Enhancing Fluid Characterization and Pore Fluid Content Accuracy Through Integrated Formation Water Resistivity Analysis: A Case Study

Fluid characterization and saturation modeling are foundational to effective field development, particularly in carbonate reservoirs where water chemistry is highly variable and dynamic. This paper presents a case study from a carbonate field in Oman, where uncertainties in determining Formation Water Resistivity (Rw) significantly impacted water saturation estimates and fluid property modeling. To address these challenges, an integrated calibration workflow was developed, combining surface water sample analysis, salinity profiling, and wireline log interpretation. Laboratory measurements—including total dissolved solids, ionic concentrations, and resistivity—were used to assess formation conditions and identify geochemical trends. Special attention was given to salinity variations influenced by hydrodynamic gradients and proximity to disposal wells. The study revealed a broad range of Rw values across the field, with notable discrepancies between laboratory and log-derived estimates. These differences were most pronounced in wells affected by water disposal activities, where contamination and salinity gradients distorted sample readings. A refined Rw model was constructed through zonal adjustments and contamination screening, resulting in improved alignment between calculated and observed saturation endpoints. This enhanced model significantly reduced uncertainty in hydrocarbon volume forecasts, particularly in low-quality zones with marginal net pay. Recognizing the evolving nature of formation water chemistry, a time-lapse fluid monitoring program was initiated to track changes in ionic composition over time. This ongoing effort aims to further refine the Rw model and ensure its adaptability to dynamic reservoir conditions. The study demonstrates that a robust and evolving Rw framework not only improves saturation accuracy but also strengthens the reliability of fluid property models, offering a scalable solution for complex carbonate reservoirs and long-term development planning. This paper demonstrates how Rw calibration can be a critical enabler for accurate fluid property modeling. The new Rw approach bridges the gap between real samples and log data, creating a stronger basis for reserves estimation. The method is adaptable to reservoirs with variable water salinity and hydrodynamic complexity, offering a field-ready framework to enhance confidence in development planning and long-term production forecasting.