location based on the seismic signal to determine a plurality of stations that receive the seismic signal.

[0045] In some embodiments, the seismic signal includes an east-west direction seismic signal, a north-south direction seismic signal, and a vertical direction seismic signal; that is, the seismic signal represents real-time seismic waveform data with three components, and the three components correspond to the three directions of east-west, north-south, and vertical respectively.

[0046] In some embodiments, earthquake source location is performed based on the shear wave and longitudinal wave in the seismic signal to determine a plurality of stations that receive the seismic signal.

[0047] In some embodiments, a plurality of stations that receive the seismic signal are determined by the following formula 1-1:

[0048] [ x 1 − x 2 y 1 − y 2 z 1 − z 2 x 1 − x 3 y 1 − y 3 z 1 − z 3 ⋮ ⋮ ⋮ ] [ x 0 y 0 z 0 ] = [ 1 2 ( r 1 2 − r 2 2 + R 2 2 − R 1 2 ) 1 2 ( r 1 2 − r 3 2 + R 3 2 − R 1 2 ) ⋮ ] 1-1

[0049] Wherein, is the earthquake source coordinate of the seismic signal; is the coordinate of station , ; , is the radius of the seismic signal received by station ; , is the diameter of the seismic signal received by station .

[0050] Exemplarily, assume that the earthquake source coordinate is , the earthquake occurrence time is , and the coordinate of station is , where . The arrival time of the longitudinal wave (P wave) in the seismic signal is , and the arrival time of the shear wave (S wave) in the seismic signal is . At this time, based on formula 1-2, and the arrival time of the P wave and the arrival time , it is possible to determine the diameter of the seismic signal.

[0051] 1-2

[0052] Among them, is the velocity of the S-wave in the seismic signal, is the velocity of the P-wave in the seismic signal.

[0053] Based on Equation 1-2, Equation 1-3 can be obtained:

[0054] 1-3

[0055] Among them, is the velocity of the seismic signal.

[0056] Based on Equation 1-3, Equation 1-4 can be obtained:

[0057] 1-4

[0058] Based on Equations 1-2 to 1-4, subtracting the equations corresponding to different stations can obtain a linear equation, that is, Equation 1-1. Based on Equation 1-1, the stations receiving the seismic signal can be determined, and thus multiple stations can be determined.

[0059] Among them, . Solving the above equation can obtain the source location.

[0060] In some embodiments, the origin time can be determined by Equation 1-5 , and Equation 1-5 is as follows:

[0061] 1-5

[0062] S102. Determine the component information of the seismic signals received by each station.

[0063] For example, Figure 2 as shown, in some embodiments, S102 may include:

[0064] S1021. Based on the seismic signals received by each station, determine the data matrix corresponding to the seismic signals received by each station.

[0065] Exemplarily, let the data matrix corresponding to the seismic signal be , as follows:

[0066] X = A + W = [ x 1 , x 2 , x 3 ] ∈ R M × 3

[0067] Among them, Represents the east-west seismic signal (east-west waveform data), Represents the east-west seismic signal (north-south waveform data), Represents the vertical seismic signal (vertical waveform data). Represents the signal matrix, Represents the noise matrix, Represents the signal duration.

[0068] Component, reducing the influence of noise on subsequent endpoint discrimination and improving the detection accuracy of micro-seismic signals.

[0069] S1022. Filter the data matrix corresponding to the seismic signals received by each station to obtain the filtered data matrix.

[0070] In some embodiments, since there is inevitably noise in the actual data matrix, therefore, filter the data matrix corresponding to the seismic signals received by each station to obtain the filtered data matrix.

[0071] Exemplarily, filter the data matrix corresponding to the seismic signals received by each station through a high-pass filter to obtain the filtered data matrix .

[0072] It can be understood that by performing high-pass filtering on the initial three-component seismic signal through a high-pass filter, the influence of low-frequency pulsating noise and DC components in the east-west seismic signal, north-south seismic signal, and vertical seismic signal can be eliminated; that is, the influence of low-frequency pulsating noise and DC components in the seismic signal on the seismic signal is eliminated.

