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Risk quantification and ranking of oil fields and wells facing asphaltene deposition problem using fuzzy TOPSIS coupled with AHP
被引:10
|作者:
Ali, Syed Imran
[1
]
Lalji, Shaine Mohammadali
[1
]
Hashmi, Saud
[2
]
Awan, Zahoor
[6
]
Iqbal, Amjad
[3
]
Al-Ammar, Essam A.
[4
]
Gull, Anaiz
[5
]
机构:
[1] NED Univ Engn & Technol, Dept Petr Engn, Karachi, Pakistan
[2] NED Univ Engn & Technol, Dept Chem Engn, Karachi, Pakistan
[3] Silesian Tech Univ, Fac Mat Engn, Dept Mat Technol, PL-44100 Gliwice, Poland
[4] King Saud Univ, Coll Engn, Dept Elect Engn, POB 800, Riyadh 11421, Saudi Arabia
[5] Univ Karachi, Dept Petr Technol, Karachi 75270, Pakistan
[6] NED Univ Engn & Technol, Dept Food Engn, Karachi, Pakistan
关键词:
Asphaltene;
Wells;
Risk Ranking;
Multi-criteria decision making;
Fuzzy Technique for Order of Preference by;
Similarity to Ideal Solution;
CRUDE-OIL;
PRECIPITATION;
STABILITY;
FLOCCULATION;
PREDICTION;
PRESSURE;
ONSET;
D O I:
10.1016/j.asej.2023.102289
中图分类号:
T [工业技术];
学科分类号:
08 ;
摘要:
Asphaltene precipitation and its subsequent deposition always remain a major concern for Oil industry. Formulation of a comprehensive and reliable risk management system for asphaltene prone wells and fields is a challenging task because of the influence of diverse factors. In this study, a decision support system is developed for the asphaltene risk assessment in wells and fields. Since, the data present in the literature is scarce and not consistent, therefore, a hypothetical data of fields and their wells was considered to conduct the study comprehensively. Three hypothetical fields namely; Field A, Field B and Field C were assumed and in each field ten wells were taken into consideration. A decision support system for assessing the risk of asphaltene prone wells was developed using one of the popular and powerful multicriteria decision making technique i.e. Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (Fuzzy TOPSIS) coupled with Analytic Hierarchy process (AHP). The risk of wells was evaluated using three criteria namely; Detection, Severity and Controls. These criteria were further sub-divided into sub-criteria and their data was assumed. The assumed data was transformed into Triangular fuzzy numbers for calculations. According to the final outcomes, Field A was proved be the most risky field followed by Field B and in the last comes Field C. The outcomes were further validated by other method namely; Fuzzy Complex Proportional Assessment (COPRAS) and all TOPSIS outcomes were found in good relationship with Fuzzy COPRAS. The proposed methodology proposed in this study will be landmark in risk ranking of asphaltene prone wells and fields. (c) 2023 THE AUTHORS. Published by Elsevier BV on behalf of Faculty of Engineering, Ain Shams University. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
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