Automatic detection of P- and S-wave arrival times: new strategies based on the modified fractal method and basic matching pursuit

Automatic detection of P- and S-wave arrival times: new strategies based on the modified fractal... In this work, new strategies for automatic identification of P- and S-wave arrival times from digital recorded local seismograms are proposed and analyzed. The database of arrival times previously identified by a human reader was compared with automatic identification techniques based on the Fourier transformation in reduced time (spectrograms), fractal analysis, and the basic matching pursuit algorithm. The first two techniques were used to identify the P-wave arrival times, while the third was used for the identification of the S-wave. For validation, the results were compared with the short-time average over long-time average (STA/LTA) of Rietbrock et al., Geophys Res Lett 39(8), (2012) for the database of aftershocks of the 2010 Maule M w = 8.8 earthquake. The identifiers proposed in this work exhibit good results that outperform the STA/LTA identifier in many scenarios. The average difference from the reference picks (times obtained by the human reader) in P- and S-wave arrival times is ∼ 1 s. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Journal of Seismology Springer Journals

Automatic detection of P- and S-wave arrival times: new strategies based on the modified fractal method and basic matching pursuit

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Publisher
Springer Journals
Copyright
Copyright © 2017 by Springer Science+Business Media Dordrecht
Subject
Earth Sciences; Geophysics/Geodesy; Structural Geology; Hydrogeology; Geotechnical Engineering & Applied Earth Sciences
ISSN
1383-4649
eISSN
1573-157X
D.O.I.
10.1007/s10950-017-9658-0
Publisher site
See Article on Publisher Site

Abstract

In this work, new strategies for automatic identification of P- and S-wave arrival times from digital recorded local seismograms are proposed and analyzed. The database of arrival times previously identified by a human reader was compared with automatic identification techniques based on the Fourier transformation in reduced time (spectrograms), fractal analysis, and the basic matching pursuit algorithm. The first two techniques were used to identify the P-wave arrival times, while the third was used for the identification of the S-wave. For validation, the results were compared with the short-time average over long-time average (STA/LTA) of Rietbrock et al., Geophys Res Lett 39(8), (2012) for the database of aftershocks of the 2010 Maule M w = 8.8 earthquake. The identifiers proposed in this work exhibit good results that outperform the STA/LTA identifier in many scenarios. The average difference from the reference picks (times obtained by the human reader) in P- and S-wave arrival times is ∼ 1 s.

Journal

Journal of SeismologySpringer Journals

Published: May 31, 2017

References

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