Abstract Recent studies have demonstrated that residual oil zones (ROZ) below the free water level (FWL) in carbonate reservoirs can contain significant volumes of oil that are not recoverable by conventional methods but may be mobilized through enhanced oil recovery (EOR) techniques such as CO2 or water injection. However, most previous work has treated the ROZ as a single, undifferentiated interval, without detailed characterization of sub-category or direct integration of dynamic data. In this study, we present an integrated workflow for evaluating the oil potential within the ROZ of a giant offshore carbonate field in Abu Dhabi, utilizing a combination of Movable Hydrocarbon Index (MHI), water saturation (Sw) logs, fluid identification (FID), wettability measurements, and pressure data. By correlating these datasets, we subdivide the ROZ with wetting phase and clarify the depth distribution of each. Our results reveal that significant intervals containing potentially movable oil exist below the current FWL, with their distribution closely linked to wettability transitions and pressure inflections. This approach enables more accurate net pay estimation and provides a practical basis for optimizing EOR strategies in heterogeneous carbonate reservoirs. The findings highlight the importance of integrating static and dynamic data for detailed ROZ characterization, moving beyond the limitations of previous studies.
Accurate characterization of CO₂-brine relative permeability and residual trapping is essential to design reliable carbon sequestration in geological formations. This study presents an integrated workflow that combines special core analysis (SCAL), digital rock physics (DRP) and pore-network modeling (PNM). This workflow is used to quantify and accurately assess the multiphase flow and capillary trapping of CO₂ in reservoir sandstones under subsurface-relevant conditions. This approach links pore-scale mechanisms with core-scale behavior using high-resolution X-ray micro-computed tomography (micro-CT) to capture pore structures, fluid configuration and wettability, alongside PNM. The good agreement between the SCAL and DRP experimental results ensures consistent macroscopic flow properties for the two experiments conducted at different length scales. Both experimental results indicate limited CO₂ mobility in water-wet systems during drainage where limited viscous force is applied. The distribution of CO₂ ganglia volume obtained from micro-CT imaging narrows considerably after waterflooding, indicating successful CO₂ capillary trapping. Furthermore, PNM is used to match the measured relative permeability and capillary trapping. This matched PNM can then be used to predict conditions that are difficult to achieve experimentally, such as reaching the maximum CO₂ saturation after drainage and multiple hysteresis cycles to determine the Land trapping curve. The integrated workflow advances the mechanistic understanding of CO₂ transport and immobilization in geological formations, offering a robust tool for optimizing carbon storage strategies.
