Application of Subspace Detectors to 2012 Sumatera Earthquake Sequence

Technical Report · Mon Sep 16 04:00:00 EDT 2013

DOI:https://doi.org/10.2172/1097763· OSTI ID:1097763

Dodge, Doug ^[1]

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1. Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

In this report the aftershock sequence of the 2012 Sumatra earthquake is used to study the performance of subspace detectors (Harris, 2006) to detect and classify the events. The ground truth used for this study is 1222 aftershock solutions from the LLNL database drawn mostly from the Reviewed Event Bulletin (REB). Subspace detectors are built using several spawning strategies with waveforms recorded by the Makanchi Array (MKAR). Because we desire the subspace detectors to have a very low false alarm rate, the subspace templates are required to be about 50 seconds long (most of the P-bundle). For the same reason, the power detections used to create the subspace templates are restricted to have high SNR. Because of these restrictions, none of the subspace detectors are able to reproduce the entire ground truth catalog. They do have a very low false alarm rate, however, and so can reliably be used as single-array detection classifiers. Because of their reliability, in a suitably designed system, these detectors could be used to segregate detections from regions of high seismicity such as aftershock sequences, and allow processing of those detections in isolation from routine seismicity. It may also be possible to use these detectors to process groups of detections simultaneously. This leads to the concept of “analyst workload reduction factor”; a measure of the reduction in effort achieved by processing N detections in M groups instead of individually. If M is much smaller than N, a significant reduction factor is achieved.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE
• DOE Contract Number: W-7405-ENG-48; AC52-07NA27344
• OSTI ID: 1097763
• Report Number(s): LLNL--TR-643863
• Country of Publication: United States
• Language: English

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