Microseismic events enhancement in sensor arrays using autocorrelation based filtering


Passive microseismic data are commonly buried in noise, which presents a significant challenge in microseismic data analysis and event detection. In this work, we consider the situation where a sensor array provides multiple traces that each contain an arrival from the event, and propose an autocorrelation-based method that designs a denoising filter in the frequency domain to facilitate the following microseismic applications. This approach uses stacking of the autocorrelation functions, which works well because the autocorrelations of all the traces are centered at zero in the lag domain. Thus, it does not suffer the usual drawback of stacking where the time off sets among traces must be known. The simplicity and robustness of this method is validated with numerical simulations.