Effect of Network Structure on Characterization and Flow Modeling Using X-ray Micro-Tomography Images of Granular and Fibrous Porous Media

The Impacts of Surface Microchannels on the Transport Properties of Porous Fibrous Media Using Stochastic Pore Network Modeling

A stochastic pore network modeling method with tailored structures is proposed to investigate the impacts of surface microchannels on the transport properties of porous fibrous media. Firstly, we simplify the original pore network extracted from the 3D images. Secondly, a repeat sampling strategy is applied during the stochastic modeling of the porous structure at the macroscale while honoring the structural property of the original network. Thirdly, the microchannel is added as a spherical chain and replaces the overlapped elements of the original network. Finally, we verify our model via a comparison of the structure and flow properties. The results show that the microchannel increases the permeability of flow both in the directions parallel and vertical to the microchannel direction. The microchannel plays as the highway for the pass of reactants while the rest of the smaller pore size provides higher resistance for better catalyst support, and the propagation path in the network with microchannels is more even and predictable. This work indicates that our modeling framework is a promising methodology for the design optimization of cross-scale porous structures.

A (Dual) Network Model for Heat Transfer in Porous Media

We present a dual network model to simulate coupled single-phase flow and energy transport in porous media including conditions under which local thermal equilibrium cannot be assumed. The models target applications such as the simulation of catalytic reactors, micro-fluidic experiments, or micro-cooling devices. The new technique is based on a recently developed algorithm that extracts both the pore space and the solid grain matrix of a porous medium from CT images into an interconnected network representation. We simulate coupled heat and mass transfer in these networks simultaneously, allowing naturally to model scenarios with heterogeneous temperature distributions in both void space and solid matrix. The model is compared with 3D conjugate heat transfer simulations for both conduction- and convection-dominated scenarios. It is shown to reproduce effective thermal conductivities over a wide range of fluid to solid thermal conductivity ratios with a single parameter set. Morevoer, it captures local thermal nonequilibrium effects in a micro-cooling device scenario.

Effective Diffusion in Fibrous Porous Media: A Comparison Study between Lattice Boltzmann and Pore Network Modeling Methods

The understanding of the correlation between a pore-scale structure and its coupled diffusion transport property is crucial in the virtual design and performance optimization of porous fibrous material for various energy applications. Two most common and widely employed pore-scale modeling techniques are the lattice Boltzmann method (LBM) and the pore network modeling (PNM). However, little attention has been paid to the direct comparison between these two methods. To this end, stochastic porous fibrous structures are reconstructed reflecting the structural properties of the fibrous porous material on a statistical level with structural properties obtained from X-ray computed microtomography. Diffusion simulation through the porous phase was subsequently conducted using LBM of D3Q7 lattice and topological equivalent PNM derived from the watershed method, respectively. It is detected that the effective diffusion coefficients between these two methods are in good agreement when the throat radius in the pore network is estimated using the cross-section area equivalent radius. Like most literature, the diffusivity in the in-plane (IP) direction is larger than in the through-plane (TP) direction due to the laid fiber arrangement, but the values are very close. Besides, tortuosity was evaluated from both geometry and transport measurements. Tortuosity values deduced from both methods are in line with the anisotropy of the diffusion coefficients.

Validation of pore network modeling for determination of two-phase transport in fibrous porous media

Pore network modeling (PNM) has been widely investigated in the study of multiphase transport in porous media due to its high computational efficiency. The advantage of PNM is achieved in part at the cost of using simplified geometrical elements. Therefore, the validation of pore network modeling needs further verification. A Shan-Chen (SC) multiphase lattice Boltzmann model (LBM) was used to simulate the multiphase flow and provided as the benchmark. PNM using different definitions of throat radius was performed and compared. The results showed that the capillary pressure and saturation curves agreed well when throat radius was calculated using the area-equivalent radius. The discrepancy of predicted phase occupations from different methods was compared in slice images and the reason can be attributed to the capillary pressure gradients demonstrated in LBM. Finally, the relative permeability was also predicted using PNM and provided acceptable predictions when compared with the results using single-phase LBM.

