A novel technique for automatic seismic data processing using both integral and local features of seismograms

Reliable automation of data processing is of great significance for modern seismic monitoring. A novel technique for automatic seismic data processing which utilizes both integral and local features of seismograms was presented in this paper. However, unlike some previous efforts which seek to use envelope cross-correlation to detect seismic events directly, our technique keeps to follow the DIAL approach, i.e., by steps of signal detection, phase identification, association and event localization. However, in addition to detect signals corresponding to individual seismic phases, the new technique also detects continuous wave-trains and explores their envelope features for phase type identification and signal association. More concrete ideas about how to define wave-trains and combine them with various detections as well as how to measure and utilize their features in the seismic data processing were expatiated in the paper. This approach has been applied to the routine data processing of regional seismic networks for several years, and as an application example, here were presented test results for a 16 days' period using data from the Xinjiang regional seismic network. Practical application results show that the new technique can reduce both false alarm and missed event rate significantly and has good application prospects.