Abstract
Optimization of Gas Lift Allocation Using Different Models
Highlights
The normal yield of an oil well does not meet the demands of oil industry due to increasing rate of collection
Pump and gas lift is one of the artificial lift approaches; it could not be used in all wells with maximum power due to energy consumption problem
Studying gas lift is usually performed by using gas lift performance curve
Summary
Gas lift for oil-gas extraction is a common practice; obtaining maximum productivity of a series of set is not a simple tax because high amount of gas lift makes the optimization of few wells at the same time a very hard task. It could be possible to obtain higher production rate versus less gas consumption. The present paper is a new approach that uses neural functions and genetic algorithm and studies the different aspects of problem solving for gas allocation optimization in five wells. The results showed that artificial neural networks have very good function in modeling gas lift process and creating gas lift performance curve versus classic methods. The differences between the results obtained by artificial neural network in comparison with results that are obtained in classic methods prove this claim
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