Abstract
Rocks contain multi-scale pore structures, with dimensions ranging from nano- to sample-scale, the inherent tradeoff between imaging resolution and sample size limits the simultaneous characterization of macro-pores and micro-pores using single-resolution imaging. Here, we developed a new hybrid digital rock modeling approach to cope with this open challenge. We first used micron-CT to construct the 3D macro-pore digital rock of tight sandstone, then performed high-resolution SEM on the three orthogonal surfaces of sandstone sample, thus reconstructed the 3D micro-pore digital rock by Markov chain Monte Carlo (MCMC) method; finally, we superimposed the macro-pore and micro-pore digital rocks to achieve the integrated digital rock. Maximal ball algorithm was used to extract pore-network parameters of digital rocks, and numerical simulations were completed with Lattice-Boltzmann method (LBM). The results indicate that the integrated digital rock has anisotropy and good connectivity comparable with the real rock, and porosity, pore-throat parameters and intrinsic permeability from simulations agree well with the values acquired from experiments. In addition, the proposed approach improves the accuracy and scale of digital rock modeling and can deal with heterogeneous porous media with multi-scale pore-throat system.
Bayesian uncertainty quantification for flows in heterogeneous porous media using reversible jump Markov chain Monte Carlo methods
