Arrival time picking for microseismic signals is an essential step in microseismic data processing. The conventional methods for arrival time picking are biased for the seimic signal with high signal-to-noise ratio (SNR), but the SNR of the microseismic signal is low and the noises can submerge the valid signals, so it is difficult to obtain arrival time of microseismic signals accurately by conventional methods. In order to improve the accuracy of the arrival time picking for microseismic signals, we propose a new arrival time algorithm based on the shearlet transform and the ratio of short time window kurtosis and long time window kurtosis (S-STK/LTK). In this algorithm, the valid signals are highlighted by the multi-scale and multi-direction of the shearlet transform, we introduce sliding long and short time windows into the PAI-S/K algorithm (kurtosis and skewness algorithm) and propose a brand new weighting factor. In order to verify the reliability of the S-STK/LTK algorithm, we conduct numerous tests including synthetic microseismic data and field microseismic data. The results illustrate that the S-STK/LTK algorithm can pick the arrival time for microseismic signals accurately when SNR is very low. For instance, the accuracy of our algorithm is still up to 91% when the SNR of data is as low as ?7 dB. Furthermore, comparison with conventional methods shows that our algorithm outperforms the conventional methods in arrival time picking for microseismic signals.
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