A holistic review on artificial intelligence techniques for well placement optimization problem

Islam, J. and Vasant, P.M. and Negash, B.M. and Laruccia, M.B. and Myint, M. and Watada, J. (2020) A holistic review on artificial intelligence techniques for well placement optimization problem. Advances in Engineering Software, 141.

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Abstract

Well placement optimization is one of the major challenging factors in the field development process of oil and gas industry. The objective function of well placement optimization is considered as high dimensional, discontinuous and multi-model. Over the last decade, both gradient-based and gradient-free optimization methods have been implemented to tackle this problem. Nature-inspired gradient-free optimization algorithms like particle swarm optimization, genetic algorithm, covariance matrix adaptation evolution strategy and differential evolution have been utilized in this area. These optimization techniques are implemented as stand-alone or as hybrid form to maximize the economic factors. In this paper, several nature-inspired metaheuristic optimization techniques and their application to maximize the economic factors are reviewed. Newly developed optimization algorithms are very efficient and favorable when compared to other established optimization algorithms and in all cases, it has been noticed that hybridization of two or more algorithms works better than stand-alone algorithms. Furthermore, none of the single optimization techniques can be established as being universally superior which aligns with no free lunch theorem. For future endeavor, combining optimization methods and exploiting multiple optimization processes for faster convergence and developing efficient proxy model is expected. © 2019 Elsevier Ltd

Item Type: Article
Impact Factor: cited By 13
Uncontrolled Keywords: Biomimetics; Covariance matrix; Gas industry; Genetic algorithms; Multiobjective optimization; Particle swarm optimization (PSO), Artificial intelligence techniques; Covariance matrix adaptation evolution strategies; Gradient-free optimizations; Meta-heuristic optimization techniques; Metaheuristic; Nonlinear problems; Reservoir simulation; Well placement optimization, Oil field development
Depositing User: Ms Sharifah Fahimah Saiyed Yeop
Date Deposited: 19 Aug 2021 05:27
Last Modified: 19 Aug 2021 05:27
URI: http://scholars.utp.edu.my/id/eprint/23088

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