An algorithm for automated identification of fault zone trapped waves
We develop an algorithm for automatic identification of fault zone trapped waves in data recorded by seismic fault zone arrays. Automatic S picks are used to identify time windows in the seismograms for subsequent search for trapped waves. The algorithm calculates five features in each seismogram recorded by each station: predominant period, 1 s duration energy (representative of trapped waves), relative peak strength, arrival delay and 6 s duration energy (representative of the entire seismogram). These features are used collectively to identify stations in the array with seismograms that are statistical outliers. Applying the algorithm to large data sets allows for distinguishing genuine trapped waves from occasional localized site amplification in seismograms of other stations. The method is verified on a test data set recorded across the rupture zone of the 1992 Landers earthquake, for which trapped waves were previously identified manually, and is then applied to a larger data set with several thousand events recorded across the San Jacinto fault zone. The developed technique provides an important tool for systematic objective processing of large seismic waveform data sets recorded near fault zones.
Additional Information© The Authors 2015. Published by Oxford University Press on behalf of The Royal Astronomical Society. Accepted 2015 May 11. Received 2015 May 8; in original form 2014 December 11. We thank Hongrui Qiu and Pieter-Ewald Share for useful discussions. The study was supported by the National Science Foundation (grant EAR-0908903). The manuscript benefitted from constructive comments of two anonymous referees.
Published - ggv197.pdf