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...
| 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 |
| Institution: | Universiti Teknologi Petronas |
| Record Id / ISBN-0: | utp-eprints.33058 / |
| 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/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|