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TitleTracking earthquake sequences in real time: application of seismicity-scanning based on navigated automatic phase-picking (S-SNAP) to the 2019 Ridgecrest, California sequence
 
AuthorTan, F; Kao, HORCID logo; Nissen, E; Visser, R
SourceGeophysical Journal International vol. 223, issue 3, 2020 p. 1511-1524, https://doi.org/10.1093/gji/ggaa387
Image
Year2020
Alt SeriesNatural Resources Canada, Contribution Series 20200360
PublisherOxford University Press
Documentserial
Lang.English
Mediapaper; on-line; digital
File formatpdf; html
AreaRidgecrest, California; United States of America
Lat/Long WENS-119.4167 -116.0000 37.0000 34.3333
SubjectsScience and Technology; seismology
Illustrationslocation maps; cross-plots; graphs; diagrams
ProgramPublic Safety Geoscience Assessing Earthquake Geohazards
Released2020 08 17
AbstractRecent improvements in seismic data processing techniques have enhanced our ability to detail the evolution of major earthquake sequences in space and time. One such advance is new scanning algorithms that allow large volumes of waveform data to be analysed automatically, removing human biases and inefficiencies that inhibit standardized monitoring. The Seismicity-Scanning based on Navigated Automatic Phase-picking (S-SNAP) workflow has previously been shown to be capable of producing high-quality earthquake catalogues for injection-induced seismicity monitoring. In this study, we modify the original S-SNAP workflow to enable it to delineate the spatiotemporal distribution of major earthquake sequences in real time. We apply it to the 2019 Ridgecrest, southern California earthquake sequence, which culminated in an Mw 6.4 foreshock on July 4 and an Mw 7.1 main shock on July 6 and generated tens of thousands of smaller earthquakes. Our catalogue-which spans the period 2019 June 1 to July 16-details the spatiotemporal evolution of the sequence, including early foreshocks on July 1 and accelerating foreshocks on July 4, a seismicity gap before the main shock around its epicentre, seismicity on discrete structures within a broad fault zone and triggered earthquakes outside the main fault zone. We estimate the accuracy and false detection rate of the S-SNAP catalogue based on the reviewed catalogue reported by Southern California Seismic Network (SCSN) and our own visual inspection. We demonstrate the advantages of S-SNAP over a generalized automatic earthquake monitoring software, Seiscomp3, and a customized real-time earthquake information system for southern California, TriNet. In comparison, the S-SNAP catalogue contains five times more events than the Seiscomp3 catalogue and 1.4-2.2 times as many events per hour as the TriNet catalogue at most times. In addition, S-SNAP is more likely to solve phase association ambiguities correctly and provide a catalogue with consistent quality through time. S-SNAP would be beneficial to both routine network operations and the earthquake review process.
Summary(Plain Language Summary, not published)
The innovative earthquake location algorithm, Seismicity-Scanning based on Navigated Automatic Phase-Picking (S-SNAP), was originally developed to produce high-quality earthquake catalogs for induced seismicity monitoring. In this study, we modify the original S-SNAP workflow to make it capable of delineating complicated seismicity distribution of major earthquake sequences in real time. We apply it to the July 2019 Ridgecrest, southern California earthquake sequence. The results show that our catalog is able to detail the complicated evolution of the sequence, including early foreshocks on July 1st, seismicity on discrete structures within a broad fault zone and triggered earthquakes outside the main fault zone. We demonstrate the advantages of S-SNAP over other methods and routine catalogs. If S-SNAP is used in routine network operations, it is technically feasible to provide real-time information on aftershock-related hazard assessment during major earthquake sequences.
GEOSCAN ID327049

 
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