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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 ...
Application of ARX neural networks to model the rate of penetration of petroleum wells drilling
(2006-12-01)
Bit performance prediction has been a challenging problem for the petroleum industry. It is essential in cost reduction associated with well planning and drilling performance prediction, especially when rigs leasing rates ...
Application of ARX neural networks to model the rate of penetration of petroleum wells drilling
(2006-12-01)
Bit performance prediction has been a challenging problem for the petroleum industry. It is essential in cost reduction associated with well planning and drilling performance prediction, especially when rigs leasing rates ...
Polymeric networks based on tung oil: reaction and modification with green oil monomers
(Elsevier, 2015-01-19)
A highly unsaturated vegetable oil (tung oil) was cationically copolymerized with a vegetable oil derived monomer, that replaces the more frequently used styrene. The synthesized comonomer was methyl ester of tung oil, ...
Antibacterial activity of oregano essential oil against foodborne pathogens
(2013-03-20)
Purpose: This paper aims to evaluate in vitro antibacterial activity of oregano essential oil against foodborne pathogens as a starting point for the use of spice as a natural preservative in food. Design/methodology/approach: ...
Antibacterial activity of oregano essential oil against foodborne pathogens
(2013-03-20)
Purpose: This paper aims to evaluate in vitro antibacterial activity of oregano essential oil against foodborne pathogens as a starting point for the use of spice as a natural preservative in food. Design/methodology/approach: ...