Comparative study of different risk measures for robust optimization of oil production under the market uncertainty: a regret-based insight-Reference-Cited by-同舟云学术

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Comparative study of different risk measures for robust optimization of oil production under the market uncertainty: a regret-based insight

Published:2020-05-06 Issue:3 Volume:24 Page:1409-1427
ISSN:1420-0597
Container-title:Computational Geosciences
language:en
Short-container-title:Comput Geosci

Author:

Mohammadi Mostafa,Ahmadi Mohammad,Kazemi Alireza

Publisher

Springer Science and Business Media LLC

Subject

Computational Mathematics,Computational Theory and Mathematics,Computers in Earth Sciences,Computer Science Applications

Link

https://link.springer.com/content/pdf/10.1007/s10596-020-09960-7.pdf

Reference42 articles.

1. Brouwer, D.: Dynamic water flood optimization with smart wells using optimal control theory [D]. Delft University of Technology, Delft (2004)

2. Van den Hof, P.M., J.D. Jansen, and A. Heemink. Recent developments in model-based optimization and control of subsurface flow in oil reservoirs. in Proceedings of the 2012 IFAC Workshop on Automatic Control in Offshore Oil and Gas Production. 2012

3. Foss, B.: Process control in conventional oil and gas fields—challenges and opportunities. Control. Eng. Pract. 20(10), 1058–1064 (2012)

4. Van den Hof, P.M., et al. Model-based control and optimization of large scale physical systems-challenges in reservoir engineering. In Control and Decision Conference, 2009. CCDC’09. Chinese. 2009. IEEE

5. van Essen, G., et al.: Robust waterflooding optimization of multiple geological scenarios. SPE J. 14(01), 202–210 (2009)

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