Small Seismic Events in Oklahoma Detected and Located by Machine Learning–Based Models

Ma, Xiaofei; Chen, Ting

doi:10.1785/0120220029

Small Seismic Events in Oklahoma Detected and Located by Machine Learning–Based Models

Journal Article · Wed Sep 14 00:00:00 EDT 2022 · Bulletin of the Seismological Society of America

DOI:https://doi.org/10.1785/0120220029· OSTI ID:1924420

Ma, Xiaofei ^[1]; ^[1]

Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

A complete earthquake catalog is essential to understand earthquake nucleation and fault stress. Following the Gutenberg–Richter law, smaller, unseen seismic events dominate the earthquake catalog and are invaluable for revealing the fault state. The published earthquake catalogs, however, typically miss a significant number of small earthquakes. Part of the reason is due to a limitation of conventional algorithms, which can hardly extract small signals from background noise in a reliable and efficient way. To address this challenge, we utilized a machine learning method and developed new models to detect and locate seismic events. These models are efficient in processing a large amount of seismic data and extracting small seismic events. We applied our method to seismic data in Oklahoma, United States, and detected ~14 times more earthquakes compared with the standard Oklahoma Geological Survey catalog. The rich information contained in the new catalog helps better understand the induced earthquakes in Oklahoma.

View Accepted Manuscript (DOE)

Research Organization:: Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)

Sponsoring Organization:: USDOE Office of Fossil Energy (FE)

Grant/Contract Number:: 89233218CNA000001

OSTI ID:: 1924420

Report Number(s):: LA-UR-22-28753

Journal Information:: Bulletin of the Seismological Society of America, Journal Name: Bulletin of the Seismological Society of America Journal Issue: 6 Vol. 112; ISSN 0037-1106

Publisher:: Seismological Society of AmericaCopyright Statement

Country of Publication:: United States

Language:: English

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