USGS ScienceSearch

USGS · 70204502

Characterizing seismogenic fault structures in Oklahoma using a relocated template matched catalog

Abstract

Oklahoma is one of the most seismically active places in the United States as a result of industry activities. In order to characterize the fault networks responsible for these earthquakes in Oklahoma, we relocated a large-scale template matching catalog between 2010-2016 using the GrowClust algorithm . This relocated catalog is currently the most complete statewide catalog for Oklahoma during this seven-year window. Using this relocated catalog, we identified seismogenic fault segments by developing an algorithm that clusters earthquakes and then identifies linear trends within each cluster. Considering the large number of earthquakes in Oklahoma, this algorithm made the process of identifying previously unmapped seismogenic faults more approachable and objective. We identify approximately 2500 seismogenic fault segments which are in general agreement with focal mechanisms and optimally oriented relative to maximum principle stress measurements. We demonstrate that these fault orientations can be used to approximate the maximum principle stress orientations.

Explore related subjects

90° N90° S · 180° W ← longitude → 180° E
Source-reported bounding extent: 33.616567° to 37.002206° latitude; -103.002434° to -94.431215° longitude. This indicates report coverage, not an exact sampling location. View area on OpenStreetMap.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Robert Skoumal, Joern Ole Kaven, Jake Water. 2019-05-29. Characterizing seismogenic fault structures in Oklahoma using a relocated template matched catalog. https://doi.org/10.1785/0220190045

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related USGS reports

Digitizer Suite: The Albuquerque Seismological Laboratory Digitizer Testing Suite

Laboratory testing of digitizers and seismometers helps ensure that prior to deployment the instrumentation can produce high quality data and is operating within specifications. In this work we detail the software package called: the Albuquerque Seismological Laboratory (ASL) Digitizer Test Suite. This Java software package provides several algorithms to verify various performance parameters of digitizers commonly used for recording analog seismic instruments. The goal of these tests is not to be exhaustive, but to identify common failures that could compromise the integrity of seismic data being recorded on the digitizer. For example, Sandia National Laboratories (e.g., Slad and Merchant, 2018) routinely do comprehensive testing of digitizers for various monitoring missions. While these tests reports are valuable for comprehensively characterizing a recording system, it would be resource intensive to conduct such tests on every seismic recorder used in a network. We focus on tests that include ways to estimate the sensitivity, timing, self-noise, and clip-level of the digitizer, as well as the fidelity of the signal being recorded. The software is publicly available and provides a way for the community to verify the integrity of a digitizer using a minimum amount of outside equipment.

Seismological Research Letters

The digital archivist: Automating legacy macroseismic data processing using large language models

Macroseismic data are a key resource to investigate shaking and damage from preinstrumental and early instrumental eras. However, data are often stored as inconsistently formatted reports describing observed shaking and damage, making manually parsing and interpreting accounts labor‐intensive. We introduce a novel workflow using Google’s Gemini 2.5 Pro large language model (LLM) to automate the extraction and structuring of macroseismic observations from summary reports. We apply this workflow to the 22 March 1957 M 5.3 Daly City, California, earthquake as a case study. We used Gemini to extract addresses, originally assigned modified Mercalli intensity values, and descriptions from each report. To address coordinate precision limits, addresses were geocoded via Google’s Geocoding application programming interface. This workflow yielded over 2300 geocoded intensity reports for the Daly City earthquake. We use the geocoded accounts, with the original report intensity assignments, to develop a shaking intensity map that in some respects rivals modern Did You Feel It? Maps. We also extract and present data for the 9 February 1971 M L 6.7 Sylmar, California, earthquake. Our results demonstrate the potential of LLMs for reliably extracting and analyzing large, unstructured macroseismic datasets. LLMs offer a scalable solution for rapidly digitizing macroseismic archives, enabling their broader use to constrain ground‐motion models in modern seismic hazard analysis and to improve our understanding of site effects in urban areas. The concepts explored here may also be applied to the handling of other legacy seismological and earth science data.

Seismological Research Letters