Experimental studies of both drainage and imbibition displacements are needed to improve our fundamental understanding of multi-phase flow and trapping in CO2-brine systems and effectively take advantage of the large storage capacity of saline aquifers. Very few relative permeability measurements have been made and even fewer with in situ saturation measurements. Two new sets of steady state relative permeability measurements have been made in two different rock samples, and over a range of injection flow rates. These studies show that multi-phase brine displacement efficiency is strongly affected by the heterogeneity of the core. Moreover, we observe that, at any given fractional flow, different flow rates result in different CO2 saturations. Similarly, different flow rates lead to different relative permeability curves. Numerical simulations of two phase displacement are performed on one sample, and at one fractional flow of CO2. Numerical simulations demonstrate that some of the features of the saturation distributions can be qualitatively replicated. However, improvements in the correlations between porosity, saturation and capillary pressure will be needed to replicate the saturation distributions measured in the experiments

Summary: Saline-aquifer storage of carbon dioxide (CO2) has become recognized as an important strategy for climate-change mitigation. Saline aquifers have very large estimated storage capacities, are distributed broadly across the globe, and have the potential for geologic-scale retention times. Many of these storage sites are not well characterized, and it is critical to conduct detailed experiments and analysis to understand how features such as heterogeneity can influence the theoretical storage capacity, spatial extent of plume migration, and secondary trapping processes. Coreflooding experiments are used routinely by the oil and gas industry for such analysis and provide a very useful tool for studying saline-aquifer formations also. Numerical simulations of these coreflooding experiments can provide insight beyond the experimental measurements themselves, such as numerically studying how properties such as relative permeability and capillary pressure affect CO2 distribution in these systems under various flow conditions. However, accurate subcore-scale simulations of these experiments have remained a challenge, and the issue of how to represent subcorescale permeability has not been resolved previously. Laboratory coreflooding experiments injecting CO2 into a saline-water-saturated Berea sandstone core have been conducted at reservoir conditions. Computed-tomography (CT) scans of the core show large spatial variations of CO2 saturation, even within a relatively homogeneous core. Numerical simulations of the experiment have been conducted to study the effect of subcorescale heterogeneity and the role of permeability in determining the subcore-scale CO2 distribution in the core to explain these very large spatial variations in CO2 saturation. Numerical simulations of the experiment consistently showed that use of traditional methods for estimating subcore-scale permeability, typically based solely on porosity distributions, results in subcore-scale saturation distributions that do not match experimental measurements. In this paper, we develop a new method for calculating subcore-scale permeability distributions on the basis of capillary pressure measurements and porosity distributions as an alternative to the traditional porosity-only-based models. Using experimentally measured saturation and porosity distributions and capillary pressure data to calculate permeability, simulations based on this new method show a substantial improvement both in the absolute value and in the spatial distribution of predicted CO2-saturation values. With this technique for accurately calculating permeability distributions, it is possible to study subcore-scale multiphase flow of brine and CO2 to understand how small-scale heterogeneities influence the spatial distribution of CO2 saturation and to improve our ability to predict the fate of stored CO2.