Understanding the Significance of Microporosity in Pore-Scale Fluid Flow Modelling Within Carbonate Reservoirs Using Multiscale Pore Networks

Pore network modelling, due to its computation efficiency, is a widely used technique in digital rock physics for predicting reservoir properties such as porosity, permeability, Capillary pressure and relative permeability at the pore scale. Instead, Pore network extraction depends on the quality of the image acquired using X-ray micro-computed tomography. Despite all the development in computed tomography techniques, there still exists a trade-off between image resolution and field of view. Particularly in carbonate reservoir rocks, heterogeneities exist at different scales and pore size ranges from submicron to several millimetres. Hence, it is rather impossible to obtain a single-scale image that can represent the sample's microstructure and, therefore, the pore network.

In this study, we have obtained a micro-CT image of a core plug at multiscale (resolution) to extract micro and macro networks, which resolved the microporosity and macrostructure of the sample. In this process, a pore network is extracted for multiresolution image data after applying preprocessing methods for contrast enhancement, artifacts and noise removal from original data. The extracted network at multiscale is then used to generate a stochastically equivalent network based on the extracted micro-network properties with a larger field of view.

Pore networks obtained after merging micro and macro networks are used to investigate the impact of microporosity on fluid flow in carbonate reservoir rock of the Miocene age by simulating primary drainage and imbibition processes in a network with micropores. In order to validate the results of the numerical simulations, we compare our results with available laboratory measurements at the core scale.