Generalized lattice Boltzmann model for flow through tight porous media with Klinkenberg's effect

Multiscale modeling of gas flow behaviors in nanoporous shale matrix considering multiple transport mechanisms

This study proposes a multiscale model combining molecular simulation and the lattice Boltzmann method (LBM) to explore gas flow behaviors with multiple transport mechanisms in nanoporous media of shale matrix. The gas adsorption characteristics in shale nanopores are first investigated by molecular simulations, which are then integrated and upscaled into the LBM model through a local adsorption density parameter. In order to adapt to high Knudsen number and nanoporous shale matrix, a multiple-relaxation-time pore-scale LBM model with a regularization procedure is developed. The combination of bounce-back and full diffusive boundary condition is adopted to take account of gas slippage and surface diffusion induced by gas adsorption. Molecular simulation results at the atomic scale show that gas adsorption behaviors are greatly affected by the pressure and pore size of the shale organic nanopore. At the pore scale, the gas transport behaviors with multiple transport mechanisms in nanoporous shale matrix are explored by the developed multiscale model. Simulation results indicate that pressure exhibits more significant influences on the transport behaviors of shale gas than temperature does. Compared with porosity, the average pore size of nanoporous shale matrix plays a more significant role in determining the apparent permeability of gas transport. The roles of the gas adsorption layer and surface diffusion in shale gas transport are discussed. It is observed that under low pressure, the gas adsorption layer has a positive influence on gas transport in shale matrix due to the strong surface diffusion effect. The nanoporous structure with the anisotropy characteristic parallel to the flow direction can enhance gas transport in shale matrix. The obtained results may provide underlying and comprehensive understanding of gas flow behaviors considering multiple transport mechanisms in shale matrix. Also, the proposed multiscale model can be considered as a powerful tool to invesigate the multiscale and multiphysical flow behaviors in porous media.

Numerical Investigation of Metal Foam Pore Density Effect on Sensible and Latent Heats Storage through an Enthalpy-Based REV-Scale Lattice Boltzmann Method

In this work, an unsteady forced convection heat transfer in an open-ended channel incorporating a porous medium filled either with a phase change material (PCM; case 1) or with water (case 2) has been studied using a thermal lattice Boltzmann method (TLBM) at the representative elementary volume (REV) scale. The set of governing equations includes the dimensionless generalized Navier–Stokes equations and the two energy model transport equations based on local thermal non-equilibrium (LTNE). The enthalpy-based method is employed to cope with the phase change process. The pores per inch density (10≤PPI≤60) effects of the metal foam on the storage of sensible and latent heat were studied during charging/discharging processes at two Reynolds numbers (Re) of 200 and 400. The significant outcomes are discussed for the dynamic and thermal fields, the entropy generation rate (Ns), the LTNE intensity, and the energy and exergy efficiencies under the influence of Re. It can be stated that increasing the PPI improves the energy and exergy efficiencies of the latent heat model, reduces energy losses, and improves the stored energy quality. Likewise, at a moderate Re (=200), a low PPI (=10) would be suitable to reduce the system irreversibility during the charging period, while a high value (PPI = 60) might be advised for the discharging process. As becomes clear from the obtained findings, PPI and porosity are relevant factors. In conclusion, this paper further provides a first analysis of entropy generation during forced convection to improve the energy efficiency of various renewable energy systems.

Predicting Effective Diffusivity of Porous Media from Images by Deep Learning

We report the application of machine learning methods for predicting the effective diffusivity (De) of two-dimensional porous media from images of their structures. Pore structures are built using reconstruction methods and represented as images, and their effective diffusivity is computed by lattice Boltzmann (LBM) simulations. The datasets thus generated are used to train convolutional neural network (CNN) models and evaluate their performance. The trained model predicts the effective diffusivity of porous structures with computational cost orders of magnitude lower than LBM simulations. The optimized model performs well on porous media with realistic topology, large variation of porosity (0.28-0.98), and effective diffusivity spanning more than one order of magnitude (0.1 ≲ De < 1), e.g., >95% of predicted De have truncated relative error of <10% when the true De is larger than 0.2. The CNN model provides better prediction than the empirical Bruggeman equation, especially for porous structure with small diffusivity. The relative error of CNN predictions, however, is rather high for structures with De < 0.1. To address this issue, the porosity of porous structures is encoded directly into the neural network but the performance is enhanced marginally. Further improvement, i.e., 70% of the CNN predictions for structures with true De < 0.1 have relative error <30%, is achieved by removing trapped regions and dead-end pathways using a simple algorithm. These results suggest that deep learning augmented by field knowledge can be a powerful technique for predicting the transport properties of porous media. Directions for future research of machine learning in porous media are discussed based on detailed analysis of the performance of CNN models in the present work.

Lattice Boltzmann Model for Gas Flow through Tight Porous Media with Multiple Mechanisms

In the development of tight gas reservoirs, gas flow through porous media usually takes place deep underground with multiple mechanisms, including gas slippage and stress sensitivity of permeability and porosity. However, little work has been done to simultaneously incorporate these mechanisms in the lattice Boltzmann model for simulating gas flow through porous media. This paper presents a lattice Boltzmann model for gas flow through porous media with a consideration of these effects. The apparent permeability and porosity are calculated based on the intrinsic permeability, intrinsic porosity, permeability modulus, porosity sensitivity exponent, and pressure. Gas flow in a two-dimensional channel filled with a homogeneous porous medium is simulated to validate the present model. Simulation results reveal that gas slippage can enhance the flow rate in tight porous media, while stress sensitivity of permeability and porosity reduces the flow rate. The simulation results of gas flow in a porous medium with different mineral components show that the gas slippage and stress sensitivity of permeability and porosity not only affect the global velocity magnitude, but also have an effect on the flow field. In addition, gas flow in a porous medium with fractures is also investigated. It is found that the fractures along the pressure-gradient direction significantly enhance the total flow rate, while the fractures perpendicular to the pressure-gradient direction have little effect on the global permeability of the porous medium. For the porous medium without fractures, the gas-slippage effect is a major influence factor on the global permeability, especially under low pressure; for the porous medium with fractures, the stress-sensitivity effect plays a more important role in gas flow.

