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Crustal Imaging With Bayesian Inversion of Teleseismic P Wave Coda Autocorrelation
Author(s) -
Tork Qashqai Mehdi,
Saygin Erdinc,
Kennett B. L. N.
Publication year - 2019
Publication title -
journal of geophysical research: solid earth
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.983
H-Index - 232
eISSN - 2169-9356
pISSN - 2169-9313
DOI - 10.1029/2018jb017055
Subject(s) - seismology , coda , geology , receiver function , inversion (geology) , autocorrelation , reflection (computer programming) , bayesian probability , spatial analysis , probabilistic logic , remote sensing , tectonics , lithosphere , computer science , artificial intelligence , statistics , mathematics , programming language
The autocorrelation of the seismic transmission response of a layered medium (autocorrelogram), in the presence of a free surface, corresponds to the reflection response. Despite many studies on the imaging of local structures through retrieval and forward modeling of stacked autocorrelograms, there is limited work on the inversion of these data. In this study, we demonstrate that the probabilistic inversion of autocorrelograms is efficient and can be used as an alternative imaging tool when other approaches are not applicable. Here, we calculate autocorrelograms of teleseismic P wave coda recorded on more than 1,200 permanent and temporary seismic stations across Australia and utilize a Bayesian framework to invert these data for crustal imaging. The results show patterns of structures consistent with those seen in previous crustal models constructed from receiver function, seismic reflection, and refraction methods. The new approach can therefore image large‐scale crustal structures comparable to those from other seismological methods.