Title:
Human and Machine Listening of Seismic Data
Human and Machine Listening of Seismic Data
Authors
Paté, Arthur
Holtzman, Benjamin
Waldhauser, Felix
Repetto, Douglas
Paisley, John
Holtzman, Benjamin
Waldhauser, Felix
Repetto, Douglas
Paisley, John
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Abstract
Geothermal energy mining consists of injecting cold water into
hot rocks in order to create micro-fractures allowing heat to be
extracted and converted into electrical energy. This water injection
can trigger several rock fracture processes. Seismologists are
facing the challenge of identifying and understanding these fracture
processes in order to maximize heat extraction and minimize
induced seismicity. Our assumption is that each fracture process
is characterized by spectro-temporal features and patterns that are
not picked up by current signal processing methods used in seismology,
but can be identified by the human auditory system and/or
by machine learning. We present here a pluridisciplinary methodology
aimed at addressing this problem, combining machine learning,
auditory display and sound perception.
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2017-06
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This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.