In this work, we test a fully automatic procedure to obtain local earthquake tomography (LET), starting from seismic waveforms and applying the capability of the automatic phase picker and locator engine “RSNI-Picker” (Spallarossa et al., 2014), which is based on a multistep iterative procedure working on P and S arrival times. This code is currently operating as part of the Earthquake Monitoring System at the University of Genoa (RSNI designates the regional seismic network of northwestern Italy). In particular, we compare P- and S-wave tomographic results obtained using this fully automatic procedure for picking and locations with those based on data from accurate manual picking and revised locations. We use a dataset of 409 earthquakes that occurred in the Trentino region (Northeastern Italy) in the 1994–2007 period. The highly variable waveform qualities (e.g., signal-tonoise ratio), mainly due to recording stations equipped with different types of sensors and digitizers (including both one-component narrowband stations and three-component broadband seismic stations), ensure a severe test for the automatic procedure. The comparison of the two 3D velocity propagation models for the Trentino region (i.e., LET images) from the automatic and manual procedures, shows maximum differences of 0.54 and 0:34 km=s for P and S waves, respectively (if we consider 90% of all the computed absolute velocities, as a reference percentage). The automatic LET shows velocity anomaly distributions and reliability patterns (e.g., resolution diagonal element [RDE] values) similar to those obtained using the manual procedure; 90% of RDE differences are lower than 0.15. The results obtained by testing the RSNI-Picker engine suggest it can be used to automatically process large amounts of seismic recordings in order to identify P and S wavepicks for reliable LET analysis.

Automatic P- and S-wave local earthquake tomography: testing performance of the automatic phase-picker engine "RSNI-Picker"

SCAFIDI, DAVIDE;SPALLAROSSA, DANIELE;TURINO, CHIARA;FERRETTI, GABRIELE;
2016-01-01

Abstract

In this work, we test a fully automatic procedure to obtain local earthquake tomography (LET), starting from seismic waveforms and applying the capability of the automatic phase picker and locator engine “RSNI-Picker” (Spallarossa et al., 2014), which is based on a multistep iterative procedure working on P and S arrival times. This code is currently operating as part of the Earthquake Monitoring System at the University of Genoa (RSNI designates the regional seismic network of northwestern Italy). In particular, we compare P- and S-wave tomographic results obtained using this fully automatic procedure for picking and locations with those based on data from accurate manual picking and revised locations. We use a dataset of 409 earthquakes that occurred in the Trentino region (Northeastern Italy) in the 1994–2007 period. The highly variable waveform qualities (e.g., signal-tonoise ratio), mainly due to recording stations equipped with different types of sensors and digitizers (including both one-component narrowband stations and three-component broadband seismic stations), ensure a severe test for the automatic procedure. The comparison of the two 3D velocity propagation models for the Trentino region (i.e., LET images) from the automatic and manual procedures, shows maximum differences of 0.54 and 0:34 km=s for P and S waves, respectively (if we consider 90% of all the computed absolute velocities, as a reference percentage). The automatic LET shows velocity anomaly distributions and reliability patterns (e.g., resolution diagonal element [RDE] values) similar to those obtained using the manual procedure; 90% of RDE differences are lower than 0.15. The results obtained by testing the RSNI-Picker engine suggest it can be used to automatically process large amounts of seismic recordings in order to identify P and S wavepicks for reliable LET analysis.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/830845
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