Assessing Dynamic Time Warping Techniques for Discriminating Seismic Sources at Local and Regional Distances

Technical Report · Fri Aug 01 00:00:00 EDT 2025

DOI:https://doi.org/10.2172/3007935· OSTI ID:3007935

Beskardes, Gungor Didem ^[1]; Tibi, Rigobert ^[1]; Young, Christopher John ^[1]

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1. Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)

Effective monitoring of seismic explosions and hazard assessment relies heavily on the accurate discrimination of underground seismic sources. This study investigates the application of novel nonlinear alignment techniques, specifically Dynamic Time Warping (DTW), for event-type discrimination at regional and local distances. Building on prior research that used DTW and Elastic Shape Analysis (ESA) in discrimination at regional distances, we evaluate the performance of recently developed variants of DTW, including a method that employs Pearson cross-correlation as a measure of warping distance and a time distortion coefficient that quantifies the type and degree of time distortion between signals. By analyzing observational datasets that include different source types, we assess the performance of these approaches for realistic monitoring scenarios. Specifically, we consider a dataset recorded at regional distances in the Korean Peninsula and a local-distance subset from the Unconstrained Utah Event Bulletin catalog to evaluate DTW-based discrimination across multiple distance scales. Additionally, we introduce the maximum cross-correlations of warped waveforms as a similarity metric for event classification. Through hierarchical cluster analysis and dendrogram interpretation, we present our findings, highlighting the strengths and limitations of these techniques in seismic event classification.

• Research Organization: Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation
• DOE Contract Number: NA0003525
• OSTI ID: 3007935
• Report Number(s): SAND--2025-14908; 1794254
• Country of Publication: United States
• Language: English