Automated ambient-noise processing applied to fiber-optic seismic acquisition (DAS)
Citations Over TimeTop 13% of 2018 papers
Abstract
Distributed acoustic sensing (DAS) is an emerging technology used to record seismic data that employs fiber optic cables as a probing system. Recently, a DAS array has been deployed beneath Stanford campus in the existing fiber optic telecommunication conduits. Because we can so easily use our telecomm infrastructure for continuous, dense, seismic acquisition, data collected in such a manner will go to waste unless we significantly automate ambient noise processing. Herein we present relevant data features for exploratory data analysis and identify coherent noise sources which inhibit reliable extraction of useful signals. We then train a convolutional neural network for detecting traffic noise and selectively filter it out to generate ambient seismic noise fields that are suitable for interferometry purposes. Presentation Date: Thursday, October 18, 2018 Start Time: 8:30:00 AM Location: 212A (Anaheim Convention Center) Presentation Type: Oral
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