The phase identification and travel time picking are critical for seismic tomography,yet it will be challenging when the numbers of stations and earthquakes are huge.We here present a method to quickly obtain P and S ...The phase identification and travel time picking are critical for seismic tomography,yet it will be challenging when the numbers of stations and earthquakes are huge.We here present a method to quickly obtain P and S travel times of pre-determined earthquakes from mobile dense array with the aid from long term phase records from co-located permanent stations.The records for 1768 M≥2.0 events from 2011 to 2013 recorded by 350 ChinArray stations deployed in Yunnan Province are processed with an improved AR-AIC method utilizing cumulative envelope and rectilinearity.The reference arrivals are predicted based on phase records from 88 permanent stations with similar spatial coverage,which are further refined with AR-AIC.Totally,718573 P picks and 512035 S picks are obtained from mobile stations,which are 28 and 22 times of those from permanent stations,respectively.By comparing the automatic picks with manual picks from 88 permanent stations,for M≥3.0 events,81.5%of the P-pick errors are smaller than 0.5 second and 70.5%of S-pick errors are smaller than1 second.For events with a lower magnitude,76.5%P-pick errors fall into 0.5 second and 69.5%S-pick errors are smaller than 1 second.Moreover,the Pn and Sn phases are easily discriminated from directly P/S,indicating the necessity of combining traditional auto picking and integrating machine learning method.展开更多
基金This project is supported by the National Key Research and Development Program of China(2018YFC1503200)the Fundamental Research Funds for the Institute of Geophysics of China Earthquake Administration(DQJB19B29)+1 种基金the National Natural Science Foundation of China(41790463)the Science and Technology Projects of Zhejiang Earthquake Agency(2019zjj05)。
文摘The phase identification and travel time picking are critical for seismic tomography,yet it will be challenging when the numbers of stations and earthquakes are huge.We here present a method to quickly obtain P and S travel times of pre-determined earthquakes from mobile dense array with the aid from long term phase records from co-located permanent stations.The records for 1768 M≥2.0 events from 2011 to 2013 recorded by 350 ChinArray stations deployed in Yunnan Province are processed with an improved AR-AIC method utilizing cumulative envelope and rectilinearity.The reference arrivals are predicted based on phase records from 88 permanent stations with similar spatial coverage,which are further refined with AR-AIC.Totally,718573 P picks and 512035 S picks are obtained from mobile stations,which are 28 and 22 times of those from permanent stations,respectively.By comparing the automatic picks with manual picks from 88 permanent stations,for M≥3.0 events,81.5%of the P-pick errors are smaller than 0.5 second and 70.5%of S-pick errors are smaller than1 second.For events with a lower magnitude,76.5%P-pick errors fall into 0.5 second and 69.5%S-pick errors are smaller than 1 second.Moreover,the Pn and Sn phases are easily discriminated from directly P/S,indicating the necessity of combining traditional auto picking and integrating machine learning method.
