Machine learning modelling and prediction of crude oil nanoemulsion viscosity under various conditions

Key Points

• This research aims to develop a machine learning model for predicting the viscosity of crude oil nanoemulsions across various conditions.
• Utilized machine learning algorithms to analyze data on crude oil nanoemulsion viscosity.
• Tested various environmental and compositional conditions affecting viscosity.
• Built predictive models to estimate viscosity changes.
• Successfully predicted viscosity changes in nanoemulsions with high accuracy.
• Identified key factors influencing viscosity, including temperature and composition.
• Demonstrated that machine learning can enhance understanding of crude oil properties.

Abstract