A Pressure-Driven Recovery Factor Equation for Enhanced Oil Recovery Estimation in Depleted Reservoirs: A Practical Data-Driven Approach

This study presents a new equation, the dynamic recovery factor ( DRF ), for evaluating the recovery factor ( RF ) in homogeneous and heterogeneous reservoirs. The DRF method’s outcomes are validated and compared using the decline curve analysis (DCA) method. Real measured field data from 15 wells in a homogenous sandstone reservoir and 10 wells in a heterogeneous carbonate reservoir are utilized for this study. The concept of the DRF approach is based on the material balance principle, which integrates several components (weighted average cumulative pressure drop (Δ P cum ), total compressibility ( C t ), and oil saturation ( S o )) for predicting RF. The motivation for this study stems from the practical restrictions of conventional RF valuation techniques, which often involve extensive datasets and use simplifying assumptions that are not applicable in complex heterogeneous reservoirs. For the homogenous reservoir, the DRF approach predicts an RF of 8%, whereas the DCA method predicted 9.2%. In the heterogeneous reservoir, the DRF approach produces an RF of 6% compared with 5% for the DCA technique. Sensitivity analysis shows that RF is very sensitive to variations in C t , Δ P cum , and S o , with values that vary from 6.00% to 10.71% for homogeneous reservoirs and 4.43% to 7.91% for heterogeneous reservoirs. Uncertainty calculation indicates that errors in C t , Δ P cum , and S o propagate to RF , with weighting factor ( W i ) uncertainties causing changes of ±3.7% and ±4.4% in RF for homogeneous and heterogeneous reservoirs, respectively. This study shows the new DRF approach’s ability to provide reliable RF estimations via pressure dynamics, while DCA is used as a validation and comparison baseline. The sensitivity analyses and uncertainty analyses provide a strong foundation for RF estimation that helps to select well-informed decisions in reservoir management with reliable RF values. The novelty of the new DRF equation lies in its capability to correctly estimate RFs using limited available historical data, making it appropriate for early-stage development and data-scarce situations. Hence, the new DRF equation is applied to various reservoir qualities, and the results show a strong alignment with those obtained from DCA, demonstrating high accuracy. This agreement validates the applicability of the DRF equation in estimating recovery factors through different reservoir qualities.