[0073] S1023. Perform principal component extraction on the filtered data matrix to determine the component information corresponding to the seismic signal.

[0074] In some embodiments, perform principal component extraction on the filtered data matrix through a preset neural network.

[0075] In some embodiments, the principal component extraction of the filtered data matrix can be performed through Formula 1-6:

[0076] { w ( t + 1 ) = w ( t ) + η [ z ( t ) y ( t ) − z 2 ( t ) w ( t ) ] z ( t ) = y ( t ) w T ( t ) 1-6

[0077] Wherein, Represents The weight value of the seismic signal at time ; Represents The signal vector of the seismic signal at time ; Represents The component information at time is a preset learning factor.

[0078] S103. Divide the seismic signals received by each station based on the component information of the seismic signals received by each station, as well as the first preset velocity range and the second preset velocity range.

[0079] In some embodiments, the seismic signals received by each station are divided based on the component information of the seismic signals received by each station, as well as the first preset velocity range and the second preset velocity range, to obtain a first signal and a second signal.

[0080] Exemplarily, the first signal is the longitudinal wave signal (P-wave signal) in the seismic signal, and the second signal is the transverse wave signal (S-wave signal) in the seismic signal.

[0081] In some embodiments, the first preset velocity range is the velocity range of the transverse wave of the seismic signal, and the second preset velocity range is the velocity range of the longitudinal wave of the seismic signal.

[0082] Exemplarily, let the first preset velocity range (P-wave velocity range) be [ v P 1 , v P 2 ] , and the second preset velocity range (S-wave velocity range) be [ v S 1 , v S 2 ] ; based on the P-wave velocity range, the start and stop times of the P-wave can be determined based on Formula 1-7 and Formula 1-8, and Formula 1-7 and Formula 1-8 are shown as follows:

[0083] 1-7

[0084] 1-8

[0085] Wherein, is the start time of the P-wave in the seismic signal; is the stop time of the P-wave in the seismic signal.

[0086] Based on the S-wave velocity range, the start and stop times of the S-wave can be determined based on Formula 1-9 and Formula 1-10, and Formula 1-9 and Formula 1-10 are shown as follows:

[0087] 1-9

[0088] 1-10

[0089] Wherein, is the start time of the S-wave in the seismic signal; is the stop time of the S-wave in the seismic signal.

[0090] After that, let be the For the principal component signals corresponding to each station, based on the start and end times of the P wave, the P wave signal of the th station can be determined as:

[0091]

[0092] Based on the start and end times of the S wave, the S wave signal of the th station can be determined as:

[0093]

[0094] S104. Perform Fourier transform on the divided seismic signals to obtain a first amplitude-frequency curve and a second amplitude-frequency curve.

[0095] In some embodiments, perform Fourier transform on the first signal and the second signal obtained after division to obtain a first amplitude-frequency curve and a second amplitude-frequency curve.

[0096] Exemplarily, perform Fourier transform on the P wave signals and S wave signals of each station respectively, so as to obtain a first amplitude-frequency curve (the amplitude-frequency value of the P wave signal ) and a second amplitude-frequency curve (the amplitude-frequency value of the S wave signal ). Among them, 50-point Fourier transform can be performed on the P wave signals and S wave signals of each station respectively.

[0097] S105. Based on the first amplitude-frequency curve and the second amplitude-frequency curve, obtain a ratio eigenvalue.

[0098] As Figure 3 shown, in some embodiments, S105 may include:

[0099] S1051. Filter the first amplitude-frequency curve and the first amplitude-frequency curve through a median filter to obtain a filtered first amplitude-frequency curve and a filtered second amplitude-frequency curve.

[0100] S1052. Based on the first amplitude-frequency value of the first preset frequency point in the filtered first amplitude-frequency curve and the second amplitude-frequency value of the second preset frequency point in the filtered second amplitude-frequency curve, obtain a ratio eigenvalue.

[0101] In some embodiments, the ratio eigenvalue is obtained through formula 1-11, and formula 1-11 is as follows:

[0102] 1-11

[0103] Wherein, represents the amplitude-frequency value of the first amplitude-frequency curve, represents the amplitude-frequency value of the second amplitude-frequency curve.

