Adapting Pipeline Architectures to Track Developing Aftershock Sequences and Recurrent Explosions
Abstract
A detection framework has been developed which augments a routine processing pipeline with mechanisms for spawning and administering so-called pattern detectors to identify and organize repeating waveforms discovered in multichannel seismic data streams. The framework has been tested and evaluated on a variety of different test cases from mining blasts in Central Asia to moderate and large earthquake aftershock sequences. The framework performs exceptionally in identifying repeating mining blasts, with signals from large clusters of events belonging exclusively to known quarries being detected and grouped fully automatically. For the moderate aftershock sequence scenario, the framework provided an event catalog down to a significantly lower completeness magnitude than could be generated with the available analyst resources. The large earthquake scenarios are far more challenging given the exceptionally large source regions covered by the aftershocks. The formation of high-rank subspace detectors can sweep up large proportions of the seismicity although not necessarily in a way that reduces significantly the burden of analyst interpretation. We suggest the use of a subspace-measure of waveform similarity that may perform better than the classical correlation coefficient for forming and evaluating clusters in such cases. Submerging a signal from the DPRK nuclear test into data from the same array from an extensive aftershock sequence, we demonstrate that this important signal is not screened out by the pattern detector components of the framework. We propose empirical matched field processing (EMFP) on single array streams as a sensitive primary detector for generating triggers at, and only at, the times of arrivals from events in the region of interest.
Document Details
- Document Type
- Technical Report
- Publication Date
- Feb 14, 2014
- Accession Number
- ADA602522
Entities
People
- D. B. Harris
- D. Dodge
- S. J. Gibbons
- Tormod Kvaerna