Applications of Data-Driven Techniques in Reservoir Simulation and Management

Author:

Jahanbani Ghahfarokhi Ashkan

Publisher

Springer International Publishing

Reference43 articles.

1. Amiri B (2022) A fast and accurate investigation into CO2 storage challenges by making a proxy model on a developed static model with the application of artificial intelligence/machine learning. Politecnico di Torino. http://webthesis.biblio.polito.it/id/eprint/23043. http://creativecommons.org/licenses/by-nc-nd/3.0/

2. Bahrami P, Sahari Moghaddam F, James LA (2022) A review of proxy modeling highlighting applications for reservoir engineering. Energies 15:5247. https://doi.org/10.3390/en15145247. https://creativecommons.org/licenses/by/4.0/

3. Benamara C, Gharbi K, Nait Amar M, Hamada B (2020) Prediction of wax appearance temperature using artificial intelligent techniques. Arab J Sci Eng 45:1319–1330

4. Bratvold RB, Bickel JE, Lohne HP (2009) Value of information in the oil and gas industry: past, present and future. SPE Reserv Eval Eng 12

5. Chaturvedi A (2021) Well control optimization by coupling smart proxy models with genetic algorithm. Norwegian University of Science and Technology. NTNU Open: https://hdl.handle.net/11250/2781628

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