Improving seismic fault mapping through data conditioning using a pre-trained deep convolutional neural network: A case study on Groningen field

Seismic fault interpretation is a crucial and indispensable step in reservoir exploration that requires substantial time. As a result, much research has been dedicated to applying deep learning in this venture. Deep learning has shown significant progress in the identification of seismic faults. How...

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Bibliographic Details
Main Authors: Otchere, D.A., Tackie-Otoo, B.N., Mohammad, M.A.A., Ganat, T.O.A., Kuvakin, N., Miftakhov, R., Efremov, I., Bazanov, A.
Format: Article
Published: Elsevier B.V. 2022
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85127071545&doi=10.1016%2fj.petrol.2022.110411&partnerID=40&md5=163d700ea6710c065c7de00a7579fb64
http://eprints.utp.edu.my/33058/
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