Seismic Event Identification: Context to Confidence

We present a probabilistic framework to automate event-type labeling of seismic event catalogs via contextual data fusion. Our framework fuses information derived from seismic waveform features with geospatial context such as the location of known earthquakes, nuclear test sites, and mining operatio...

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Main Authors: Richard Alfaro-Diaz, Jonas A. Kintner, Josh D. Carmichael
Format: Article
Language:English
Published: Seismological Society of America 2025-04-01
Series:The Seismic Record
Online Access:https://doi.org/10.1785/0320250005
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author Richard Alfaro-Diaz
Jonas A. Kintner
Josh D. Carmichael
author_facet Richard Alfaro-Diaz
Jonas A. Kintner
Josh D. Carmichael
author_sort Richard Alfaro-Diaz
collection DOAJ
description We present a probabilistic framework to automate event-type labeling of seismic event catalogs via contextual data fusion. Our framework fuses information derived from seismic waveform features with geospatial context such as the location of known earthquakes, nuclear test sites, and mining operations to infer event-type labels and associated uncertainty. This framework mirrors expert analyst reasoning by simultaneously considering both the seismic waveform characteristics and the geospatial context of each event to formally combine multiple lines of evidence. We integrate these disparate observations via Bayesian hierarchical modeling to structure data and exchange of information across data categories. Unlike standard approaches with deterministic seismic event-type labels, our framework provides a quantitative measure of uncertainty for informed decision-making. We demonstrate this technique on a comprehensive catalog of analyst-derived ground-truth earthquake and explosion event types located within the Great Basin in the western United States.
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spelling doaj-art-09d485d7335c442e99405cbc9dcce2c52025-08-20T03:52:33ZengSeismological Society of AmericaThe Seismic Record2694-40062025-04-015215516410.1785/0320250005tsr2025005Seismic Event Identification: Context to ConfidenceRichard Alfaro-Diaz0https://orcid.org/0000-0001-6723-5996Jonas A. Kintner1https://orcid.org/0000-0002-0739-6349Josh D. Carmichael2https://orcid.org/0000-0001-5752-5738Los Alamos National Laboratory, Geophysical Explosion Monitoring Team, Los Alamos National Laboratory, Los Alamos, New Mexico, U.S.A.Los Alamos National Laboratory, Geophysical Explosion Monitoring Team, Los Alamos National Laboratory, Los Alamos, New Mexico, U.S.A.Los Alamos National Laboratory, Geophysical Explosion Monitoring Team, Los Alamos National Laboratory, Los Alamos, New Mexico, U.S.A.We present a probabilistic framework to automate event-type labeling of seismic event catalogs via contextual data fusion. Our framework fuses information derived from seismic waveform features with geospatial context such as the location of known earthquakes, nuclear test sites, and mining operations to infer event-type labels and associated uncertainty. This framework mirrors expert analyst reasoning by simultaneously considering both the seismic waveform characteristics and the geospatial context of each event to formally combine multiple lines of evidence. We integrate these disparate observations via Bayesian hierarchical modeling to structure data and exchange of information across data categories. Unlike standard approaches with deterministic seismic event-type labels, our framework provides a quantitative measure of uncertainty for informed decision-making. We demonstrate this technique on a comprehensive catalog of analyst-derived ground-truth earthquake and explosion event types located within the Great Basin in the western United States.https://doi.org/10.1785/0320250005
spellingShingle Richard Alfaro-Diaz
Jonas A. Kintner
Josh D. Carmichael
Seismic Event Identification: Context to Confidence
The Seismic Record
title Seismic Event Identification: Context to Confidence
title_full Seismic Event Identification: Context to Confidence
title_fullStr Seismic Event Identification: Context to Confidence
title_full_unstemmed Seismic Event Identification: Context to Confidence
title_short Seismic Event Identification: Context to Confidence
title_sort seismic event identification context to confidence
url https://doi.org/10.1785/0320250005
work_keys_str_mv AT richardalfarodiaz seismiceventidentificationcontexttoconfidence
AT jonasakintner seismiceventidentificationcontexttoconfidence
AT joshdcarmichael seismiceventidentificationcontexttoconfidence