S-Wave Identification by Polarization Filtering and Waveform Coherence Analyses

High-resolution imaging with microseismic events requires the use of large and consistent data sets of seismic phase arrival times. In particular the S phase is important to derive physical parameters of the subsurface. Typically this phase is identified on one of the horizontal seismogram components by a change of signal amplitude and frequency as compared to the previous P phase. However, reliable S-phase identification can be difficult for local events because of a signal overlap with the P coda, the presence of converted phases, and possible S-wave splitting due to anisotropy. In this study we propose a new data processing technique aiming at uniquely identifying the S-phase arrival using all available records from a seismic network. The technique combines polarization analysis of single three-component recordings of an event with analysis of lateral waveform coherence across the network. This makes it possible to construct seismic sections in which the first arrival is the S phase. This graphical representation can support an operator in both the analysis of single events and in semiautomatic analyses of large datasets. In addition, an automated stacking velocity analysis provides S-wave velocities from these sections. We demonstrate the applicability of this technique using synthetic seismograms, and we evaluate the efficacy on a dataset of three-component velocimeter records from local earthquakes of the Campania-Lucania Apennines (southern Italy) recorded by the Irpinia Seismic Network (ISNet).