| Autor: |
Syed Imran Ali, Shaine Mohammadali Lalji, Saud Hashmi, Zahoor Awan, Amjad Iqbal, Essam A. Al-Ammar, Anaiz gull |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
Ain Shams Engineering Journal, Vol 15, Iss 1, Pp 102289- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2090-4479 |
| DOI: |
10.1016/j.asej.2023.102289 |
| Popis: |
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 multi-criteria 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. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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