Abstract
A methodology is suggested for the explicit computation of the absolute permeability and Knudsen diffusion coefficient of tight rocks (shales) from pore structure properties. The pore space is regarded as a pore-and-throat network quantified by the statistical moments of bimodal pore and throat size distributions, pore shape factors, and pore accessibility function. With the aid of percolation theory, analytic equations are developed to express the nitrogen (N2) adsorption/desorption isotherms and mercury (Hg) intrusion curve as functions of all pertinent pore structure parameters. A multistep procedure is adopted for the successive estimation of each set of parameters by the inverse modeling of N2 adsorption–desorption isotherms, and Hg intrusion curve. With the aid of critical path analysis of percolation theory, the absolute permeability and Knudsen diffusion coefficient are computed as functions of estimated pore network properties. Application of the methodology to the datasets of several shale samples enables us to evaluate the predictability of the approach.
Highlights
Tight and shale reservoir systems pose a tremendous potential resource for future development, and the determination of their microscopic and macroscopic properties has long attracted the attention of scientific society
The digital shale rock could be developed by 3-Dimensional (3D) images obtained from micro/nano Computed Tomography (CT) and FIB-SEM images reconstructed from 2D SEM images of the pore structure, and using the Lattice Boltzmann method to compute the intrinsic permeability, porosity and tortuosity; these parameters are used to calculate the apparent permeability by accounting for different gas transport mechanisms (Sun et al, 2017)
Other factors that prevent the simultaneous prediction of all datasets and favor the shift of Pore Size Distributions (PSDs) and TSD toward small sizes are: (i) the higher contribution fraction of N2 sorption to the estimation process (2 datasets against 1 dataset); (ii) the uncertainty of the “fixed values” of parameters included in N2 adsorption/desorption equations; (iii) the lack of sufficient information concerning the large pore sizes that are not detected at all by N2 adsorption isotherm, and are shadowed in Hg intrusion curve; such large pore sizes might be correlated with the Hg retraction curve (Tsakiroglou et al 2009) which was overlooked in the present approach
Summary
Tight and shale reservoir systems pose a tremendous potential resource for future development, and the determination of their microscopic and macroscopic properties has long attracted the attention of scientific society. The digital shale rock could be developed by 3-Dimensional (3D) images obtained from micro/nano Computed Tomography (CT) and FIB-SEM images reconstructed from 2D SEM images of the pore structure, and using the Lattice Boltzmann method to compute the intrinsic permeability, porosity and tortuosity; these parameters are used to calculate the apparent permeability by accounting for different gas transport mechanisms (Sun et al, 2017). Three-dimensional nano-porous structures of shales reconstructed from SEM images of shale samples enabled the computational analysis of structural characteristics and calculation of tortuosity, effective Knudsen diffusivity. The FIB-SEM technique was employed to observe and characterize the morphology of the nanopores in shales, Lattice Boltzmann Method (LBM) was used to simulate high-Knudsen gas flows, and the nano-scale pore morphology was found to play an important role on the gas transport properties of shale matrix (Zheng et al, 2017). The critical path analysis of percolation theory is used to calculate the liquid permeability and Knudsen diffusion coefficient of porous media explicitly from the aforementioned pore structure parameters and compare the predictions with experimental measurements
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