S21E:
New Advances in Automatic Detection, Location, and Characterization of Seismic Events II

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Session ID#: 32782

Session Description:
The number of seismic instruments being installed around the world has grown exponentially in the last two decades. The recorded data should provide much more detailed information about seismically active regions but only if seismic events can be accurately detected, located and their sources identified. The large amount of data collected daily by seismic networks precludes human analysts to manually process these waveforms routinely. The constant improvement in computational capacities requests the design of new approaches to process continuous waveform data automatically. Apart from a significant reduction in processing time, automatic analysis ensures consistency of the analysis over time. This session’s aim is to bring to light new methods that can be applied to large datasets, either retro-actively or in near-real time, to automatically detect, locate and characterize tectonic and non-tectonic seismic events. We encourage contributions that demonstrate how the proposed methods help improve our understanding of seismic processes.
Primary Convener:  Christian Baillard, School of Oceanography, University of Washington, Marine Geology and Geophysics, Seattle, United States
Conveners:  Clément Hibert, Ecole et Observatoire des Sciences de la Terre, CNRS UAR 830, EOST/Université de Strasbourg, Strasbourg, France, Felix Waldhauser, Columbia University of New York, Palisades, NY, United States and Alessia Maggi, Université de Strasbourg, EOST/CNRS, Institut Terre et Environnement de Strasbourg, UMR 7063, Strasbourg Cedex, France
Chairs:  Christian Baillard, School of Oceanography, University of Washington, Marine Geology and Geophysics, Seattle, United States, Clément Hibert, CNRS EOST/IPGS, DA, Strasbourg, France and Felix Waldhauser, Lamont-Doherty Earth Observatory, Palisades, NY, United States
OSPA Liaison:  Christian Baillard, School of Oceanography, University of Washington, Marine Geology and Geophysics, Seattle, United States
Index Terms:

7219 Seismic monitoring and test-ban treaty verification [SEISMOLOGY]
7230 Seismicity and tectonics [SEISMOLOGY]
7290 Computational seismology [SEISMOLOGY]
7294 Seismic instruments and networks [SEISMOLOGY]

Abstracts Submitted to this Session:

Efficient blind search for similar-waveform earthquakes in years of continuous seismic data (Invited) (233120)
Clara E Yoon1, Karianne J. Bergen2, Kexin Rong3, Hashem Elezabi3, Peter Bailis3, Philip Levis3 and Gregory C Beroza4, (1)Stanford University, Geophysics, Stanford, United States, (2)Stanford University, Institute for Computational and Mathematical Engineering, Stanford, United States, (3)Stanford University, Computer Science, Stanford, CA, United States, (4)Stanford University, Geophysics, Stanford, CA, United States
Automatic Seismic-Event Classification with Convolutional Neural Networks. (231934)
Angel Bueno Rodriguez1, Manuel Titos Luzón1, Luz Garcia Martinez1, Carmen Benitez1 and Jesús M Ibáñez2, (1)University of Granada, Signal Theory, Telematic and Communications, Granada, Spain, (2)University of Granada, Instituto Andaluz de Geofísica, Granada, Spain
An automated multi-scale network-based scheme for detection and location of seismic sources (265195)
Natalia Poiata1,2, Florent Aden-Antoniow3, Claudio Satriano4, Pascal Bernard2, Jean-Pierre Vilotte2 and Kazushige Obara5, (1)National Institute for Earth Physics, Ilfov, Romania, (2)Institut de Physique du Globe de Paris, Paris, France, (3)Massachusetts Institute of Technology, Boston, MA, United States, (4)Institut Physique du Globe de Paris, Paris, France, (5)ERI, The University of Tokyo, Bunkyo-Ku, Tokyo, Japan
Earthquake Monitoring with the MyShake Global Smartphone Seismic Network (261707)
Asaf Inbal1, Qingkai Kong2, Richard M Allen1 and William H Savran3, (1)University of California Berkeley, Berkeley, CA, United States, (2)Lawrence Livermore National Laboratory, Livermore, CA, United States, (3)Southern California Earthquake Center, Los Angeles, CA, United States
Spatial Coherency of Seismic Waves for Microseismic Detection/Location/Characterization: Application of 2016 IRIS Wavefield Experiment in Oklahoma (239494)
Nori Nakata, University of Oklahoma, ConocoPhillips School of Geology and Geophysics, Norman, OK, United States
Automatic seismic waveform location using multichannel coherency migration for induced and natural earthquakes (279454)
Andy Nowacki1, Peidong Shi2, Doug AC Angus3, Sebastian Rost4, Claire E Birnie2 and Sanyi Yuan5, (1)University of Leeds, School of Earth and Environment, Leeds, LS2, United Kingdom, (2)University of Leeds, School of Earth and Environment, Leeds, United Kingdom, (3)University of Leeds, Leeds, LS2, United Kingdom, (4)The University of Leeds, Leeds, United Kingdom, (5)China University of Petroleum, Beijing, China

See more of: Seismology