Abstract
The mechanism of fluid migration in porous networks continues to attract great interest. Darcy's law (phenomenological continuum theory), which is often used to describe macroscopically fluid flow through a porous material, is thought to fail in nano-channels. Transport through heterogeneous and anisotropic systems, characterized by a broad distribution of pores, occurs via a contribution of different transport mechanisms, all of which need to be accounted for. The situation is likely more complicated when immiscible fluid mixtures are present. To generalize the study of fluid transport through a porous network, we developed a stochastic kinetic Monte Carlo (KMC) model. In our lattice model, the pore network is represented as a set of connected finite volumes (voxels), and transport is simulated as a random walk of molecules, which "hop" from voxel to voxel. We simulated fluid transport along an effectively 1D pore and we compared the results to those expected by solving analytically the diffusion equation. The KMC model was then implemented to quantify the transport of methane through hydrated micropores, in which case atomistic molecular dynamic simulation results were reproduced. The model was then used to study flow through pore networks, where it was able to quantify the effect of the pore length and the effect of the network's connectivity. The results are consistent with experiments but also provide additional physical insights. Extension of the model will be useful to better understand fluid transport in shale rocks.
Highlights
The economic success related to shale gas production in the United States has generated great interest worldwide
Considering that permeability depends on a number of factors, such as pore characteristics, chemical composition, and transport mechanisms, an approach that accounts for all these factors at low computational cost is required
P1 − p2 where J is the molar flux of methane from the kinetic Monte Carlo (KMC) calculations, lp is the length of the pore, p1 is the pressure applied in the feed phase, p2 is the pressure applied in the permeate region (p2 = 0)
Summary
The economic success related to shale gas production in the United States has generated great interest worldwide. One approach implements empirical equations derived from Darcy’s law Within this approach, Darcy’s equation is enriched with coefficients designed to match experimental data for systems that, e.g., exhibit slip flow. Darcy’s equation is enriched with coefficients designed to match experimental data for systems that, e.g., exhibit slip flow Most commonly, these models take into consideration effective stress and slip flow contributions, in order to model the apparent permeability. Considering that permeability depends on a number of factors, such as pore characteristics, chemical composition, and transport mechanisms, an approach that accounts for all these factors at low computational cost is required. We are interested in investigating how the pore characteristics and the pore network connectivity affect the transport properties of light hydrocarbons in hydrated nanopores with different chemical compositions by performing KMC simulations.
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