A Modified Niching Crow Search Approach to Well Placement Optimization

Jahedul Islam, Md Shokor A. Rahaman, Pandian M. Vasant, Berihun Mamo Negash, Ahshanul Hoqe, Hitmi Khalifa Alhitmi and Junzo Watada
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Jahedul Islam: Fundamental and Applied Sciences Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia
Md Shokor A. Rahaman: Shale Gas Research Group, Institute of Hydrocarbon Recovery, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia
Pandian M. Vasant: Fundamental and Applied Sciences Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia
Berihun Mamo Negash: Petroleum Engineering Department, Universiti Teknologi PETRONAS, Seri Iskandar 32610, Perak Darul Ridzuan, Malaysia
Ahshanul Hoqe: Electrical & Electronic Engineering Department, Chittagong University of Engineering and Technology, Chittagong 4349, Bangladesh
Hitmi Khalifa Alhitmi: College of Business and Economics, Qatar University, Doha 00974, Qatar
Junzo Watada: Department of Computer & Information Sciences, Universiti Teknologi Petronas, Seri Iskandar 32610, Perak, Malaysia

Energies, 2021, vol. 14, issue 4, 1-33

Abstract: Well placement optimization is considered a non-convex and highly multimodal optimization problem. In this article, a modified crow search algorithm is proposed to tackle the well placement optimization problem. This article proposes modifications based on local search and niching techniques in the crow search algorithm (CSA). At first, the suggested approach is verified by experimenting with the benchmark functions. For test functions, the results of the proposed approach demonstrated a higher convergence rate and a better solution. Again, the performance of the proposed technique is evaluated with well placement optimization problem and compared with particle swarm optimization (PSO), the Gravitational Search Algorithm (GSA), and the Crow search algorithm (CSA). The outcomes of the study revealed that the niching crow search algorithm is the most efficient and effective compared to the other techniques.

Keywords: non-convex; crow search algorithm; well placement optimization; multimodal optimization; niching crow search algorithm (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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