A method of phase identification for seismic data acquired with the controlled accurate seismic source (CASS). Issue 1 (23rd April 2020)

• Record Type: Journal Article
• Authors: Wang, Xiaolei; Xue, Bing; Cui, Rensheng; Gu, Guoliang; Peng, Chaoyong; Zheng, Yu; Yang, Jiansi
• Is Part Of: Geophysical journal international. Volume 222:Issue 1(2020)
• Page Start: 54
• Page End: 68
• Publication Date: 2020-04-23
• Subjects: Time-series analysis -- Computational seismology -- Controlled source seismology -- Seismic interferometry; Geophysics -- Periodicals; 550
• DOI: 10.1093/gji/ggaa108
• Languages: English
• ISSNs: 0956-540X

Abstract

SUMMARY: With the advantages of the little destruction to the deployment site and high repeatability compared with explosive sources, the controlled accurate seismic source (CASS) has many potential applications with respect to the investigation of the crustal structure and seismic wave velocities. However, the signal generated by the CASS rapidly attenuates with the increasing distance because of its poor signal-to-noise ratio (SNR). Consequently, the difficulties in identifying specific seismic phases from the CASS data limit its application and popularization. The aim of this study is to present a new method to improve the accuracy of traveltime estimation and to identify more seismic phases travelling through the crust. We adopt the global seismic phase scanning algorithms (GSPSA) combined with an optimized narrowband time-varying filter, whose central frequency corresponds to the instantaneous frequency of the linear frequency modulation (LFM) signals produced by the CASS. Using the seismic data from the 40-ton CASS in a field experiment around Xinfengjiang reservoir in southeast China, we attain the seismic phases such as Pg, Sg, PmP and SmS at epicentral distances of more than 200 km with GSPSA. To identify and verify these seismic phases information, we also calculate synthetic waveforms. The results demonstrate that the GSPSA method is an effective tool for seismic phase identification of CASS data.