High porosity with tiny pore constrictions and unbending pathways characterize the 3D structure of intervessel pit membranes in angiosperm xylem

Pit membranes between xylem vessels play a major role in angiosperm water transport. Yet, their three-dimensional (3D) structure as fibrous porous media remains unknown, largely due to technical challenges and sample preparation artefacts. Here, we applied a modelling approach based on thickness measurements of fresh and fully shrunken pit membranes of seven species. Pore constrictions were also investigated visually by perfusing fresh material with colloidal gold particles of known sizes. Based on a shrinkage model, fresh pit membranes showed tiny pore constrictions of ca. 20 nm, but a very high porosity (i.e. pore volume fraction) of on average 0.81. Perfusion experiments showed similar pore constrictions in fresh samples, well below 50 nm based on transmission electron microscopy. Drying caused a 50% shrinkage of pit membranes, resulting in much smaller pore constrictions. These findings suggest that pit membranes represent a mesoporous medium, with the pore space characterized by multiple constrictions. Constrictions are much smaller than previously assumed, but the pore volume is large and highly interconnected. Pores do not form highly tortuous, bent, or zigzagging pathways. These insights provide a novel view on pit membranes, which is essential to develop a mechanistic, 3D understanding of air-seeding through this porous medium.

Experimental comparison of agent-enhanced flushing for the recovery of crude oil from saturated porous media

The subsurface remediation of nonaqueous liquid (NAPL) has proven to be challenging even when implementing more aggressive enhanced-flushing techniques. The objective of this study was to evaluate the effectiveness of a combination of alkaline- and surfactant-based enhanced flushing for the removal of crude oil (medium fraction) from saturated porous media. Synchrotron X-ray microtomography (SXM) was used to perform pore-scale examination of NAPL fragmentation and changes in blob morphology, and recovery using three different advective flushing methods: surface-active agent (surfactant) flushing, alkaline flushing, and sequential alkaline-surfactant flushing. This set of experiments was conducted to understand effects on such processes (fragmentation and recovery) as a function of media composition (geochemical/mineralogical) and pH alterations due to calcium-carbonate fraction. Results showed that the sequential flushing technique (alkaline→ surfactant) yielded the highest recovery, 32% after 5 pore volumes (PV) of flushing. The crude oil (NAPL) distribution varied due to differences in porous medium mixture composition and type of fluid (i.e. surfactant vs. alkaline) used for flushing. The results of this study can be used to aid in the understanding of physical and chemical parameters/properties that control mobilization of crude oil in saturated porous media. This can help reduce time and cost during remediation of contaminated sites that contain crude oil or less dense NAPL derivatives consistent with fuel-type petroleum hydrocarbons.

A pore-scale investigation of heavy crude oil trapping and removal during surfactant-enhanced remediation

The presence of nonaqueous phase liquid (NAPL) in the subsurface presents significant challenges for soil and groundwater remediation. In particular, heavy crude oil, coal tar and/or bitumen present unique difficulties for removal and cleanup due to associated high viscosities, low aqueous solubilities, and limited mobility extraction potential. Although surfactant-enhanced aquifer remediation (SEAR) techniques have shown some promise for source removal, overall remediation (mobilization) performance will depend significantly on interfacial effects between the fluid and solid phases. A pore-scale study, implementing synchrotron X-ray microtomography (SXM), was conducted to understand and quantify the trapping and mobilization mechanisms and in-situ emulsification processes of heavy crude oil distributed within increasing complexity (i.e. physical heterogeneity) unconsolidated sands during surfactant flushing events. Pore-scale imaging analyses were conducted to quantify the changes in oil blob morphology before and after surfactant flushing events to assess the primary factors controlling the recovery. Results showed relatively low (10%) net recovery from the homogeneous sand after 5 pore volumes (PVs) of surfactant flushing and may be, in part, due to the more connected ganglia (i.e. single continuous) oil-phase. Such a condition may have limited the surfactant/oil contact resulting in relatively low interfacial activity and correspondingly inefficient oil mobilization and recovery. Negligible net oil recovery was achieved from the mildly-heterogeneous-sand and is likely due to the lower associated permeability of this particular porous medium. Furthermore, the oil-phase distribution within this medium primarily consisted of small disconnected blobs more readily exposed (in contact with) the surfactant solution. For the highly-heterogeneous-sand experiments, an average of 20% heavy-oil recovery resulted after each flushing event (total of ~37% after 5 PVs) and was attributed to more efficient reduction of interfacial tension associated with the increased surfactant-oil contact. The associated higher pH sand/fine‑carbonate system may have aided in maintaining a water-wet porous medium, a condition more conducive to higher oil recovery and displacement efficiency.

