Abstract
The denoising for the microseismic signals in the strong background interferences during the microseismic monitoring of hydraulic fracturing is very important for events identification and first-arrival picking. As characteristics of microseismic signals are normally random, non-stationary, and time-varying, a powerful tool for weak signal extraction of microseismic data is still a great challenge. In this study, a denoising method for microseismic signals is proposed based on the synchrosqueezing transform in the time-frequency domain. Firstly, the microseismic signals are denoised by the adaptive threshold method in the time-frequency domain by the synchrosqueezing transform. Then, the frequency center of the effective signal is integrated and extracted in the time-frequency domain. At last, the weak signal is extracted by the reconstruction of synchrosqueezing transform. The results from the synthesized non-stationary signal with different noise intensities and the real microseismic single of a track record show that this method has better anti-noise ability and higher signal extraction accuracy. Moreover, according to the processing and analysis of microseismic data in field wells, it is proved that this denoising method has a good practical value and can extract the effective and high-precision signals in the strong noise background.
Published Version
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