Petroleum Well Site Selection Using MCRAT Integrated with Rough Set Theory

Authors

  • Shaaban M. Shaaban Center for Scientific Research and Entrepreneurship , Northern Border University, 73213 Arar, Saudi Arabia
  • Anas M. El-Sherif Engineering College, Northern Border University, Arar 1321, Saudi Arabia
  • Ahmed A. Hammam General Courses Department, Northern Border University, Arar 1321, Saudi Arabia
  • Husham M. Attaalfadeel Department of Mathematics, College of Science, Northern Border University, Arar 91431, Saudi Arabia
  • Yehya I. Mesalam Department of Industrial Engineering, College of Engineering, Northern Border University, Arar 1321, Saudi

DOI:

https://doi.org/10.29020/nybg.ejpam.v18i2.6049

Keywords:

Multi criteria decision making (MCDM), shale oil, multiple criteria ranking by alternative trace (MCRAT), rough set theory (RST)

Abstract

Shale Oil (SO) has emerged as an attractive additional supply of conventional crude oil throughout the world in recent years. Shale oil quality evaluation includes a variety of geochemical parameters. In this research, we propose a novel Integrated shale oil evaluation approach. This method firstly determines the relative weights of parameters using rough set theory. Finally, Multiple Criteria Ranking by Alternative Trace (MCRAT) technique is utilized to calculate the rank of Shale oil wells. Twenty-seven samples of shale oil were collected from various distinct well sites. Twelve different geochemical parameters were examined in the gathered samples in order to determine the grade of the shale oil. The results reveal that shale oil sample 17 geochemical parameters, with shale oil grade I is the best collection parameters concentrations. The suggested approach is compared to five Multi-Criteria Decision Making (MCDM) approaches to demonstrate its effectiveness. The obtained results gained by the MCRAT Integrated with Rough Set Theory (RST) is clear in ideas and easy in computation, which may be effectively applied to address a variety of problems, both similar and different.

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Published

2025-05-01

Issue

Vol. 18 No. 2: (April 2025)

Section

Approximation Theory

License

Copyright (c) 2025 Shaaban M. Shaaban, Anas M. El-Sherif , Ahmed A. Hammam, Husham M. Attaalfadeel, Yehya I. Mesalam

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How to Cite

Petroleum Well Site Selection Using MCRAT Integrated with Rough Set Theory. (2025). European Journal of Pure and Applied Mathematics, 18(2), 6049. https://doi.org/10.29020/nybg.ejpam.v18i2.6049