Micro-seismic wave signal first arrival time automatic pickup method and micro-seismic monitoring device

Abstract

The invention provides a micro-seismic wave signal first arrival time automatic picking method and a micro-seismic monitoring device. The micro-seismic wave first arrival time picking precision and the data processing efficiency are improved. The method comprises the following steps: step 1, reconstructing a micro-seismic signal: preprocessing a loaded micro-seismic signal by using band-pass filtering, intercepting a micro-seismic effective signal, and carrying out noise reduction processing in combination with Gaussian noise to form a new signal; step 2, establishing a relative energy adaptive characteristic function, introducing a relative energy coefficient alpha to establish a relative energy adaptive characteristic function ACF based on an Allen envelope function, solving the ACF for a new loaded signal, and performing data normalization; step 3, determining micro-seismic P wave duration L0; and step 4, determining accurate first arrival time pickup time: based on the duration L0, taking the length capable of containing the microseismic waveform as the time window length of the AIC pickup method, determining an AIC curve, and searching the minimum value of a local window of the AIC curve, namely the accurate microseismic wave first arrival time pickup time.

Description

technical field [0001] The invention belongs to the technical field of microseismic monitoring, and in particular relates to a method for automatically picking up a microseismic wave signal when it first arrives and a microseismic monitoring device. Background technique [0002] In recent years, with the increase of mining depth and mining intensity, it is very easy to induce serious geological disasters such as mine earthquakes, rockbursts, and roof collapses, which pose a serious threat to people's lives and property safety. Microseismic monitoring technology can play a good early warning role in the monitoring of microseismic activities in mines. The identification of microseismic events and the picking up of the first arrival of p-waves are the basis of microseismic data, which directly affects the analysis, positioning and prediction of the source of the earthquake. Microseismic P-wave The picking accuracy of the first arrival directly affects the effect of monitoring a...

AI Technical Summary

Problems solved by technology

The STA / LTA method is simple and quick to calculate, but due to the difference in feature function selection and the empirical setting of the initial threshold value, there is a large error in the arrival time of the STA / LTA method, and it is difficult to pick up the accurate initial arrival time.

The AIC method has the characteristics of quickness and intuition in picking up the microseismic arrival time, but because of the difficulty in determining the position and length of the time window, it is not suitable for continuous seismic record sliding analysis, which limits its application in engineering

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