Developing a cost-effective tool for choke flow rate prediction in sub-critical oil wells using wellhead data

Developing a cost-effective tool for choke flow rate prediction in sub-critical oil wells using wellhead data

Abstract Accurate prediction of oil production rates through wellhead chokes is critical for optimizing crude oil production and operational efficiency in the petroleum industry. The central thrust of this investigation involves the systematic creation of machine learning (ML) paradigms for the robu...

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Main Authors: Zhiwei Xun, Farag M. A. Altalbawy, Prakash Kanjariya, R. Manjunatha, Debasish Shit, M. Nirmala, Ajay Sharma, Sarbeswara Hota, Shirin Shomurotova, Fadhil Faez Sead, Hojjat Abbasi, Mohammad Mahtab Alam
Format: Article
Language:English
Published: Nature Portfolio 2025-07-01
Series:Scientific Reports
Subjects:
Choke flow modeling
Machine learning
Crude oil production
Optimization
SHAP analysis
Online Access:https://doi.org/10.1038/s41598-025-10060-8
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https://doi.org/10.1038/s41598-025-10060-8

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