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Comparing EGF methods for estimating corner frequency and stress drop from p wave spectra

TitleComparing EGF methods for estimating corner frequency and stress drop from p wave spectra
Publication TypeJournal Article
Year of Publication2019
AuthorsShearer PM, Abercrombie R.E, Trugman D.T, Wang W.
JournalJournal of Geophysical Research-Solid Earth
Date Published2019/04
Type of ArticleArticle
ISBN Number2169-9313
Accession NumberWOS:000468912000040
Keywords2009 laquila; attenuation; borehole; constrain; corner frequency; earthquake; EGF estimation; Geochemistry & Geophysics; greens-function analysis; m-w; site response; source; source scaling relationships; southern california; stress drop

Empirical Green's functions (EGFs) are widely applied to correct earthquake spectra for attenuation and other path effects in order to estimate corner frequencies and stress drops, but these source parameter estimates often exhibit poor agreement between different studies. We examine this issue by analyzing a compact cluster of over 3,000 aftershocks of the 1992 Landers earthquake. We apply and compare two different analysis and modeling methods: (1) the spectral decomposition and global EGF fitting approach and (2) a more traditional EGF method of modeling spectral ratios. We find that spectral decomposition yields event terms that are consistent with stacks of spectral ratios for individual events, but source parameter estimates nonetheless vary between the methods. The main source of differences comes from the modeling approach used to estimate the EGF. The global EGF-fitting approach suffers from parameter trade-offs among the absolute stress drop, the stress drop scaling with moment, and the high-frequency falloff rate but has the advantage that the relative spectral shapes and stress drops among the different events in the cluster are well resolved even if their absolute levels are not. The spectral ratio approach solves for a different EGF for each target event without imposing any constraint on the corner frequency, f(c), of the smaller events, and so can produce biased results for target event f(c). Placing constraints on the small-event f(c) improves the performance of the spectral ratio method and enables the two methods to yield very similar results.

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