Mapping fluid distributions in 3D at the pore scale: Quantifying the influence of wettability and saturation history on rock resistivity

Complexities in pore scale structure, rock-fluid and fluid-fluid interactions have a profound effect on the estimation of reserves, reservoir recovery and productivity in reservoir core material. These complexities determine the pore scale distribution of fluids within the pore space, which, in turn, determine the petrophysical response of the rock. A very important example is the estimation of water saturation via resistivity measurements. Default saturation exponents (n=2) are often used in estimating saturations despite numerous measurements which have shown that n can depend strongly on the rock type, mineralogy, saturation history and wettability. NonArchie behavior is reported frequently. Experimental laboratory results for the resistivity response of clastic and carbonate reservoir cores under varying wettability states have exhibited a range of saturation exponents; 1<n<6. Understanding the resistivity response of reservoir cores requires an ability to accurately map the pore scale structure and the fluid distributions in 3D within core material under variable wettability states and based on different saturation history. We use an image registration technique which allows voxel perfect overlays of 3D tomographic images of the same core sample at varying saturation states. The method allows one to explicitly visualize the experimental two-phase fluid distributions within reservoir core material at the pore scale. The ability to perform multiple experiments on the same core and to accurately compare their fluid distributions at the pore scale allows one to probe the (potentially competing) roles of complex rock structure, rock type, wettability and saturation history on the resistivity response. Reasons for non-Archie behavior can be explained from the direct visualization of pore scale fluid distributions. This understanding can lead to more accurate predictions of in-situ fluid saturations within reservoir core. The technique can also be applied to the prediction of other petrophysical and multiphase flow properties (e.g., recoveries, relative permeability).