Hierarchical Bayesian Approach to Locating Seismic Events
Conference
·
OSTI ID:888581
We propose a hierarchical Bayesian model for conducting inference on the location of multiple seismic events (earthquakes) given data on the arrival of various seismic phases to sensor locations. The model explicitly accounts for the uncertainty associated with a theoretical seismic-wave travel-time model used along with the uncertainty of the arrival data. Posterior inferences is carried out using Markov chain Monte Carlo (MCMC).
- Research Organization:
- Lawrence Livermore National Laboratory (LLNL), Livermore, CA
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- W-7405-ENG-48
- OSTI ID:
- 888581
- Report Number(s):
- UCRL-PROC-217057
- Country of Publication:
- United States
- Language:
- English
Similar Records
Stochastic Inversion of Seismic Amplitude-Versus-Angle Data (Stinv-AVA)
Sequential Monte-Carlo Framework for Dynamic Data-Driven Event Reconstruction for Atmospheric Release
Sequential Monte-Carlo Based Framework for Dynamic Data-Driven Event Reconstruction for Atmospheric Release
Software
·
Thu Apr 03 00:00:00 EDT 2008
·
OSTI ID:1231039
Sequential Monte-Carlo Framework for Dynamic Data-Driven Event Reconstruction for Atmospheric Release
Conference
·
Mon Jul 17 00:00:00 EDT 2006
·
OSTI ID:893974
Sequential Monte-Carlo Based Framework for Dynamic Data-Driven Event Reconstruction for Atmospheric Release
Conference
·
Tue Nov 15 23:00:00 EST 2005
·
OSTI ID:883520