Next-generation earthquake monitoring

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Abstract/Contents

Abstract
Earthquake monitoring programs such as the one operated by the United States Geological Survey provide near-real-time information of earthquakes occurring around the globe. However, the provided information is often incomplete or not detailed enough, so that it is often necessary to reprocess the recorded continuous waveform data when analyzing seismicity in specific regions. This can delay progress in understanding ongoing seismic sequences or making decisions that are time sensitive. In this dissertation, I introduce a concept of next-generation earthquake monitoring - an earthquake monitoring task that aims at averting data reprocessing needs and delivering near-real-time information in a way that users can better utilize and interpret. I develop and explain in detail various approaches that can boost the standard workflow of building earthquake catalogs to the next level where high-quality earthquake catalogs can be produced almost fully automatically. I also demonstrate the value of next-generation earthquake monitoring through various case studies of induced earthquakes in the mid-continent oil and gas province of the United States.

Description

Type of resource text
Form electronic resource; remote; computer; online resource
Extent 1 online resource.
Place California
Place [Stanford, California]
Publisher [Stanford University]
Copyright date 2022; ©2022
Publication date 2022; 2022
Issuance monographic
Language English

Creators/Contributors

Author Park, Yongsoo, (Seismologist)
Degree supervisor Beroza, Gregory C. (Gregory Christian)
Thesis advisor Beroza, Gregory C. (Gregory Christian)
Thesis advisor Baker, Jack W
Thesis advisor Ellsworth, William L
Degree committee member Baker, Jack W
Degree committee member Ellsworth, William L
Associated with Stanford University, Department of Geophysics

Subjects

Genre Theses
Genre Text

Bibliographic information

Statement of responsibility Yongsoo Park.
Note Submitted to the Department of Geophysics.
Thesis Thesis Ph.D. Stanford University 2022.
Location https://purl.stanford.edu/nq694sf4627

Access conditions

Copyright
© 2022 by Yongsoo Park
License
This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).

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