Ehsan Khamehchi - Faculty of Petroleum Engineering, Amirkabir University of Technology (Tehran Polytechnic), Hafez Avenue, Tehran, Iran
Mohammad Reza Mahdiani - Faculty of Petroleum Engineering, Amirkabir University of Technology (Tehran Polytechnic), Hafez Avenue, Tehran, Iran
Amir Gharcheh Beydokhti - Faculty of Petroleum Engineering, Amirkabir University of Technology (Tehran Polytechnic), Hafez Avenue, Tehran, Iran

In gas lift, gas is injected into wells to lift the oil to the surface and increases the production oil rate. Each well shows a different response to the injected gas rate and because of the limited amount of available lift, the gas allocation between wells should be in a way to maximize the total production oil rate. For this purpose, different optimization algorithms have been used in previous studies, but most of them suffer from a long runtime and low quality optimum point, in addition to not including some othernecessary parameters such as the production choke size. In this study, the lift gas injection rate and the production choke sizes have been optimized using the moth swarm algorithm (MSA) and its result compared with genetic algorithm and particle swarm optimization. Results show that MSA can find a good optimum point (lift rates and choke sizes) in minimum time

Gas lift ; Moth Swarm Algorithm ; Genetic Algorithm ; Particle Swarm Optimization ; Optimization