Integrated Hierarchy–Correlation Model for Evaluating Water-Driven Oil Reservoirs

[Image: see text] With the increasing demands on energy and environmental domains, not only high oil production but also its accurate quantification has become one of the most important topics in academia and industry. This paper initially proposes a comprehensive workflow in which an integrated hierarchy–correlation model is used to thoroughly evaluate the influences of all relevant reservoir parameters on the ultimate oil recovery for water-flooding oil reservoirs. More specifically, the analytic hierarchy process, grey relation, and entropy weight are combined through the multiplicative weighting method to quantitatively describe the production parameters. Accordingly, novel multivariable linear and nonlinear correlations are developed to predict the production performance and validated through comparisons with numerical reservoir simulations. Seven factors, including five reservoir parameters, namely, permeability and its contrast, porosity, thickness, and saturation, and two production parameters, namely, the injection–production ratio and the operating pressure, have been identified as the most influential factors on recovery performances and thus are employed in the proposed correlations to predict the ultimate oil recovery factor. The results obtained by the proposed method are quite close to the real-time simulation data, while the accuracy is retained. The numerical results show that the recovery factors of water-flooding oil reservoirs are about 33.5–59.5%, and the corresponding linear and nonlinear correlation coefficients are 0.903 and 0.789, respectively. In comparison with the numerical simulation, the approximation error by the linear correlation is about 0.5%, which is lower than that of nonlinear correlation, for example, 12.3%. This study will be beneficial to analyze the reservoir-related parameters and provide a useful tool for rapid production performance evaluation of the water-flooding production scenario.