Consistent second-order boundary implementations for convection-diffusion lattice Boltzmann method

In this study, an alternative second-order boundary scheme is proposed under the framework of the convection-diffusion lattice Boltzmann (LB) method for both straight and curved geometries. With the proposed scheme, boundary implementations are developed for the Dirichlet, Neumann and linear Robin conditions in a consistent way. The Chapman-Enskog analysis and the Hermite polynomial expansion technique are first applied to derive the explicit expression for the general distribution function with second-order accuracy. Then, the macroscopic variables involved in the expression for the distribution function is determined by the prescribed macroscopic constraints and the known distribution functions after streaming [see the paragraph after Eq. (29) for the discussions of the "streaming step" in LB method]. After that, the unknown distribution functions are obtained from the derived macroscopic information at the boundary nodes. For straight boundaries, boundary nodes are directly placed at the physical boundary surface, and the present scheme is applied directly. When extending the present scheme to curved geometries, a local curvilinear coordinate system and first-order Taylor expansion are introduced to relate the macroscopic variables at the boundary nodes to the physical constraints at the curved boundary surface. In essence, the unknown distribution functions at the boundary node are derived from the known distribution functions at the same node in accordance with the macroscopic boundary conditions at the surface. Therefore, the advantages of the present boundary implementations are (i) the locality, i.e., no information from neighboring fluid nodes is required; (ii) the consistency, i.e., the physical boundary constraints are directly applied when determining the macroscopic variables at the boundary nodes, thus the three kinds of conditions are realized in a consistent way. It should be noted that the present focus is on two-dimensional cases, and theoretical derivations as well as the numerical validations are performed in the framework of the two-dimensional five-velocity lattice model.

Understanding hydraulic fracturing: a multi-scale problem

Despite the impact that hydraulic fracturing has had on the energy sector, the physical mechanisms that control its efficiency and environmental impacts remain poorly understood in part because the length scales involved range from nanometres to kilometres. We characterize flow and transport in shale formations across and between these scales using integrated computational, theoretical and experimental efforts/methods. At the field scale, we use discrete fracture network modelling to simulate production of a hydraulically fractured well from a fracture network that is based on the site characterization of a shale gas reservoir. At the core scale, we use triaxial fracture experiments and a finite-discrete element model to study dynamic fracture/crack propagation in low permeability shale. We use lattice Boltzmann pore-scale simulations and microfluidic experiments in both synthetic and shale rock micromodels to study pore-scale flow and transport phenomena, including multi-phase flow and fluids mixing. A mechanistic description and integration of these multiple scales is required for accurate predictions of production and the eventual optimization of hydrocarbon extraction from unconventional reservoirs. Finally, we discuss the potential of CO2 as an alternative working fluid, both in fracturing and re-stimulating activities, beyond its environmental advantages.This article is part of the themed issue 'Energy and the subsurface'.

Grayscale lattice Boltzmann model for multiphase heterogeneous flow through porous media

The grayscale lattice Boltzmann (LB) model has been recently developed to model single-phase fluid flow through heterogeneous porous media. Flow is allowed in each voxel but the degree of flow depends on that voxel's resistivity to fluid motion. Here we extend the grayscale LB model to multiphase, immiscible flow. The new model is outlined and then applied to a number of test cases, which show good agreement with theory. This method is subsequently used to model the important case where each voxel may have a different resistance to each particular fluid that is passing through it. Finally, the method is applied to model fluid flow through real porous media to demonstrate its capability. Both the capillary and viscous flow regimes are recovered in these simulations.

Finite-volume method with lattice Boltzmann flux scheme for incompressible porous media flow at the representative-elementary-volume scale

Based on the Darcy-Brinkman-Forchheimer equation, a finite-volume computational model with lattice Boltzmann flux scheme is proposed for incompressible porous media flow in this paper. The fluxes across the cell interface are calculated by reconstructing the local solution of the generalized lattice Boltzmann equation for porous media flow. The time-scaled midpoint integration rule is adopted to discretize the governing equation, which makes the time step become limited by the Courant-Friedricks-Lewy condition. The force term which evaluates the effect of the porous medium is added to the discretized governing equation directly. The numerical simulations of the steady Poiseuille flow, the unsteady Womersley flow, the circular Couette flow, and the lid-driven flow are carried out to verify the present computational model. The obtained results show good agreement with the analytical, finite-difference, and/or previously published solutions.

Full Eulerian lattice Boltzmann model for conjugate heat transfer

In this paper a full Eulerian lattice Boltzmann model is proposed for conjugate heat transfer. A unified governing equation with a source term for the temperature field is derived. By introducing the source term, we prove that the continuity of temperature and its normal flux at the interface is satisfied automatically. The curved interface is assumed to be zigzag lines. All physical quantities are recorded and updated on a Cartesian grid. As a result, any complicated treatment near the interface is avoided, which makes the proposed model suitable to simulate the conjugate heat transfer with complex interfaces efficiently. The present conjugate interface treatment is validated by several steady and unsteady numerical tests, including pure heat conduction, forced convection, and natural convection problems. Both flat and curved interfaces are also involved. The obtained results show good agreement with the analytical and/or finite volume results.