DocumentCode :
2467554
Title :
Multiobjective Evolutionary Approach to the Solution of Gas Lift Optimization Problems
Author :
Ray, Tapabrata ; Sarker, Ruhul
Author_Institution :
Univ. of New South Wales, Canberra
fYear :
0
fDate :
0-0 0
Firstpage :
3182
Lastpage :
3188
Abstract :
In this paper, we discuss a practical oil production problem from a petroleum field. A field typically consists of a number of oil wells and to extract oil from these wells, gas is usually injected which is referred as gas-lift. The total gas used for the oil extraction is constrained by daily availability limits. The oil extracted from each well is known to be a nonlinear function of the gas injected into a well and varies between wells. The problem is to identify the optimal amount of gas that needs to be injected into each well to maximize the amount of oil extracted subject to the constraint mentioned earlier on a daily basis. The problem has long been of practical interest to all major oil exploration companies as it has a potential of deriving large financial benefits. Considering the complexity of the problem, we have used an evolutionary algorithm to solve the production planning problem. The multiobjective formulation is attractive as it eliminates the need to solve such problems on a daily basis while maintaining the quality of solutions. Our results show significant improvement over the existing practices.
Keywords :
computational complexity; evolutionary computation; nonlinear functions; oil technology; optimisation; petroleum industry; production planning; computational complexity; evolutionary algorithm; gas lift optimization problem; multiobjective evolutionary approach; nonlinear function; oil extraction; oil production problem; oil well; petroleum field; production planning; Aerospace engineering; Australia; Costs; Data mining; Evolutionary computation; Hydrocarbon reservoirs; Mechanical engineering; Petroleum; Production planning; Production systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-9487-9
Type :
conf
DOI :
10.1109/CEC.2006.1688712
Filename :
1688712
Link To Document :
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