Redshift of Earthquakes via Focused Blind Deconvolution of Teleseisms

This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: http://doi.org/10.1093/gji/ggaa419. This is version 3 of this Preprint.

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Authors

Pawan Bharadwaj, Chunfang Meng, Aimé Fournier, Laurent Demanet, Mike Fehler

Abstract

We present a robust factorization of the teleseismic waveforms resulting from an earthquake source into signals that originate from the source and signals that characterize the path effects. The extracted source signals represent the earthquake spectrum and its variation with azimuth. Unlike most prior work on source extraction, our method is data-driven, and it does not depend on any path-related assumptions e.g., the empirical Green’s function. Instead, our formulation involves focused blind deconvolution (FBD), which associates the source characteristics with the similarity among a multitude of recorded signals. We also introduce a new spe...  more

DOI

https://doi.org/10.31223/osf.io/ehza7

Subjects

Applied Mathematics, Earth Sciences, Electrical and Computer Engineering, Engineering, Geophysics and Seismology, Physical Sciences and Mathematics, Signal Processing

Keywords

Surface waves, Earthquake source, Andaman, blind deconvolution, Doppler effect, fault inversion, focusing, Fraunhofer, redshift, Ridgecrest, rupture velocity

Dates

Published: 2019-10-13 12:52

Last Updated: 2020-03-30 21:50

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License

GNU Lesser General Public License (LGPL) 2.1