Anomalous Transport in Carbonate Rock - Predictions and Quantitative Measures

Solute transport in rock subsurface is important in a number of applications such as contaminant hydrology, carbon storage and enhanced oil recovery. Carbonate rock contain most of the world's oil reserves and potentially hold a storage capacity for carbon dioxide. Pore structure in carbonate rock introduces an additional complexity in the form of bimodal pore size distributions, which leads to complex anomalous transport behavior and poses a significant challenge for accurate predictions. We present a new modeling concept that simulates flow and transport on micro-CT images containing the information on inter- and intra-grain pore space of carbonate rock. Navier-Stokes equations are solved for flow in the image voxels comprising the pore space, streamline-based simulation is used to account for advection, and diffusion is superimposed by random walk. Firstly, the model is validated against the experimental NMR measurements in the dual porosity beadpack. Furthermore, the model predictions are made for a number of carbonate rock images which are then classified in terms of heterogeneity of the inter- and intra-grain pore space, heterogeneity in the flow field, and the mass transfer characteristics of the porous media. Finally, we demonstrate the predictive capabilities of the model through an analysis that includes a number of probability density functions (PDFs) measures of non-Fickian transport on the micro-CT images.