Research on the main control factors of carbon dioxide flooding and storage based on random forest algorithm

Abstract

Objective To achieve carbon peak and carbon neutrality goals, carbon dioxide flooding and storage are the main technical means for carbon emission reduction. It is crucial to clarify the main controlling factors of carbon dioxide flooding and storage under reservoir conditions, which provides the basis for realizing the efficient development of carbon dioxide flooding and storage. Methods In this study, with the widely used PUNQ-S3 case study as the basis, an integrated numerical simulation model of carbon dioxide flooding and geological storage is constructed. It considers the miscible interaction between carbon dioxide and crude oil as well as storage mechanisms, including structural, residual, dissolved, and mineral trapping. By employing the random forest intelligent algorithm, a feature importance analysis of reservoir and production parameters during the carbon dioxide flooding and storage process is carried out. The differences between carbon dioxide flooding and storage at different time scales are considered. A time series-based feature importance analysis method is established, and the main controlling factors in the different carbon dioxide flooding and storage stages are analysed. Through the fluctuation of the evaluation index, the influence of reservoir and production parameters on different stages of carbon dioxide flooding and storage is inferred. Results The results show that the time series-based random forest model for carbon dioxide flooding and storage has high accuracy. In the early stage of carbon dioxide flooding and storage, the amount of carbon dioxide structural storage is controlled by the reservoir water saturation, and the amount of dissolved storage is controlled by the salinity of the formation brine; In the middle and later stages of carbon dioxide flooding and storage, the amount of carbon dioxide structural storage is controlled by reservoir permeability, while the amount of dissolved storage is controlled by reservoir permeability and formation water salinity; The residual storage capacity is small in the early stage of carbon dioxide flooding and storage, resulting in unclear main controlling factors.In the later stage of carbon dioxide flooding and storage, it is controlled by reservoir permeability and water saturation; The amount of mineralization storage is controlled by the pH value and the salinity of the formation brine throughout the entire CO2 flooding and storage stage; The amount of carbon dioxide production is controlled by reservoir permeability and water saturation throughout the entire carbon dioxide flooding and storage stage. Conclusion The time-series-based random forest algorithm can identify the main controlling factors of different carbon dioxide flooding and storage stages and can provide support for cimproving crude oil recovery and implementing efficient geological storage with carbon dioxide.

Keywords

• carbon dioxide flooding and storage
• random forest algorithm
• feature importance analysis
• oil recovery
• numerical simulation
• salinity of formation brine
• reservoir