Global Seismic Monitoring: A Bayesian Approach

Authors

  • Nimar Arora University of California, Berkeley
  • Stuart Russell University of California, Berkeley
  • Paul Kidwell Lawrence Livermore National Lab
  • Erik Sudderth Brown University

Abstract

The automated processing of multiple seismic signals to detect and localize seismic events is a central tool in both geophysics and nuclear treaty verification. This paper reports on a project, begun in 2009, to reformulate this problem in a Bayesian framework. A Bayesian seismic monitoring system, NET-VISA, has been built comprising a spatial event prior and generative models of event transmission and detection, as well as an inference algorithm. Applied in the context of the International Monitoring System (IMS), a global sensor network developed for the Comprehensive Nuclear-Test-Ban Treaty (CTBT), NET-VISA achieves a reduction of around 50% in the number of missed events compared to the currently deployed system. It also finds events that are missed even by the human analysts who post-process the IMS output.

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Published

2011-08-04

How to Cite

Arora, N., Russell, S., Kidwell, P., & Sudderth, E. (2011). Global Seismic Monitoring: A Bayesian Approach. Proceedings of the AAAI Conference on Artificial Intelligence, 25(1), 1533-1536. Retrieved from https://ojs.aaai.org/index.php/AAAI/article/view/7955

Issue

Section

New Scientific and Technical Advances in Research