Versatile and efficient pore network extraction method using marker-based watershed segmentation

Obtaining structural information from tomographic images of porous materials is a critical component of porous media research. Extracting pore networks is particularly valuable since it enables pore network modeling simulations which can be useful for a host of tasks from predicting transport properties to simulating performance of entire devices. This work reports an efficient algorithm for extracting networks using only standard image analysis techniques. The algorithm was applied to several standard porous materials ranging from sandstone to fibrous mats, and in all cases agreed very well with established or known values for pore and throat sizes, capillary pressure curves, and permeability. In the case of sandstone, the present algorithm was compared to the network obtained using the current state-of-the-art algorithm, and very good agreement was achieved. Most importantly, the network extracted from an image of fibrous media correctly predicted the anisotropic permeability tensor, demonstrating the critical ability to detect key structural features. The highly efficient algorithm allows extraction on fairly large images of 500^{3} voxels in just over 200 s. The ability for one algorithm to match materials as varied as sandstone with 20% porosity and fibrous media with 75% porosity is a significant advancement. The source code for this algorithm is provided.

Review of pore network modelling of porous media: Experimental characterisations, network constructions and applications to reactive transport

Pore network models have been applied widely for simulating a variety of different physical and chemical processes, including phase exchange, non-Newtonian displacement, non-Darcy flow, reactive transport and thermodynamically consistent oil layers. The realism of such modelling, i.e. the credibility of their predictions, depends to a large extent on the quality of the correspondence between the pore space of a given medium and the pore network constructed as its representation. The main experimental techniques for pore space characterisation, including direct imaging, mercury intrusion porosimetry and gas adsorption, are firstly summarised. A review of the main pore network construction techniques is then presented. Particular focus is given on how such constructions are adapted to the data from experimentally characterised pore systems. Current applications of pore network models are considered, with special emphasis on the effects of adsorption, dissolution and precipitation, as well as biomass growth, on transport coefficients. Pore network models are found to be a valuable tool for understanding and predicting meso-scale phenomena, linking single pore processes, where other techniques are more accurate, and the homogenised continuum porous media, used by engineering community.

Method for obtaining silver nanoparticle concentrations within a porous medium via synchrotron X-ray computed microtomography

Attempts at understanding nanoparticle fate and transport in the subsurface environment are currently hindered by an inability to quantify nanoparticle behavior at the pore scale (within and between pores) within realistic pore networks. This paper is the first to present a method for high resolution quantification of silver nanoparticle (nAg) concentrations within porous media under controlled experimental conditions. This method makes it possible to extract silver nanoparticle concentrations within individual pores in static and quasi-dynamic (i.e., transport) systems. Quantification is achieved by employing absorption-edge synchrotron X-ray computed microtomography (SXCMT) and an extension of the Beer-Lambert law. Three-dimensional maps of X-ray mass linear attenuation are converted to SXCMT-determined nAg concentration and are found to closely match the concentrations determined by ICP analysis. In addition, factors affecting the quality of the SXCMT-determined results are investigated: 1) The acquisition of an additional above-edge data set reduced the standard deviation of SXCMT-determined concentrations; 2) X-ray refraction at the grain/water interface artificially depresses the SXCMT-determined concentrations within 18.1 μm of a grain surface; 3) By treating the approximately 20 × 10(6) voxels within each data set statistically (i.e., averaging), a high level of confidence in the SXCMT-determined mean concentrations can be obtained. This novel method provides the means to examine a wide range of properties related to nanoparticle transport in controlled laboratory porous medium experiments.