Biofilm growth is a significant factor in subsurface processes governing fluid flow and contaminant transport. Biobarriers are known to reduce hydraulic conductivity, as well as to immobilise metals in the matrix of the exopolymeric substances (EPS) produced by bacterial cells. It is therefore necessary to develop understanding of how bioclogging and related mechanisms occur in porous media, and how contaminants interact with biofilms at the laboratory scale, which ultimately can be scaled up to field scenarios. The aims of the laboratory experiments were to a) enable uniform biofilm growth in columns packed with different types of porous media, b) develop methods of quantifying and visualising biofilm distribution in porous media, and c) measure transport of zinc oxide (ZnO) nanoparticles in columns with and without biofilm growing on the porous media. Experiments were conducted with columns and batch tests. Biofilms were grown by inoculating columns with Pseudomonas putida. Biofilm distribution was quantified by biomass extraction and visualised using X-ray computed microtomography (μCT) imaging. Colorimetric methods were used predominantly to quantify protein and polysaccharide content in biofilms. However, these methods possess several major disadvantages, which were highlighted using experimental data from batch tests. X-ray computer microtomography is a non-destructive method of visualising biofilm growth and illustrating flow paths in porous media. Particular components of μCT images (porous media, biofilm, tracer) were subtracted from images based on density contrasts. Reconstructed images of small, bio-clogged columns show that clogging occurs not only as a result of abundant biofilm growth but also air bubbles. Nanoparticle transport in porous media involved the injection of bare and capped ZnO nanoparticle suspensions into columns packed with glass beads, sand and calcite with and without inoculation of bacteria. Results, as well as modelled predictions, showed that ZnO nanoparticles generally possess low mobility, and that biofilm impedes nanoparticle transport. Porous media surface charge, as well as the extent of biofilm growth, play an important role in nanoparticle transport.

During carbon dioxide (CO₂) sequestration, CO₂ injection suffers from viscous fingering and low sweep efficiency. In addition, the lower density of CO₂ compared to in-situ brine leads to the possibility of sequestered CO₂ rising up through the relatively permeable path in the cap rock and being emitted back out to the atmosphere. This research proposes a mechanism of CO₂-in-brine emulsion stabilization by surface-coated nanoparticles as a potential cure for these problems. This mechanism is studied in detail by conducting a series of core floods to investigate the interactions between nanoparticles and the surroundings such as fluids and rock surfaces during nanoparticle transport in sedimentary rocks. The experiments presented here use n-octane as a low-pressure analog fluid to supercritical CO₂ as they share several key characteristics. Comparisons of pressure drop and CT images from drainage displacement experiments with and without nanoparticles show that nanoparticle-stabilized emulsions were generated in-situ in highly permeable and homogeneous Boise sandstones tested in this study. Roof snap-off is proposed as the key mechanism for generating the emulsions. The imbibition experiment presents a case where Roof snap-off does not occur. The pressure drop for the control experiment and the nanoparticle experiments confirmed that without Roof snap-off nanoparticles do not affect the dynamics of the displacement except for the viscosity increase of the aqueous phase. However, it was inferred from the saturation profiles and effluent concentration history that nanoparticles were traveling faster than the aqueous phase in which they were dispersed and accumulating at the main displacement front. Inaccessible pore volume is proposed as a mechanism responsible for the accelerated transport of nanoparticles. The single-phase flow experiments demonstrate the accelerated transport of nanoparticles in porous media that was invoked to explain observations during imbibition displacement. During these experiments, tracer and nanoparticles were simultaneously injected into a porous medium and their effluent concentrations were monitored using a UV-Vis detector. The results show that nanoparticles traveled faster than the tracer in Boise and Berea sandstones studied in this research. Two-site model developed by Zhang (2012) was used to fit the data. Simulations suggested that the two-site model could replicate the overall shape of the experimental data when a slug of nanoparticle dispersion was injected, but it was not able to accurately predict the leading edge and the trailing edge of the effluent concentration history, where nanoparticles appeared before tracer due to accelerated transport. To account for the enhanced transport of nanoparticles, a modified two-site model with an acceleration factor, E, is proposed. The resulting fit matched the experimental data better than the original two-site model. / text

