Application of subspace methods to detect and characterize coal mine related seismicity in the Western United States

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Title Application of subspace methods to detect and characterize coal mine related seismicity in the Western United States
Publication Type thesis
School or College College of Mines and Earth Sciences
Department Mining Engineering
Author Chambers, Derrick James Allen
Date 2015
Description An approach for subspace detection and magnitude estimation of small seismic events is proposed. The process is used to identify mining related seismicity from a surface coal mine and an underground coal mining district, both located in the Western U.S. Using a blasting log and a locally derived seismic catalog as ground truth, the detector performance is assessed in terms of verified detections, false positives, and failed detections. Over 95% of the surface coal mine blasts and about 33% of the events from the underground mining district are correctly identified. The number of potential false positives are kept relatively low by requiring detections to simultaneously occur on two stations. Many of the potential false detections for the underground coal district are genuine events missed by the local seismic network, demonstrating the usefulness of regional subspace detectors in augmenting local catalogs. A trade-off in detection performance between stations at smaller source-receiver distances, which have increased signal to noise ratios, and stations at larger distances, which have greater waveform similarity, is observed. The increased detection capabilities of a single higher dimension subspace detector, compared to multiple lower dimension detectors, are explored in identifying events that can be described as linear combinations of training events. In this data set, such an advantage can be significant, justifying the use of a subspace detection scheme over conventional correlation methods.
Type Text
Publisher University of Utah
Subject Matched Filters; Seismology; Subspace Detection
Dissertation Name Master of Science
Language eng
Rights Management Copyright © Derrick James Allen Chambers 2015
Format application/pdf
Format Medium application/pdf
Format Extent 27,144 bytes
Identifier etd3/id/3863
ARK ark:/87278/s6tt8099
Setname ir_etd
ID 197414
Reference URL https://collections.lib.utah.edu/ark:/87278/s6tt8099
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