Use of AI tools to understand and model surface-interaction based EOR processes2022

– The paper focuses on using AI tools to understand and model surface-interaction based EOR processes.
– The research analyzes different parameters and their impact on the outcome of the EOR process.

10.1016/j.acags.2022.100111

In this article , the authors used several data analysis methods followed by use of machine learning methods (a subset of AI) are used to analyse the different parameters and their impact on the outcome of the EOR process.

– AI tools are used to understand and model surface-interaction based EOR processes.
– Key parameters for the success of this EOR process are determined.

– AI and computational technology are revolutionizing interior design graphics and modeling.
– These technologies offer benefits such as design iterations, material visualization, and time optimization.

– AI tools can be used to understand and model surface-interaction based EOR processes.
– Key parameters for the success of the EOR process are brine composition, salinity, oil API, and wettability.

– Use of AI tools to understand and model surface-interaction based EOR processes
– Determination of key parameters for the success of the EOR process

AI tools are used in this research to understand, model, and screen the surface-interaction based EOR process.

– Data analysis methods
– Machine learning methods (subset of AI)

– AI tools can help understand and model EOR processes
– AI tools can be used for screening EOR technologies

– The paper discusses the use of AI tools in disinformation.
– AI tools will make disinformation more potent.

– AI tools are used to understand and model surface-interaction based EOR processes.
– Key parameters for the success of the EOR process are determined.

– EOR is a tertiary recovery strategy for oilfields.
– AI tools used to understand and model EOR processes.