Machine learning models for estimating the overall oil recovery of waterflooding operations in heterogenous reservoirs

Machine learning models for estimating the overall oil recovery of waterflooding operations in heterogenous reservoirs

Abstract Waterflooding is the most widely used improved oil recovery technique. Predicting the overall oil recovery resulting from waterflooding in oil reservoirs is crucial for effective reservoir management and appropriate decision-making. Machine learning (ML) techniques present resourceful and f...

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Bibliographic Details
Main Authors: Sayed Gomaa, Ahmed Ashraf Soliman, Mohamed Mansour, Fares Ashraf El Salamony, Khalaf G. Salem
Format: Article
Language:English
Published: Nature Portfolio 2025-04-01
Series:Scientific Reports
Subjects:
Waterflooding
Oil recovery
Machine learning
Artificial neural network
Mobility ratio
Reservoir permeability variation
Online Access:https://doi.org/10.1038/s41598-025-97235-5
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