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

) values are 0.97, 0.95, and 0.80 and the RMSE scores are 0.0282, 0.0405, and 0.0629 on the validation dataset, respectively. The innovative application of such ML models demonstrates significant improvements in prediction accuracy and reliability, offering a robust solution for optimizing oil recovery processes. These machine learning models provide the industry and research with efficient and economical tools for accurately estimating oil recovery in waterflooding operations within heterogeneous reservoirs.