Enhancing Dynamic Reservoir Modelling Value with Quality-Assured Initialization Technique: A Case Study of Complex Tight Oil Reservoir

Abstract Discrepancies between static and dynamic reservoir models often arise due to differences in water saturation estimation methods. While static models rely on saturation height functions (SHF), dynamic models require laboratory-measured capillary pressure (Pc) curves to accurately represent water saturation for reservoir simulation. However, in tight oil reservoirs with extensive transition zones, acquiring sufficient Pc data is often impractical or even impossible. This study presents a novel methodology, successfully implemented in a tight oil field, to overcome the limitations of experimental Pc data availability and improve Field Development Planning (FDP). Our workflow begins with log-derived water saturation (Sw) to develop SHF for different rock types, ensuring precise rock-type characterization based on cored wells. These SHF curves are then transformed into Pc functions using height above the free water level (FWL) while incorporating rock quality indices. This approach was applied and validated through a real-world case study, where Pc-derived and log-derived Sw was compared, alongside statistical analysis, water volume consistency, and field-recorded production data during dynamic reservoir modelling. The strong alignment between modeled and observed field performance confirmed the robustness of this methodology. This case study demonstrates the effectiveness of integrating log-derived Sw and rock quality indices to initialize dynamic reservoir models when laboratory-measured Pc data is unavailable. By enabling reliable model calibration and improved history matching, this approach provides reservoir engineers with a practical and scalable solution for optimizing FDP in complex tight oil systems.