Agwu, Okorie Ekwe and Okoro, Emeka Emmanuel and Sanni, Samuel Eshorame (2022) Modelling oil and gas flow rate through chokes: A critical review of extant models. Journal of Petroleum Science and Engineering, 208.
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Abstract
Oil and gas metering is primarily used as the basis for evaluating the economic viability of oil wells. Owing to the economic implications of oil and gas metering, the subject of oil and gas flow rate measurement has witnessed a sustained interest by the oil and gas community and the academia. To the best of the authors’ knowledge, despite the growing number of published articles on this subject, there is yet no comprehensive critical review on it. The objective of this paper is to provide a broad overview of models and modelling techniques applied to the estimation of oil and gas flow rate through chokes while also critically evaluating them. For the sake of simplicity and ease of reference, the outcomes of the review are presented in tables in an integrated and concise manner. The articles for this review were extracted from many subject areas. For the theoretical pieces related to oil and gas flow rate in general, the authors relied heavily upon several key drilling fluid texts. For operational and field studies, the authors relied on conference proceedings from the society of petroleum engineers. These sources were supplemented with articles in peer reviewed journals in order to contextualize the subject in terms of current practices. This review is interspersed with critiques of the models while the areas requiring improvement were also outlined. Findings from the bibliometric analysis indicate that there is no universal model for all flow situations despite the huge efforts in this direction. Furthermore, a broad survey of literature on recent flow models reveals that researchers are gravitating towards the field of artificial intelligence due to the tremendous promises it offers. This review constitutes the first critical compilation on a broad range of models applied to predicting oil and gas flow rates through chokes.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Artificial intelligence Multiphase flow Ensemble models Non-linear regression Sensors Wellhead chokes |
| Subjects: | T Technology > T Technology (General) T Technology > TP Chemical technology |
| Divisions: | Faculty of Engineering, Science and Mathematics > School of Engineering Sciences |
| Depositing User: | nwokealisi |
| Date Deposited: | 29 Nov 2023 12:04 |
| Last Modified: | 29 Nov 2023 12:04 |
| URI: | http://eprints.covenantuniversity.edu.ng/id/eprint/17647 |
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