Abstract

The microstructure of carbonate rocks experiences substantial changes under reactive processes, in particular chemical dissolution and deposition including dissolution-released fines migration occurring during acidizing. A better understanding of such changes at the pore scale and their influences on rock properties is of great value for the effective design and implementation of reactive processes in carbonate reservoirs. In this work, we demonstrate the use of X-ray micro-computed tomography (μ-CT) to quantitatively investigate the local porosity changes in a meso/microporous carbonate core sample during chemical dissolution. A reactive flooding experiment in a core sample by a non-acidic solution is designed such that changes in pore space from before to after the reactant injection could be imaged in exactly the same locations using μ-CT at resolution of less than 5μm. A methodology based on three-phase segmentation and 2D intensity histograms of images is used to quantify distributions of the evolution of each image voxel. This technique allows the incorporation of microporosity into the calculation of the evolution regions including the migration of fines in order to accurately quantify the evolution scenarios. The µ-CT images reveal a quasi-uniform dissolution pattern and allow characterizing the accompanying migration of fines within the core sample. 3D pore networks are derived from the image data, which quantify changes in network structure and the pore geometry. 2D histograms of image intensity derived from the pre- and post-dissolution images quantitatively show how macro and micropores are enlarged by dissolution close to the inlet while deposition of fines mainly occurs in pores far from the inlet boundary. These results can explain why permeability of the sample initially decreases and then increases as injection time increases. Based on the spatially resolved voxel evolution scenarios, pore surface area between each region is computed. This allows calculation of local distribution of reactive surface area which in turn will assist in the prediction of local reaction rates in reactive flow simulators.

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