Modeling of nanoparticle transport in porous media



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The unique properties of engineered nanoparticles have many potential applications in oil reservoirs, e.g., as emulsion stabilizers for enhanced oil recovery, or as nano-sensors for reservoir characterization. Long-distance propagation (>100 m) is a prerequisite for many of these applications. With diameters between 10 to 100 nanometers, nanoparticles can easily pass through typical pore throats in reservoirs, but physicochemical interaction between nanoparticles and pore walls may still lead to significant retention. A model that accounts for the key mechanisms of nanoparticle transport and retention is essential for design purposes. In this dissertation, interactions are analyzed between nanoparticles and solid surface for their effects on nanoparticle deposition during transport with single-phase flow. The analysis suggests that the DLVO theory cannot explain the low retention concentration of nanoparticles during transport in saturated porous media. Moreover, the hydrodynamic forces are not strong enough for nanoparticle removal from rough surface. Based on different filtration mechanisms, various continuum transport models are formulated and used to simulate our nanoparticle transport experiments through water-saturated sandpacks and consolidated cores. Every model is tested on an extensive set of experimental data collected by Yu (2012) and Murphy (2012). The data enable a rigorous validation of a model. For a set of experiments injecting the same kind of nanoparticle, the deposition rate coefficients in the model are obtained by history matching of one effluent concentration history. With simple assumptions, the same coefficients are used by the model to predict the effluent histories of other experiments when experimental conditions are varied. Compared to experimental results, colloid filtration model fails to predict normalized effluent concentrations that approach unity, and the kinetic Langmuir model is inconsistent with non-zero nanoparticle retention after postflush. The two-step model, two-rate model and two-site model all have both reversible and irreversible adsorptions and can generate effluent histories similar to experimental data. However, the two-step model built based on interaction energy curve fails to fit the experimental effluent histories with delay in the leading edge but no delay in the trailing edge. The two-rate model with constant retardation factor shows a big failure in capturing the dependence of nanoparticle breakthrough delay on flow velocity and injection concentration. With independent reversible and irreversible adsorption sites the two-site model has capability to capture most features of nanoparticle transport in water-saturated porous media. For a given kind of nanoparticles, it can fit one experimental effluent history and predict others successfully with varied experimental conditions. Some deviations exist between model prediction and experimental data with pump stop and very low injection concentration (0.1 wt%). More detailed analysis of nanoparticle adsorption capacity in water-saturated sandpacks reveals that the measured irreversible adsorption capacity is always less than 35% of monolayer packing density. Generally, its value increases with higher injection concentration and lower flow velocities. Reinjection experiments suggest that the irreversible adsorption capacity has fixed value with constant injection rate and dispersion concentration, but it becomes larger if reinjection occurs with larger concentration or smaller flow rate.