Accurate prediction of colloid deposition rates in porous media is essential in several applications. These include natural filtration of pathogenic microorganisms such as bacteria, viruses, and protozoa, transport and fate of colloid-associated transport of contaminants, deep bed and river bank filtration for water treatment, fate and transport of engineered nanoparticles released into the environment, and bioremediation of contaminated sites. Colloid transport in porous media is a multi-scale problem, with length scales spanning from the sub-pore scale, where the particle-soil interaction forces control the deposition, up to the Darcy scale, where the macroscopic equations governing particle transport are formulated. Colloid retention at the Darcy scale is due to the lumped effect of processes occurring at the pore scale. This requires the incorporation of the micro-scale physics into macroscopic models for a better understanding of colloid deposition in porous media. That can be achieved through pore-scale modeling and the subsequent upscaling to the Darcy scale. Colloid Filtration Theory (CFT), the most commonly used approach to describe colloid attachment onto the soil grains in the subsurface, is found to accurately predict the deposition rates of micron-sized particles under favorable conditions for deposition. But, CFT has been found to over predict particle deposition rates at low flow velocity conditions, typical of groundwater flow, and for nanoscale particles. Also, CFT is found to be inapplicable at typical environmental conditions, where conditions become unfavorable for deposition, due to factors not considered in CFT such as deposition in the secondary minimum of the interaction energy profile, grain surface roughness, surface charge heterogeneity of grains and colloids, and deposition at grain-to-grain contacts. To the best of our knowledge, mechanistic-based models for predicting colloid deposition rates under unfavorable conditions do not exist. Currently, fitting the colloid breakthrough curve (BTC), obtained from the laboratory column-or field-scale experiments, to the advection-dispersion-deposition model is used to estimate the values of deposition rate coefficients. Because of their small size (less than 100 nm), nanoparticles, a sub-class of colloids, may interact with the porous medium in a different way as compared to the larger colloids, resulting in different retention mechanisms for nanoparticles and micron-sized particles. This emphasizes the need to study nanoparticles separately from larger, micrometer-sized colloids to better understand nanoparticle retention mechanisms. The work reported in this thesis contributes towards developing mathematical models to predict nanoparticle movement in porous media. A comprehensive mechanistic approach is employed by integrating pore-scale processes into Darcy-scale models through pore-network modeling to upscale nanoparticle transport in saturated porous media to the Darcy scale, and to develop correlation equations for the Darcy-scale deposition parameters in terms of various measurable parameters at Darcy scale. Further, a one-dimensional mathematical model to simulate the co-transport of viruses and colloids in partially saturated porous media is developed to understand the relative importance of various interactions on virus transport in porous media. Pore-network modeling offers a valuable upscaling tool to express the macroscopic behavior by accounting for the relevant physics at the underlying pore scale. This is done by idealizing the pore space as an interconnected network of pore elements of different sizes and variably connected to each other, and simulating flow and transport through the network of pores, with the relevant physics implemented on a pore to pore basis (Raoof, 2011). By comparing the results of pore-network modeling with an appropriate mathematical model describing the macro-scale behavior, a relationship between the properties at the macro scale and those at the pore scale can be obtained. A three dimensional multi-directional pore-network model, PoreFlow, developed by Raoof et al. (2010, 2013) is employed in this thesis, which represents the porous medium as an interconnected network of cylindrical pore throats and spherical pore bodies, to upscale nanoparticle transport from pore scale to the Darcy scale. The first step in this procedure is to obtain relationships between adsorbed mass and aqueous mass for a single pore. A mathematical model is developed to simulate nanoparticle transport in a saturated cylindrical pore by solving the full transport equation, considering various processes such as advection, diffusion, hydrodynamic wall effects, and nanoparticle-collector surface interactions. The pore space is divided into three different regions: bulk, diffusion and potential regions, based on the dominant processes acting in each