Research on Well Selection Method for Intermittent Pumping in Oil Wells Based on the Analytic Network Process and Fuzzy Logic
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Le résumé fourni par la source
In the later stages of oilfield development, the decline in oil well production and the increase in development costs, attributed to issues such as insufficient liquid supply, necessitate the implementation of intermittent pumping measures. However, current methods for selecting these wells lack comprehensiveness in the decision-making process. This article proposes a novel method for selecting intermittent pumping wells utilizing the analytic network process (ANP) and fuzzy logic. Initial surveys identified the main factors influencing intermittent pumping effectiveness. The ANP was employed to screen and integrate six core factors, including submergence depth and water cut. Subsequently, a fuzzy-logic-based model was developed, incorporating trapezoidal and rectangular membership functions to establish detailed correlations among the factors. The model’s efficacy was validated and tested using real-world data from the oilfield. Results indicate that the model’s assessments of intermittent pumping wells align closely with professional engineering judgments. This approach not only provides clear guidance for well selection but also demonstrates high scalability and adaptability across different oilfields by adjusting membership functions, thereby showcasing significant practical value.
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Le contrôle bibliographique ouvert
DOI retrouvé dans Crossref DOI retrouvé ; titre concordant.
- Titre Crossref
- Research on Well Selection Method for Intermittent Pumping in Oil Wells Based on the Analytic Network Process and Fuzzy Logic
- Date Crossref
- 15/11/2024
- Éditeur
- MDPI AG
- Type
- journal-article
Ce recoupement confirme des métadonnées liées au DOI. Il ne confirme ni la méthode ni les conclusions de l’étude, et il ne compte pas comme une seconde source scientifique indépendante.
Où se fait cette recherche
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Changzhou University pays non établi dans la noticeUniversité ou école supérieure
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Digital China Health (China) pays non établi dans la noticeEntreprise
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School of Petroleum and Natural Gas Engineering pays non établi dans la noticeUniversité ou école supérieure
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Ltd. Beijing Zhinet Digital Technology Co. pays non établi dans la noticeEntreprise
Changzhou University, Digital China Health (China) et School of Petroleum and Natural Gas Engineering, avec 1 autre affiliation.
Une affiliation ne permet pas de déduire la nationalité d’un auteur.