Abstract: Time picking is a crucial step in microseismic data processing，the picking results have great influence on hypocenter location． Especially when the SNＲ ( Signal-To-Noise Ｒatio) is low，it is difficult to obtain arrival times accurately with conventional approaches． We propose a new time picking approach based on the AIC( Akaike Information Criterion) and Shearlet transform named the Shearlet-AIC to solve the problems mentioned above． We divide microseismic data into several scales according to different statistical characteristic between signals and noise to obtain the feature of different frequency domain． We can acquire the minimum values that represent the picking results of frequency domain by using the Shearlet-AIC． To verify the reliability of the method，we experiment it on both synthetic and field datasets． The results show that our method can precisely pick the arrival times even when the SNＲ of data is as low as -13dB and the accuracy is superior to some existing method．

Key words: arrival time picking, automatic picking, akaike information criterion ( AIC), microseismicity, Shearlet transform