Efficient AI-Physics hybrid model with productive capabilities to reduce the time of history matching and scenario assessment; a case study: Minagish oil field
Author:
Affiliation:
1. R&T Subsurface Department, R&T Subsurface Team of Innovation & Technology Group – Kuwait Oil Company (KOC), Kuwait City, Kuwait
2. Energy Technologies Department, Target Energy Solutions L.L.C. Muscat City, Oman
Publisher
Informa UK Limited
Link
https://www.tandfonline.com/doi/pdf/10.1080/10916466.2024.2324818
Reference16 articles.
1. Hybrid intelligent systems in petroleum reservoir characterization and modeling: the journey so far and the challenges ahead
2. Bengio Y. 2012. Practical recommendations for gradient-based training of deep architectures. arXiv:1206.5533v2 [cs.LG]
3. Reservoir Simulation
4. Deng, L., and Y. Dong. 2014. Deep learning: Methods and applications. Microsoft Research.Published as Foundations and Trends® in Signal Processing, Volume 7 Issues 3-4, ISSN: 1932–8346
5. Artificial Intelligence Applications in Reservoir Engineering: A Status Check
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