of these regions. In both bulk and diffusion regions, nanoparticle transport is governed by advection and diffusion. However, in the diffusion region, the diffusion is significantly reduced due to hydrodynamic wall effects. Nanoparticle-collector interaction forces dominate the transport in the potential region where deposition occurs. A sensitivity analysis of the model indicates that nanoparticle transport and deposition in a pore is significantly affected by various pore-scale parameters such as the nanoparticle and collector surface potentials, ionic strength of the solution, flow velocity, pore radius, and nanoparticle radius. The model is found to be more sensitive to all parameters under favorable conditions. It is found that the secondary minimum plays an important role in the deposition of small as well as large nanoparticles, and its contribution is found to increase as the favorability of the surface for adsorption decreases. Correlation equations for average deposition rate coefficients of nanoparticles in a saturated cylindrical pore under unfavorable conditions are developed as a function of nine pore-scale parameters: the pore radius, nanoparticle radius, mean flow velocity, solution ionic strength, viscosity, temperature, solution dielectric constant, and nanoparticle and collector surface potentials. Advection-diffusion equations for nanoparticle transport are prescribed for the bulk and diffusion regions, while the interaction between the diffusion and potential regions is included as a boundary condition. This interaction is modeled as a first-order reversible kinetic adsorption. The expressions for the mass transfer rate coefficients between the diffusion and the potential regions are derived in terms of the interaction energy profile between the nanoparticle and the collector. The resulting equations are solved numerically for a range of values of pore-scale parameters. The nanoparticle concentration profile obtained for the cylindrical pore is averaged over a moving averaging volume within the pore in order to get the 1-D concentration field. The latter is fitted to the 1-D advection-dispersion equation with an equilibrium or kinetic adsorption model to determine the values of the average deposition rate coefficients. Pore-scale simulations are performed for three values of Péclet number, Pe = 0.05, 5 and 50. It is found that under unfavorable conditions, the nanoparticle deposition at pore scale is best described by an equilibrium model at low Péclet numbers (Pe = 0.05), and by a kinetic model at high Péclet numbers (Pe = 50). But, at an intermediate Pe (e.g., near Pe = 5), both equilibrium and kinetic models fit the 1-D concentration field. Correlation equations for the pore-averaged nanoparticle deposition rate coefficients under unfavorable conditions are derived by performing a multiple-linear regression analysis between the estimated deposition rate coefficients for a single pore and various pore-scale parameters. The correlation equations, which follow a power law relationship with nine pore-scale parameters, are found to be consistent with the column-scale and pore-scale experimental results, and qualitatively agree with CFT. Nanoparticle transport is upscaled from pore to the Darcy scale in saturated porous media by incorporating the correlations equations for the pore-averaged deposition rate coefficients of nanoparticles in a cylindrical pore into a multi-directional pore-network model, PoreFlow (Raoof et al., 2013). Pore-network model simulations are performed for a range of parameter values, and nanoparticle BTCs are obtained from the pore-network model. Those curves are then modeled using 1-D advection-dispersion equation with a two-site first-order reversible deposition, with terms accounting for both equilibrium and kinetic sorption. Kinetic sorption is found to become important as the favorability of the surface for deposition decreases. Correlation equations for the Darcy¬scale deposition rate coefficients under unfavorable conditions are developed as a function of various measurable Darcy-scale parameters, including: porosity, mean pore throat radius, mean pore water velocity, nanoparticle radius, ionic strength, dielectric constant, viscosity, temperature, and surface potentials on the nanoparticle and grain surface. The correlation equations are found to be consistent with the observed trends from the column experiments available in the literature, and are in agreement with CFT for all parameters, except for the mean pore water velocity and nanoparticle radius. The Darcy-scale correlation equations contain multipliers whose values for a given set of experimental conditions need to be determined by comparing the values of the deposition rate coefficients predicted by the correlation equations against the estimated values of Darcy-scale deposition parameters obtained by fitting the BTCs from column or field experiments with 1-D advection-dispersion-deposition model. They account for the effect of factors not considered in