A Prediction Method for Technically Recoverable Reserves Based on a Novel Relationship Between the Relative Permeability Ratio and Saturation

Upon reaching stabilized production in waterflooded reservoirs, waterflood performance curves are conventionally used to predict technically recoverable reserves (TRRs). However, as reservoirs enter high water-cut stages, the relationship between the relative permeability ratio and saturation becomes nonlinear, causing deflection in waterflood performance curves. This leads to systematic overestimation of both predicted TRR and ultimate recovery factors. To overcome these limitations in conventional TRR prediction methods, this study establishes a novel relative permeability ratio-saturation relationship based on characteristic relative permeability curve behaviors. The proposed model is validated for three distinct fluid-rock interaction types. We further develop a permeability-driven forecasting model for oil production rates and water cuts. Comparative analyses with a conventional waterflood curve methodology demonstrate significant accuracy improvements. The results show that while traditional methods predict TRR ranging from 78.40 to 92.29 million tons, our model yields 70.73 million tons—effectively resolving overestimation issues caused by curve deflection during high water-cut phases. This approach establishes a robust framework for determining critical development parameters, including economic field lifespan, strategy adjustments, and ultimate recovery factor.