[0104] As Figure 4As shown, in some embodiments, the embodiments of the present application further provide a method for extracting seismic signal features, including:

[0105] S201. Perform seismic source location based on the received seismic signals to determine multiple stations that receive the seismic signals.

[0106] S202. Preprocess the P-waves (longitudinal waves in seismic signals) and S-waves (transverse waves in seismic signals) received by each station respectively, and extract the principal components.

[0107] S203. According to the P-wave velocity interval (the first preset velocity interval) and the S-wave velocity interval (the second preset velocity interval), divide the seismic signals received by each station into two interval segments and perform Fourier transform to obtain the first amplitude-frequency curve and the second amplitude-frequency curve.

[0108] S204. Use a median filter to filter the first amplitude-frequency curve and the second amplitude-frequency curve to obtain ratio eigenvalues.

[0109] As described above, the above are only the preferred specific embodiments of the present invention, and the protection scope of the present invention is not limited thereto. Within the scope of the technical concept of the present disclosure, various simple modifications can be made to the technical solutions of the present disclosure, and these simple modifications all belong to the protection scope of the present disclosure.

Claims

1. A method for extracting seismic signal features, characterized in that Including: Obtain seismic signals, perform source location based on the seismic signals, and determine multiple stations that receive the seismic signals; Determine the component information of the seismic signals received by each station; Based on the component information of the seismic signals received by each station, as well as the first preset velocity range and the second preset velocity range, divide the seismic signals received by each station; Perform Fourier transform on the divided seismic signals to obtain a first amplitude-frequency curve and a second amplitude-frequency curve; Based on the first amplitude-frequency curve and the second amplitude-frequency curve, obtain a ratio eigenvalue; Wherein, the ratio eigenvalue is obtained through the following formula: ； Among them, represents the amplitude-frequency value of the first amplitude-frequency curve, represents the amplitude-frequency value of the second amplitude-frequency curve.

2. The method for extracting seismic signal features according to claim 1, wherein The performing source location based on the seismic signals and determining multiple stations that receive the seismic signals includes: Perform source location based on the shear wave and longitudinal wave in the seismic signals to determine the multiple stations that receive the seismic signals.

3. A method for extracting seismic signal characteristics according to claim 1, characterized in that, The multiple stations that receive the seismic signals are determined through the following formula: ； Among them, is the source coordinate of the seismic signal; is the coordinate of the station ; ; , is the radius of the seismic signal received by the station ; , is the diameter of the seismic signal received by the station .

4. A method for extracting seismic signal characteristics according to claim 1, characterized in that, The determining the component information of the seismic signals received by each station includes: Based on the seismic signals received by each station, determine the data matrix corresponding to the seismic signals received by each station; Filter the data matrix corresponding to the seismic signals received by each station to obtain a filtered data matrix; Perform principal component extraction on the filtered data matrix to determine the component information corresponding to the seismic signals received by each station.

5. A method for extracting seismic signal features according to claim 4, characterized in that The principal component extraction of the filtered data matrix can be performed through the following formula: ； Among them, represents the weight value of the seismic signal at time represents the signal vector of the seismic signal at time represents the component information at time is a preset learning factor.

6. A method for extracting seismic signal characteristics according to claim 1, characterized in that, The obtaining the ratio eigenvalue based on the first amplitude-frequency curve and the second amplitude-frequency curve includes: Filter the first amplitude-frequency curve and the first amplitude-frequency curve through a median filter to obtain a filtered first amplitude-frequency curve and a filtered second amplitude-frequency curve; Based on the first amplitude-frequency value at the first preset frequency point in the filtered first amplitude-frequency curve and the second amplitude-frequency value at the second preset frequency point in the filtered second amplitude-frequency curve, obtain the ratio eigenvalue.

7. A method for extracting seismic signal features according to any one of claims 1-6, characterized in that, The seismic signals include east-west direction seismic signals, north-south direction seismic signals, and vertical direction seismic signals.

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