this study, such as the physical and chemical heterogeneity of the grain surface and nanoparticles, flow stagnation points, grain-to-grain contacts, etc. Colloids are abundant in the subsurface and have been observed to interact with a variety of contaminants, including viruses, thereby significantly influencing their transport. A mathematical model is developed to simulate the co-transport of viruses and colloids in partially saturated porous media under steady state flow conditions. The virus attachment to the mobile and immobile colloids is described using a linear reversible kinetic model. It is assumed that colloid transport is not affected by the presence of attached viruses on its surface, and hence, colloid transport is decoupled from virus transport. The governing equations are solved numerically using an alternating three-step operator splitting approach. The model is verified by fitting three sets of experimental data published in the literature: (1) Syngouna and Chrysikopoulos (2013) and (2) Walshe et al. (2010), both on the co-transport of viruses and clay colloids under saturated conditions, and (3) Syngouna and Chrysikopoulos (2015) for the co-transport of viruses and clay colloids under unsaturated conditions. The model results are found to be in good agreement with the observed BTCs under both saturated and unsaturated conditions. Then, the developed model was used to simulate the co-transport of viruses and colloids in porous media under unsaturated conditions, with the aim of understanding the relative importance of various processes on the co-transport of viruses and colloids. The virus retention in porous media in the presence of colloids is greater under unsaturated conditions as compared to the saturated conditions due to: (1) virus attachment to the air-water interface (AWI), and (2) co-deposition of colloids with attached viruses on its surface to the AWI. A sensitivity analysis of the model to various parameters showed that virus attachment to AWI is the most sensitive parameter affecting the BTCs of both free viruses and total mobile viruses, and has a significant effect on all parts of the BTC. The free and the total mobile virus BTCs are mainly influenced by parameters describing virus attachment to the AWI, virus interactions with mobile and immobile colloids, virus attachment to solid-water interface (SWI), and colloid interactions with SWI and AWI. The virus BTC is relatively insensitive to parameters describing the maximum adsorption capacity of the AWI for colloids, inlet colloid concentration, virus detachment rate coefficient from the SWI, maximum adsorption capacity of the AWI for viruses, and inlet virus concentration.

With a number of advantages hitherto unrecognized, nanoparticle-stabilized emulsions and foams have recently been proposed for enhanced oil recovery (EOR) applications. Long-distance transport of nanoparticles is a prerequisite for any such EOR applications. The transport of the particles is limited by the degree to which the particles are retained by the porous medium. In this work, experiments that quantify the retention and provide insight into the mechanisms for nanoparticle retention in porous media are described. Sedimentary rock samples (Boise sandstone and Texas Cream limestone) were crushed into single grains and sieved into narrow grain size fractions. In some cases, clay (kaolinite or illite) was added to the Boise sandstone samples. These grain samples were packed into long (1 ft – 15 ft) slim tubes (ID = 0.93 cm) to create unconsolidated sandpack columns. The columns were injected with aqueous dispersions of silica-cored nanoparticle (with and without surface coating) and flushed with brine. The nanoparticle effluent concentration history was measured and the nanoparticle recovery was calculated as a percentage of the injected nanoparticle dispersion. Fifty experiments were performed in this fashion, varying different experimental parameters while maintaining others constant to allow direct comparisons between experiments. The parameters analyzed in this thesis are: specific surface area of the porous medium, lithology, brine salinity, interstitial velocity, residence time, column length, and temperature. Our results indicate that retention is not severe, with an 8% average of the injected amount, for all our experiments. From the parameters analyzed, specific surface area was the most influential variable, with a linear effect on nanoparticle retention independently of lithology. Salinity increased nanoparticle retention slightly and delayed nanoparticle arrival. Velocity, residence time and length are coupled parameters and were studied jointly; they had a minor effect on retention. Temperature had a marginal effect, as we observed an approximate 2% increase in retention at 80°C compared to 21°C. Both surface coated and bare silica nanoparticles were successfully transported, so surface coating does not appear to be a prerequisite for transport for the particle and rock systems studied. / text