Multiphase-Flow and Reactive-Transport Validation Studies at the Pore Scale by Use of Lattice Boltzmann Computer Simulations

Abstract

Summary We describe the recent development of lattice Boltzmann (LB) and particle-tracing computer simulations to study flow and reactive transport in porous media. First, we measure both flow and solute transport directly on pore-space images obtained from micro-computed-tomography (CT) scanning. We consider rocks with increasing degree of heterogeneity: a bead pack, Bentheimer sandstone, and Portland carbonate. We predict probability distributions for molecular displacements and find excellent agreement with pulsed-field-gradient (PFG) -nuclear-magnetic-resonance (NMR) experiments. Second, we validate our LB model for multiphase flow by calculating capillary filling and capillary pressure in model porous media. Then, we extend our models to realistic 3D pore-space images and observe the calculated capillary pressure curve in Bentheimer sandstone to be in agreement with the experiment. A process-based algorithm is introduced to determine the distribution of wetting and nonwetting phases in the pore space, as a starting point for relative permeability calculations. The Bentheimer relative permeability curves for both drainage and imbibition are found to be in good agreement with experimental data. Third, we show the speedup of a graphics-processing-unit (GPU) algorithm for large-scale LB calculations, offering greatly enhanced computing performance in comparison with central-processing-unit (CPU) calculations. Finally, we propose a hybrid method to calculate reactive transport on pore-space images by use of the GPU code. We calculate the dissolution of a porous medium and observe agreement with the experiment. The LB method is a powerful tool for calculating flow and reactive transport directly on pore-space images of rock.

Simulation of mineral dissolution at the pore scale with evolving fluid-solid interfaces: review of approaches and benchmark problem set

“…Significant advancements in imaging techniques and processing capabilities have made it possible to resolve the porous media from the nanometer to the micrometer scale and beyond. These techniques include X-ray computed microtomography (XCMT, e.g., [15,66]), scanning electron microscopy (SEM), and back-scattered SEM (e.g., [33,69]), SEM Quantitative Evaluation of Minerals by Scanning Electron Microscopy (QEMSCAN ® , e.g., [12,55]), focused ion beam SEM (FIB-SEM, e.g., [50,114]), and optical microscopy (e.g., [96]). Generally, experimental images are two-or threedimensional gray scale representations of the medium, with each pixel providing a measure of the phase or phases that occupy that point in space (e.g., x-ray attenuation in XCMT).…”

“…To maintain a sharp concentration front, the advection term is discretized using van Leer flux limiter schemes. The pressure-velocity coupling (13) and (15) are handled by a predictor-corrector strategy adapted from the Pressure-Implicit with Splitting of Operators (PISO) algorithm [41]. Finally the algorithm marches in time.…”

“…Further, simulation results resolve variables that are not easily available from experiments, for example concentration gradients within the pore space. Such data enables additional insights to be drawn, especially when comparison to experimental data is possible [15,66,75,96,97,99].…”

Wetting boundary condition for the color-gradient lattice Boltzmann method: Validation with analytical and experimental data

“…To compute multiphase flow properties at the pore scale several direct numerical simulation methods have been developed using the volume-of-fluid method ( Raeini et al, 2015;Shams et al, 2018 ), the level set method ( Jettestuen et al, 2013;Prodanovi ć and Bryant, 2006 ) and the lattice Boltzmann method (LBM) ( Boek et al, 2017;Leclaire et al, 2017;Ramstad et al, 2012;Tölke et al, 2006 ). Several studies have used the LBM to compute flow through porespace images ( Ahrenholz et al, 2008;Boek et al, 2017;Leclaire et al, 2017;Ramstad et al, 2012;.…”

“…Several studies have used the LBM to compute flow through porespace images ( Ahrenholz et al, 2008;Boek et al, 2017;Leclaire et al, 2017;Ramstad et al, 2012;. In these cases, a color gradient (CG) LBM was used.…”