Abstract
We propose a new iterative workflow based on cross-correlation for improved arrival-time picking on microseismic data. In this workflow, signal-to-noise ratio (S/N) and polarity weighted stacking are used to minimize the effect of S/N and polarity fluctuations on the pilot waveform computation. We use an exhaustive search technique for polarity estimation through stack power maximization. We use pseudo-synthetic and real microseismic data from western Canada in order to demonstrate the effectiveness of proposed workflow relative to Akaike information criterion (AIC) and a previously published cross-correlation based method. The pseudo-synthetic microseismic waveforms are obtained by introducing Gaussian noise and polarity fluctuations into waveforms from a high S/N microseismic event. We find that the cross-correlation based approaches yield more accurate arrival-time picks as compared to AIC for low S/N waveforms. AIC is not affected by waveform polarities as it works on individual receiver levels whereas the accuracy of existing cross-correlation method decreases in spite of using envelope correlation. We show that our proposed workflow yields better and consistent arrival-time picks regardless of waveform amplitude and polarity variations within the receiver array. After refinement, the initial arrival-time picks are located closer to the best estimated manual picks.
Published Version
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