Geo-acoustic event location method and instability disaster early warning method based on same, geo-acoustic sensor, monitoring system, and readable storage medium

Patent metadata

Field	Value
Publication number	US-12529812-B2
Application number	US-202218014177-A
Country	US
Kind code	B2
Filing date	Jan 13, 2022
Priority date	Jan 19, 2021
Publication date	Jan 20, 2026
Grant date	Jan 20, 2026

Abstract

Sound signal when a wave generated by a geo-acoustic event source reaches any monitoring point (S1), constructing a theoretical propagation difference model and an observed propagation difference model of the waveform characterization quantity between monitoring points, to calculate a waveform characterization quantity difference value between two monitoring points (S2); and constructing an objective function based on the theoretical propagation difference model and the observed propagation difference model, and obtaining the location of the geo-acoustic event by means of inversion based on the objective function (S3). According to the geo-acoustic event location method, the arrival time, time domain parameters, spectral information, and waveform shape of the geo-acoustic signal when the wave generated by the geo-acoustic event source reaches any monitoring point are considered, then the non-uniformity of a propagation medium is comprehensively reflected, and the inversion precision of geo-acoustic event location is finally improved.

First claim

What is claimed is:

1 . An intelligent geo-acoustic sensor, comprising a geo-acoustic sensing unit, an automatic gain and acoustic-electric conversion unit, an RC filtering network unit, an analog-to-digital conversion unit, an intelligent sensing filter unit and a photoelectric conversion unit, wherein the geo-acoustic sensing unit, the automatic gain and acoustic-electric conversion unit, the RC filtering network unit, the analog-to-digital conversion unit, the intelligent sensing filter unit and the photoelectric conversion unit are connected to each other in a communication mode;
wherein the geo-acoustic sensing unit acquires multi-band geo-acoustic signals;
the automatic gain and acoustic-electric conversion unit is configured for converting a geo-acoustic signal into an analog signal, and performing initial adjustment on the analog signal to realize a fast response of a weak signal gain;
the RC filtering network unit is configured for truncating the analog signal in a frequency domain to complete preliminary filtering;
the analog-to-digital conversion unit is configured for converting the analog signal into a digital signal;
the intelligent sensing filter unit is configured for performing denoising and filtering processing on the digital signal; and
the photoelectric conversion unit is configured for converting the digital signal into an optical signal,
wherein a signal acquired by the intelligent geo-acoustic sensor is used for locating a geo-acoustic event according to steps of a geo-acoustic event location method comprising the following steps:
S1: acquiring an observed value of a waveform characterization quantity of the geo-acoustic event, the waveform characterization quantity comprising: any combination of an arrival time time domain parameters, spectral information, and waveform shape of a geo-acoustic signal when a wave generated by a geo-acoustic event source reaches any monitoring point;
S2: constructing a theoretical propagation difference model and an observed propagation difference model of the waveform characterization quantity between monitoring points, wherein a waveform characterization quantity difference value between two monitoring points is calculated; and
S3: constructing an objective function based on the theoretical propagation difference model and the observed propagation difference model and obtaining a location of the geo-acoustic event by inversion based on the objective function.

2 . The intelligent geo-acoustic sensor according to claim 1 , wherein a metal full-shielding frame is disposed outside the intelligent geo-acoustic sensor.

3 . The intelligent geo-acoustic sensor according to claim 1 , wherein in the geo-acoustic event location method, the objective function is as follows:
G ( x p ,y p ,z p , . . . )=min Σ( DA xyz +DF xyz +DS xyz +DT xyz )
wherein G(x p , y p , z p , . . . ) indicates the objective function of the geo-acoustic event (x p , y p , z p ), x p , y p , z p is a position coordinate of the geo-acoustic event, and DF xyz , DA xyz , DS xyz and DT xyz indicate a degree of deviation of an observed quantity and a theoretical value of a propagation difference of the waveform characterization quantity, respectively.

