Abstract
Abstract It is well known that shale formations exhibit multi-scale geological features such as nanopores in the formation matrix and natural fractures at multiple length scales. The key challenge in unconventional reservoir simulations is thus how to preserve fine-scale information in coarse-scale reservoir simulations for correct production forecasting and reserve estimation. Accurate prediction of shale permeability using numerical tools requires understanding of transport mechanisms in nano-scale, and upscaling from nano-scale to larger scale simulations. In our recent work (URTeC: #2459219), we presented the coupling of the molecular dynamics (MD) simulation with the lattice Boltzmann method (LBM) on multiple-scale digital rocks to estimate the transport property of shale matrix in micrometer scale. As an extension, this work is aimed to develop an upscaling workflow that integrates nanometer-scale simulations, micrometer-scale simulations and centimeter-scale simulations. The proposed approach allows calculating macro-scale transport properties of natural gas in shales with significantly reducing the loss of critical fine-scale (nano-scale) information. The reconstructions of multi-scale shale digital rocks are performed using multiple imaging techniques, i.e. FIB-SEM, Nano-CT and Micro-CT. These experiments provide micro-scale pore architectures (∼nm), meso-scale mineralogical distribution (∼μm), and macro-scale natural-fracture network (∼cm), respectively. These multi-scale digital rock reconstructions are then utilized for the investigations of multi-scale transport properties of gas shales. This upscaling process can be summarized as the following three steps. (1) nano-scale transport properties in organic and inorganic structures are calculated using the non-equilibrium MD simulations. Representative organic (kerogen) and inorganic clay (montmorillonite) molecules are built upon their molecular formulas. Transport properties determined from MD simulations are then served as input parameters for LBM simulations in larger scale; (2) micro-scale properties of each component are mapped stochastically on its corresponding voxels in Nano-CT digital rocks. The meso-scale permeabilities of Nano-CT digital rocks are then calculated using the generalized LBM model in porous media; (3) the effective permeabilities of the macro-scale shale digital rock (Micro-CT) with micro-fracture networks are calculated using the generalized LBM model, in which the matrix permeabilities obtained from the step 2 and the transport properties of micro-fractures are served as simulation inputs in macro-scale.
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