Characterization of Fluid Drainage Mechanism at Core and Pore Scales: an NMR Capillary Pressure–Based Saturation Exponent Prediction

Abstract

Capillary pressure (Pc) and electrical resistivity index (RI) curves are used in many reservoir engineering applications. Drainage capillary pressure curve represents a scenario where a non-wetting phase displaces a wetting phase such as (i) during gas injection (ii) gas storage in reservoirs (e.g. aquifer or depleted hydrocarbon reservoirs). The gas used for injection is typically natural gas, N₂, or CO₂. Gas storage principally used to meet requirement variations, and water injection into oil-wet reservoirs are drainage processes. Resistivity index (RI) curve which is used to evaluate the potential of oil recovery from a reservoir, is also an important tool used in log calibration and reservoir fluid typing. The pore drainage mechanism in a multimodal pore system is important for effective recovery of hydrocarbon reserves; enhance oil recovery (EOR) planning and underground gas storage. The understanding of pore structure and drainage mechanism within a multimodal pore system during petrophysical analysis is of paramount importance to reservoir engineers. Therefore, it becomes inherent to study and establish a way to relate these special core analyses laboratory (SCAL) methods with quick measurements such as the nuclear magnetic resonance (NMR) to reduce the time requirement for analysis. This research employed the use of nuclear magnetic resonance (NMR) to estimate saturation exponent (n) of rocks using nitrogen as the displacing fluid. Different rock types were used in this study that cover carbonates, sandstones, and dolomites. We developed an analytical workflow to separate the capillary pressure curve into capillary pressure curve for macropores and a capillary pressure curve for the micropores, and then used these pore scale Pc curves to estimate an NMR - capillary pressure - based electrical resistivity index - saturation (NMR-RI-Sw) curve for the rocks. We predicted the saturation exponent (n) for the rock samples from the NMR-RI-Sw curve. The NMR-based saturation exponent estimation method requires the transverse (T₂) relaxation distribution of the rock - fluid system at various saturations. To verify the reliability of the new workflow, we performed porous plate capillary pressure and electrical resistivity measurements on the rock samples. The reliability of the results for the resistivity index curve and the saturation exponent was verified using the experimental data obtained from the SCAL method. The pore scale Pc curve was used to ascertain the drainage pattern and fluid contribution of the different pore subsystems. For bimodal rock system, the drainage mechanism can be in series, in parallel, or in series - parallel depending on the rock pore structure.