Abstract
Cross-correlation based techniques are widely used for time-delay estimation in electrical engineering and in the processing of passive and active seismic data. We present an iterative cross-correlation based workflow to refine arrival time picks on microseismic data that were initially picked either manually or using a single-trace based algorithm such as short and long-term average ratio (STA/LTA). We then evaluate the performance of this workflow on both synthetic and real microseismic data using a Monte Carlo approach. A significant improvement in the arrival-time picks is observed for both high and low S/N. Accurate arrival times are picked, even for cases where the initial picks are perturbed by adding significant noise. For the cases considered here, an arrival-time accuracy of ±2-4 samples (±0.5 – 1ms) is achieved for both synthetic and real microseismic data.
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