利用同步挤压变换检测微地震信号

摘要

A new time-frequency tool called the synchrosqueezing wavelet transform(SWT)was used to detecting microseismic e-vents with a low signal-to-noise ratio.The results seemed to suggest that the SWT had high temporal and spatial resolution which enabled it to transform the microsesimic data from the time domain to the time-frequency spectrum with high resolution.Conse-quently,it gave an excellent time-frequency data distribution.In this study,a 2D time-frequency filter was used to “de-noise”and retain the microseismic events on the time-frequency spectrum.Then the microseismic waveforms from the filtered results were estimated using the inverse SWT.At the same time,the microseismic first arrival times were estimated according to the variation of the time-frequency spectrum of the monitoring data.The SWT was applied during the hydro-fracturing process in an oil well, and the results seemed to indicate that the SWT can detect microseismic events.This method seemed superior to the S-transform and band-pass filtering.%针对低信噪比微地震监测资料识别和检测微地震事件的难题，利用同步挤压小波变换（SWT）对微地震监测资料进行处理。结果表明，同步挤压小波变换具有较高的时间和频率分辨率，可将时域微震监测信号转化成高分辨率的时频谱，精细刻画了微地震监测信号的时频特征。分析微地震信号和噪声的时频特征，设计二维时频域滤波器，在时频域进行滤波，去除噪声，保留微地震信号时频谱，然后对滤波结果进行同步挤压小波反变换，恢复微地震波形，从而实现对微震事件的检测；同时，利用微地震信号的时频分布变化特征确定微地震到达时间。利用同步挤压小波变换对模拟信号和实测油田压裂微震资料的微地震信号进行检测，结果表明，同步挤压变换具有较好的应用效果，且优于 S 变换和带通滤波。