- Inaccurate petrophysical rock typing is a major factor leading to the failure of many Enhanced Oil Recovery (EOR) projects worldwide. Effective reservoir characterization is crucial for guiding field development plans. Hydraulic Flow Unit (HFU) techniques are typically used to model the petrophysical properties of reservoirs, thus aiding improved oil recovery projects. Various models have been developed to describe reservoirs based on available data, often relying on assumptions about the porous medium, such as cementation factor and connate water saturation. These assumptions can be inaccurate and yield inconsistent rock-type classifications within the same medium, leading to unrealistic results when applied from cored to uncored wells. This study introduced a new approach for better-characterizing sandstone and carbonate reservoirs by leveraging the porosity-permeability relationship exclusively, avoiding the need for traditional petrophysical assumptions. The new approach was derived from a permeability equation developed for several pipes in series, and it utilizes a modified normalized porosity, a modified Flow Zone Indicator (FZI), and a Reservoir Quality Index (RQI). The methodology involved detailed analysis and comparison with existing approaches for identifying HFUs and predicting permeability. The new approach demonstrated superior performance, achieving higher correlation coefficients for predicted permeability in both carbonate and sandstone reservoirs. Specifically, the method showed correlation coefficients of 0.95 for carbonate and 0.93 for sandstone reservoirs, compared to 0.85 and 0.82, respectively, for existing methods. Additionally, it identified HFUs with higher accuracy, evidenced by correlation coefficients of 0.92 for carbonate and 0.90 for sandstone reservoirs, as opposed to 0.80 and 0.78 for conventional methods. By eliminating the reliance on inaccurate petrophysical assumptions, this approach enhances the reliability of reservoir characterization, making it a valuable tool for optimizing EOR projects. Further research will explore the applicability of this method across different reservoir types and conditions to fully establish its robustness and versatility.