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Explosion discrimination using seismic gradiometry and spectrally filtered principal components; controlled field experiments

Cristian Challu, Christian Poppeliers, Predrag Punosevac and Artur Dubrawski
Explosion discrimination using seismic gradiometry and spectrally filtered principal components; controlled field experiments
Bulletin of the Seismological Society of America (September 2022) 112 (6): 3141-3150

Abstract

Spectrally filtered principal component analysis (SFPCA) is a method we developed to discriminate between seismic source types. It is based on the well-known principal component analysis but applied to seismic gradiometric data. In this article, we build on our previous efforts by testing the method on data collected in a small-scale field experiment using two source types generated by manually striking the ground at various source-receiver distances (source type A) and orientations relative to the ground surface (source type B). Using the SFPCA method that we originally developed in Challu et al. (2021), we found that we can achieve good discrimination performance for a wide range of experimental geometries and noise conditions. In addition to testing the SFPCA method using a supervised learning approach, we present an SFPCA-based discrimination method using an anomaly detection paradigm. Specifically, given a population of event-specific data (e.g., source type A), we demonstrate that an event with source type B will fall outside the accepted population range of source type A. Thus, SFPCA may have value as a seismic discriminant in the form of an anomaly detector, which may be useful if a sufficient training dataset is not available.


ISSN: 0037-1106
EISSN: 1943-3573
Coden: BSSAAP
Serial Title: Bulletin of the Seismological Society of America
Serial Volume: 112
Serial Issue: 6
Title: Explosion discrimination using seismic gradiometry and spectrally filtered principal components; controlled field experiments
Affiliation: Carnegie Mellon University, Auton Lab, Pittsburgh, PA, United States
Pages: 3141-3150
Published: 20220930
Text Language: English
Publisher: Seismological Society of America, Berkeley, CA, United States
References: 13
Accession Number: 2022-056189
Categories: Seismology
Document Type: Serial
Bibliographic Level: Analytic
Illustration Description: illus. incl. 2 tables
N34°49'60" - N35°00'00", W106°49'60" - W106°00'00"
Secondary Affiliation: Sandia National Laboratories, Geophysics Department, Albuquerque, NM, USA, United States
Country of Publication: United States
Secondary Affiliation: GeoRef, Copyright 2022, American Geosciences Institute. Abstract, Copyright, Seismological Society of America. Reference includes data from GeoScienceWorld, Alexandria, VA, United States
Update Code: 202242
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