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A Modified Niching Crow Search Approach to Well Placement Optimization

Author

Listed:
  • 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)

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.

Suggested Citation

  • Jahedul Islam & Md Shokor A. Rahaman & Pandian M. Vasant & Berihun Mamo Negash & Ahshanul Hoqe & Hitmi Khalifa Alhitmi & Junzo Watada, 2021. "A Modified Niching Crow Search Approach to Well Placement Optimization," Energies, MDPI, vol. 14(4), pages 1-33, February.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:4:p:857-:d:494836
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    References listed on IDEAS

    as
    1. Primitivo Díaz & Marco Pérez-Cisneros & Erik Cuevas & Omar Avalos & Jorge Gálvez & Salvador Hinojosa & Daniel Zaldivar, 2018. "An Improved Crow Search Algorithm Applied to Energy Problems," Energies, MDPI, vol. 11(3), pages 1-22, March.
    2. Mao, Kun & Pan, Quan-ke & Pang, Xinfu & Chai, Tianyou, 2014. "A novel Lagrangian relaxation approach for a hybrid flowshop scheduling problem in the steelmaking-continuous casting process," European Journal of Operational Research, Elsevier, vol. 236(1), pages 51-60.
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