The manipulation of a nanoconfined fluid flow is a great challenge and is critical in both fundamental research and practical applications. Compared with chemical or biochemical stimulation, the use of temperature as controllable, physical stimulation possesses huge advantages, such as low cost, easy operation, reversibility, and no contamination. We demonstrate an elegant, simple strategy by which temperature stimulation can readily manipulate the nanoconfined water flow by tuning interfacial and viscous resistances. We show that with an increase in temperature, the water fluidity is decreased in hydrophilic nanopores, whereas it is enhanced by at least four orders of magnitude in hydrophobic nanopores, especially in carbon nanotubes with a controlled size and atomically smooth walls. We attribute these opposing trends to a dramatic difference in varying surface wettability that results from a small temperature variation.
Polymer degradation is critical for polymer flooding because it can significantly influence the viscosity of a polymer solution, which is a dominant property for polymer enhanced oil recovery (EOR). In this work, physical experiments and numerical simulations were both used to study partially hydrolyzed polyacrylamide (HPAM) degradation and its effect on polymer flooding in heterogeneous reservoirs. First, physical experiments were conducted to determine basic physicochemical properties of the polymer, including viscosity and degradation. Notably, a novel polymer dynamic degradation experiment was recommended in the evaluation process. Then, a new mathematical model was proposed and an in-house three-dimensional (3D) two-phase polymer flooding simulator was designed to examine both polymer static and dynamic degradation. The designed simulator was validated by comparison with the simulation results obtained from commercial software and the results from the polymer flooding experiments. This simulator further investigated and validated polymer degradation and its effect. The results of the physical experiments showed that the viscosity of a polymer solution increases with an increase in polymer concentration, demonstrating their underlying power law relationship. Moreover, the viscosity of a polymer solution with the same polymer concentration decreases with an increase in the shear rate, demonstrating shear thinning. Furthermore, the viscosity of a polymer solution decreased with an increase in time due to polymer degradation, exhibiting an exponential relationship. The first-order dynamic degradation rate constant of 0.0022 day−1 was greater than the first-order static degradation rate constant of 0.0017 day−1. According to the simulation results for the designed simulator, a 7.7% decrease in oil recovery, after a cumulative injection volume of 1.67 pore volume (PV) was observed between the first-order dynamic degradation rate constants of 0 and 0.1 day−1, which indicates that polymer degradation has a detrimental effect on polymer flooding efficiency.
Summary
We demonstrate the effectiveness of a non-Arrhenius kinetic upscaling approach for in-situ-combustion processes, first discussed by Kovscek et al. (2013). Arrhenius reaction terms are replaced with equivalent source terms that are determined by a work flow integrating both laboratory experiments and high-fidelity numerical simulations. The new formulation alleviates both stiffness and grid dependencies of the traditional Arrhenius approach. Consequently, the computational efficiency and robustness of simulations are improved significantly. In this paper, we thoroughly investigate the performance of the non-Arrhenius upscaling method compared with Arrhenius kinetics. We investigate robustness by considering grid effects and sensitivity to heterogeneity. Performance improvements of the new kinetic upscaling approach compared with traditional Arrhenius kinetics are demonstrated through numerical experiments in one and two dimensions for both homogeneous- and heterogeneous-permeability fields.
In traditional thermal reactive reservoir simulation, mass and energy balance equations are solved numerically on discretized reservoir grid blocks. The reaction terms are calculated through Arrhenius kinetics using cell-averaged properties, such as averaged temperature and reactant concentrations. The chemical reaction front is physically very narrow, typically a few inches thick. To capture accurately this front, centimeter-sized grids are required that are orders of magnitude smaller than the affordable grid block sizes for full field reservoir models. We propose a new method based on a non-Arrhenius kinetic upscaling approach. We do not resolve the combustion front on the grid, but instead use a subgrid-scale model that captures the overall effects of the combustion reactions on flow and transport, i.e. the amount of heat released, the amount of oil burned and the reaction products generated. The subgrid-scale model is calibrated using fine-scale highly accurate numerical simulation and laboratory experiments. This approach significantly improves the computational speed of in-situ combustion simulation as compared to traditional methods. We are currently developing a field-scale simulator using the above ideas. Test cases illustrate the solution consistency when scaling up the grid sizes in multidimensional heterogeneous problems. The methodology is also applicable to other subsurface reactive flow modeling problems with fast chemical reactions and sharp fronts.
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