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Dynamic and recursive oil-reservoir proxy using Elman neural networks
(Institute of Electrical and Electronics Engineers Inc., 2017)
In this work, a reservoir simulation approximation model (proxy) based on recurrent artificial neural networks is proposed. This model is intended to obtain rates of oil, gas and water production at time t+1 from the ...
Compositional grading in oil and gas reservoirs
(Gulf Professional Publishing, 2017)
Compositional Grading in Oil and Gas Reservoirs offers instruction, examples, and case studies on how to answer the challenges of modeling a compositional gradient subject. Starting with the basics on PVT analysis, applied ...
COMPARISON OF RESIDUAL OIL SATURATION FOR WATER AND SUPERCRITICAL CO2 FLOODING IN A LONG CORE, WITH LIVE OIL AT RESERVOIR CONDITIONS
(Begell House IncReddingEUA, 2011)
Value assessment for reservoir recovery optimization
(Elsevier Science Bv, 2001-12)
This paper analyzes the managerial flexibility embedded in oil and gas exploration and production. The analysis includes the economic impact of using different production techniques on the valuation of oil reserves. Two ...
Controlling oil production in smart wells by MPC strategy with reinforcement learning
(Scopus, 2010)
This work presents the modeling and development of a methodology based on Model Predictive Control - MPC that uses a machine learning model, based on Reinforcement Learning, as the method for searching the optimal control ...
Use of Neuro-Simulation techniques as proxies to reservoir simulator: Application in production history matching
(Elsevier Science BvAmsterdamHolanda, 2007)
CO2 sequestration through enhanced oil recovery in a mature oil field
(Elsevier Science BvAmsterdamHolanda, 2009)
Assisted Process For Design Optimization Of Oil Exploitation Strategy
(Elsevier Science BVAmsterdam, 2016)