Geological Survey of Denmark and Greenland (GEUS)
University of Wisconsin-Milwaukee
In this paper, automatic detection and picking of the S-wave, in the problem of passive seismic monitoring has been studied, and a method is proposed for detecting S-phase onset time based on the eigenvalue analysis. By calculating eigenvalues of the time domain covariance matrix of the earthquake record, a characteristic function is defined, in which applying an adaptively determined threshold value, the S-phase onset time is picked. The proposed method is capable of successful determining S-phase onset time in local and near regional seismograms. Motivation towards this research has been the growing number of operating seismic stations in Iranian Broadband Network (BIN) and the necessity of providing earthquake parameters information fast and precisely. In addition, a doing well S-phase picking algorithm can be used to increase the number of determined S-phases in databases in which tomography studies are carried on. We tested the proposed method on 185 earthquakes recorded in the BIN, and evaluated the performance of the algorithm. We also examined the other algorithm of S-phase detection based on Autoregressive (AR) modeling of the seismograms on the same data, and compare the output of two algorithms. This comparison implies that the results of the proposed method are better than the AR based algorithm on our database.