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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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Published: |
Elsevier B.V.
2022
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| 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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