Title :
Neural networks versus Linear and Sequential Programming for Gas Lift Optimization in a two oil wells system
Author :
Salazar-Mendoza, R. ; Jimenez de la C, G. ; Ruz-Hernandez, J.A.
Author_Institution :
Inst. Mexicano del Petroleo, Campeche, Mexico
Abstract :
Using a model-based optimization, a neural network model is developed to calculate the optimal values of gas injection rate and oil rate of a gas lift production system. Two cases are analyzed: a) A single well production system and b) A production system composed by two gas lifted wells. The results were compared with the linear and sequential programming for gas lift optimization. For both cases minimizing the objective function the proposed strategy shows the ability of the neural networks to approximate the behavior of an oil production system and to solve optimization problems when a mathematical model is not available.
Keywords :
linear programming; natural gas technology; neural nets; production engineering computing; gas injection rate; gas lift optimization; linear programming; mathematical model; model-based optimization; neural network model; objective function; oil production system; oil rate; oil wells system; sequential programming; single well production system; Costs; Linear programming; Neural networks; Particle separators; Performance evaluation; Petroleum; Production systems; Routing; Testing; Transmitters;
Conference_Titel :
Neural Networks, 2009. IJCNN 2009. International Joint Conference on
Conference_Location :
Atlanta, GA
Print_ISBN :
978-1-4244-3548-7
DOI :
10.1109/IJCNN.2009.5179056