4 . The intelligent geo-acoustic sensor according to claim 3 , wherein in the geo-acoustic event location method, formulas for calculating DF xyz , DA xyz , DS xyz and DT xyz are respectively as follows:
DT xyz =Σ(Δ t xyz nm −Δt 0 nm ) 2
DA xyz =Σ(Δ A xyz nm −ΔA 0 nm ) 2
DF xyz =Σ(Δ f xyz nm −Δf 0 nm ) 2
DS xyz =Σ(Δ S xyz nm −ΔS 0 nm ) 2
wherein Δt xyz nm and Δt 0 nm respectively indicate a theoretical arrival time difference and an observed quantity of the arrival time difference between two different monitoring points m and n; ΔA xyz nm and ΔA 0 nm respectively indicate a theoretical attenuation difference and an observed value of an attenuation difference of the time domain parameters a 0 between two different monitoring points m and n; Δf xyz nm and Δf 0 nm respectively indicate a theoretical difference value and an observed difference value of the spectral information f between two different monitoring points m and n; and ΔS xyz nm and ΔS 0 nm respectively indicate a theoretical value of a waveform shape evolution difference and an observed value of the waveform shape evolution difference between two different monitoring points m and n.

5 . The intelligent geo-acoustic sensor according to claim 1 , wherein in the geo-acoustic event location method, the time domain parameters comprise any one or any combination of a rise time, a duration, an amplitude and energy time domain parameters of a waveform, and the spectral information is any combination of all frequency information of the waveform after Fourier decomposition; and the waveform shape is a function, wherein the function defines a shape of a geo-acoustic signal waveform in a time domain.

6 . A geo-acoustic event monitoring system, comprising a geo-acoustic signal sensing module, a geo-acoustic event location module and a geo-acoustic event instability disaster early warning module, wherein the geo-acoustic signal sensing module, the geo-acoustic event location module and the geo-acoustic event instability disaster early warning module are connected in a communication mode,
wherein the geo-acoustic signal sensing module is configured for sensing geo-acoustic signals; the geo-acoustic event location module is configured for locating geo-acoustic events by using a geo-acoustic event location method; and the geo-acoustic event instability disaster early warning module is configured for performing instability disaster early warning analysis by using an instability disaster early warning method based on the geo-acoustic event location method, wherein the instability disaster early warning method comprises the following steps:
step 1: forming self-clustering clusters according to a location result of the geo-acoustic event, the self-clustering clusters being obtained by clustering a spatial distribution of the geo-acoustic event;
step 2: counting precursor index information of each of the self-clustering clusters according to a pre-set time window,
wherein the precursor index information is any combination of indexes of a relative energy, a moment magnitude, an apparent volume, b value of each of the self-clustering clusters, a time series change of a rate of geo-acoustic events, a dominant frequency and a corner frequency of the geo-acoustic event in each of the self-clustering clusters; and
if a sum of a category of precursor indexes of all the geo-acoustic events in each of the self-clustering clusters under one time window becomes larger compared with a sum of a same category of precursor indexes under a previous time window, a precursor factor of the corresponding precursor index is 1; and
step 3: performing instability disaster early warning analysis based on precursor factors of precursor indexes of each of the self-clustering clusters, wherein a risk increases as a sum of the precursor factors of all the precursor indexes of each of the self-clustering clusters increases, wherein the geo-acoustic event location method comprising the following steps:
S1: acquiring an observed value of a waveform characterization quantity of the geo-acoustic event, the waveform characterization quantity comprising: any combination of an arrival time time domain parameters, spectral information, and waveform shape of a geo-acoustic signal when a wave generated by a geo-acoustic event source reaches any monitoring point; S2: constructing a theoretical propagation difference model and an observed propagation difference model of the w

Assignees

• Univ Central South

Inventors

• Dong Longjun
• Zhang Yihan

Classifications

• G01V2210/65

  Source localisation, e.g. faults, hypocenters or reservoirs · CPC title

• G01V2210/123

  Passive source, e.g. microseismics · CPC title

• G01V1/288 Primary

  Event detection in seismic signals, e.g. microseismics (G01V1/36 takes precedence) · CPC title

• G01V1/307 Primary

  for determining seismic attributes, e.g. amplitude, instantaneous phase or frequency, reflection strength or polarity · CPC title

• Y02D30/70

  in wireless communication networks · CPC title