Human and Machine Listening of Seismic Data | Zendy

Arthur Paté | Zendy; B. K. Holtzman | Zendy; F. Waldhauser | Zendy; Douglas Repetto | Zendy; John Paisley | Zendy

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Human and Machine Listening of Seismic Data

Author(s) -

Arthur Paté,

B. K. Holtzman,

F. Waldhauser,

Douglas Repetto,

John Paisley

Publication year - 2017

Language(s) - English

Resource type - Conference proceedings

DOI - 10.21785/icad2017.047

Subject(s) - computer science , induced seismicity , energy (signal processing) , fracture (geology) , active listening , process (computing) , signal (programming language) , perception , seismology , extraction (chemistry) , geology , artificial intelligence , acoustics , geotechnical engineering , statistics , mathematics , communication , neuroscience , sociology , biology , programming language , operating system , chemistry , physics , chromatography

by changes in volume of the rock and fluid as their temperatures change). One current challenge in the field of seismology is to be able to identify these fracture mechanisms from the seismic signals, possibly in real time, so we can have control on them in order to maximize the heat extraction while minimizing the fluid pumping and induced seismicity. In this project we focus on the earthquakes occurring at an active geothermal reservoir at “The Geysers” in Sonoma County, CA, USA.

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