JSM 2005 - Toronto

Abstract #304791

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Legend: = Applied Session, = Theme Session, = Presenter
Activity Number: 102
Type: Contributed
Date/Time: Monday, August 8, 2005 : 8:30 AM to 10:20 AM
Sponsor: Section on Bayesian Statistical Science
Abstract - #304791
Title: Hierarchical Bayesian Approach to Location Estimation of Seismic Events
Author(s): William G. Hanley*+ and Gardar Johannesson and Stephen C. Myers
Companies: Lawrence Livermore National Laboratory and Lawrence Livermore National Laboratory and Lawrence Livermore National Laboratory
Address: , , ,
Keywords: seismic events ; arrival-times ; model error ; Bayesian ; Markov chain Monte Carlo
Abstract:

Estimation and uncertainty characterization of the location (latitude, longitude, depth, and time) of an earthquake or another seismic event is a challenging problem. The available data includes observed arrival times of various wave-fronts (phases) propagated by the event to observation stations, where the number of observations depends on the magnitude of the event and station density. The observed arrival times can be compared to predicted arrival times generated via computer model for a given, hypothesized event location. In conducting inference on the event location, it is important that the methodology applied is able to take into account prior knowledge about the quality of the data, the travel-time model error, and the location. We propose a hierarchical Bayesian model that explicitly models the error processes associated with the observed arrival times and the travel-time model. This approach handles prior information in a natural (Bayesian) way. Posterior inference is conducted via Markov chain Monte Carlo (MCMC) sampling.

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