Using a visualization setup, we characterized the solute transport in a micromodel filled with two fluid phases using direct, real-time imaging. By processing the time series of images of solute transport (dispersion) in a two fluid-phase filled micromodel, we directly delineated the change of transport hydrodynamics as a result of fluid-phase occupancy. We found that, in the water saturation range of 0.6-0.8, the macroscopic dispersion coefficient reaches its maximum value and the coefficient was 1 order of magnitude larger than that in single fluid-phase flow in the same micromodel. The experimental results indicate that this non-monotonic, non-Fickian transport is saturation- and flow-rate-dependent. Using real-time visualization of the resident concentration (averaged concentration over a representative elementary volume of the pore network), we directly estimated the hydrodynamically stagnant (immobile) zones and the mass transfer between mobile and immobile zones. We identified (a) the nonlinear contribution of the immobile zones to the non-Fickian transport under transient transport conditions and (b) the non-monotonic fate of immobile zones with respect to saturation under single and two fluid-phase conditions in a micromodel. These two findings highlight the serious flaws in the assumptions of the conventional mobile-immobile model (MIM), which is commonly used to characterize the transport under two fluid-phase conditions.

Hybrid pore-network and Lattice-Boltzmann permeability modelling accelerated by machine learning.

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It is well-known that solvent treatment and preconditioning play an important role in rejection and flux performance of membranes due to solvent-induced swelling and solvent adsorption. Investigations into the effect of solvent treatment are scarce and application specific, and were limited to a few solvents only. This study reveals the trend in solvent treatment based on solvent polarity in a systematic investigation with the aim to harness such effect for intensification of membrane processes. Nine solvents with polarity indices ranging from 0.1 to 5.8 (hexane to acetonitrile) were used as treatment and process solvents on commercial Borsig GMT-oNF-2, Evonik Duramem 300, and emerging tailor-made polybenzimidazole membranes. TGA-GCMS, HS-GC-FID, and NMR techniques were employed to better understand the effect of solvent treatment on the polymer matrix of membranes. In this work, apart from the solvent treatment's direct effect on the membrane performance, a subsequent indirect effect on the ultimate separation process was observed. Consequently, a pharmaceutical case study employing chlorhexidine disinfectant and antiseptic was used to demonstrate the effect of solvent treatment on the nanofiltration-based purification. It is shown that treatment of polybenzimidazole membranes with acetone resulted in a 25% increase in product recovery at 99% impurity removal. The cost of the process intensification is negligible in terms of solvent consumption, mass intensity, and processing time.

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Conventional flow models based on Darcy's flow physics fail to model shale gas production data accurately. The failure to match field data and laboratory-scale evidence of non-Darcy flow has led researchers to propose various gas-flow models for the shale reservoirs. There is extensive evidence that suggests the size of the pores in shale is microscopic in the range of a few to hundreds of nanometers (also known as nanopores). These small pores are mostly associated with the shale's organic matter portion, resulting in a dual pore system that adds to the gas flow complexity. Unlike Darcy's law, which assumes that a dominant viscous flux determines a rock's permeability, shale's permeability leads to other flow processes besides viscous flow such as gas slippage and Knudsen diffusion. This work reviews the dominant gas-flow processes in a single nanopore on the basis of theoretical models and molecular dynamics simulations, and lattice Boltzmann modeling. We extend the review to pore network models used to study the gas permeability of shale.

Continuum‐scale models for two‐phase flow and transport in porous media are based on the empirical constitutive relations that highly depend on the porous medium heterogeneity at multiple scales including the microscale pore‐size correlation length. The pore‐size correlation length determines the representative elementary volume and controls the immiscible two‐phase invasion pattern and fluids occupancy. The fluids occupancy controls not only the shape of relative permeability curves but also the transport zonation under two‐phase flow conditions, which results in the non‐Fickian transport. This study aims to quantify the signature of the pore‐size correlation length on two‐phase flow and solute transport properties such as the capillary pressure‐ and relative permeability‐saturation, dispersivity, stagnant saturation, and mass transfer rate. Given the capability of pore‐scale models in capturing the pore morphology and detailed physics of flow and transport, a novel graphics processing unit (GPU)‐based pore‐network model has been developed. This GPU‐based model allows us to simulate flow and transport in networks with multimillions pores, equivalent to the centimeter length scale. The impact of the pore‐size correlation length on all aforementioned properties was studied and quantified. Moreover, by classification of the pore space to flowing and stagnant regions, a simple semianalytical relation for the mass transfer between the flowing and stagnant regions was derived, which showed a very good agreement with pore‐network simulation results. Results indicate that the characterization of the topology of the stagnant regions as a function of pore‐size correlation length is essential for a better estimation of the two‐phase flow and solute transport properties.

Density‐driven mixing resulting from CO 2 injection into aquifers leads to the CO 2 entrapment mechanism of solubility trapping. Crucially, the coupled flow‐geochemistry and effects of geochemistry on density‐driven mixing process for “sandstone rocks” have not been adequately addressed. Often, there are conflicting remarks in the literature as to whether geochemistry promotes or undermines dissolution‐driven convection in sandstone aquifers. Against this backdrop, we simulate density‐driven mixing in sandstone aquifers by developing a 2‐D modified stream function formulation for multicomponent reactive convective‐diffusive CO 2 mixing. Two different cases corresponding to laboratory and field scales are studied to investigate the effect of rock‐fluid interaction on density‐driven mixing and the role of mineralization in carbon storage over the project life time. A complex sandstone mineralogical assemblage is considered, and solid‐phase reactions are assumed to be kinetic to study the length‐ and time‐scale dependency of the geochemistry effects. The study revealed nonuniform impact of rock‐fluid and fluid‐fluid interaction in early‐ and late‐time stages of the process. The results show that for moderate Rayleigh (Ra) numbers, rock‐fluid interactions adversely affect solubility trapping while improving the total carbon captured through mineral trapping. Simulation results in the range of 1,500 <  Ra < 55,000 in the field‐scale model showed more pronounced impact of geochemistry for higher Ra numbers, as geochemistry stimulates the convective instabilities and improves the total sequestered carbon. This study gives new insights into the effect of rock‐fluid interactions on density‐driven mixing and solubility trapping in sandstone aquifers to improve estimation of the carbon storage capacity in deep saline aquifers.