Published in: 14th International Industrial Engineering Conference
COI code: IIEC14_071
Paper Language: English
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Authors Production and Injection Optimization in an Oil Field Using Moth Swarm AlgorithmEhsan 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
Abstract: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
Keywords:Gas lift ; Moth Swarm Algorithm ; Genetic Algorithm ; Particle Swarm Optimization ; Optimization
COI code: IIEC14_071
how to cite to this paper:If you want to refer to this article in your research, you can easily use the following in the resources and references section:
Khamehchi, Ehsan; Mohammad Reza Mahdiani & Amir Gharcheh Beydokhti, 2017, Production and Injection Optimization in an Oil Field Using Moth Swarm Algorithm, 14th International Industrial Engineering Conference, تهران, انجمن مهندسي صنايع ايران - دانشگاه علم و صنعت ايران, https://www.civilica.com/Paper-IIEC14-IIEC14_071.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Khamehchi, Ehsan; Mohammad Reza Mahdiani & Amir Gharcheh Beydokhti, 2017)
Second and more: (Khamehchi; Mahdiani & Gharcheh Beydokhti, 2017)
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The University/Research Center Information:
Type: state university
Paper No.: 19662
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