利用同步挤压变换检测微地震信号

new time-frequency tool called the synchrosqueezing wavelet transform (SWT) was used to detecting microseismic events 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. Consequently, 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.