Advances in Water Resources最新文献

There are still many unclear mechanisms in the multiphase reactive flow with solid dissolution processes. In this study, the reactive transport processes coupled with solid dissolution and self-induced multiphase flow in three-dimensional (3D) structures with increasing complexity is studied by developing a 3D computational microfluidic method, which considers multiphase flow, interfacial mass transport, heterogeneous chemical reactions, and solid structure evolution. Solid dissolution diagram in a simple channel in the framework of multiphase flow is proposed, with six coupled multiphase flow and solid dissolution patterns identified and the transition between different patterns discussed. Then, multiphase reactive flow in a porous chip is further studied, and the interesting 3D phenomena are discovered, including enhanced solid dissolution in the middle and enriched bubble generation at the corner along the thickness direction. Considering the importance of reactive surface area, correlations of reactive surface area-porosity-saturation with different dissolution patterns are proposed based on the pore-scale results. Finally, the computational microfluidic model is extended to investigate the multiphase reactive flow in a 3D digital core. Different dissolution patterns are recognized using the local porosity evolution character, and the corresponding pore size distribution and bubble characteristics are deciphered. These findings advance understanding of multiphase reactive transport processes and contribute to improve continuum-scale reactive transport modeling.

Knowing local concentration distributions is important for transport and mixing, particularly in porous media, yet a comprehensive understanding of them remains a challenge. Computing advancements have enabled high-resolution pore-scale simulations, offering an unprecedented opportunity for in-depth investigation of mixing. In this study we use simulation data to examine concentration distributions at the pore scale in the context of longitudinal (pseudo-one-dimensional) solute transport through a porous column. These distributions arise in a single column from heterogeneous flow at the pore-scale, which gets averaged out when upscaled and are not with reference to statistics across multiple random realizations. To measure these distributions, we first devise a semi-analytical approach to estimate the mean effective transport velocity profile for a non-uniform Darcy-scale fluid velocity, which unavoidably occurs due to the presence of lateral boundaries. This development allows sampling micro-scale concentrations over a moving surface that possesses a well defined Darcy-scale mean concentration, enabling empirical computation of the local concentration distribution. As an added benefit we find that our approach allows for the estimation of transverse dispersion coefficients, which is not typical in traditional column experiments. The implemented approach can estimate it via inverse modeling, and it agrees closely with previously published experimental data across the range of Peclet numbers we studied. We found that the measured pore-scale concentration probability density functions are best represented by a beta distribution, thus validating this longstanding hypothesis with direct evidence. Furthermore, we propose a model to describe the temporal and spatial evolution of the local concentration pdf, as well as its Péclet number dependence.

To realize the transition of our society to a low-carbon future with innovative subsurface energy solutions, understanding the dynamic behavior of gas invading multi-fluid systems in underground pore space is critical. In this work, a joint approach of flow imaging and digital image processing is employed to investigate the fingering dynamics of gas invading multi-fluids in porous media. We examined various gas (G) invasion scenarios of a high-viscosity defending liquid (HL), low-viscosity defending liquid (LL), and their co-existing multi-fluid system, focusing on the viscosity effect. Quantification of phase saturation shows that the displacement efficiency follows the order of G$\to$(L$\to$L) $>$ L$\to$L $>$ G$\to$L, regardless of the varieties in injection flow rate in the viscous-dominated flow regime. In other words, the enhancement in displacement efficiency and potential energy savings are achieved by solely introducing a third phase without the cost of the higher pumping power. When gas invades the HL and LL multi-liquid system, the fingering pattern in G$\to$(HL$\to$LL) and G$\to$(LL$\to$HL) significantly differs and highly depends on the sequential occupation of HL and LL in the pore spaces. The previously unobserved yarn-liked gas pattern in G$\to$(LL$\to$HL) is suspected as the main reason for the fast gas displacement. Through Local dynamics analysis, we identified that the preferential invasion into interconnected LL channels and the inhibitory effect of scattered HL on bypass invasion are the primary mechanisms behind the formation of yarn-liked fingers. We classified two distinct categories of ganglia mobilization and connection in G$\to$(LL$\to$HL), i.e. “catch up to connect” and “expand to connect”. Finally, the topological connectivity of the gas finger in G$\to$(LL$\to$HL) is evaluated using Euler number. Euler number shows an ascending trajectory before breakthrough, followed by a rapid descent and stabilization at steady state. This signifies that disconnected ganglia emerge before breakthrough and subsequently expand and reconnect. Our new findings are of great importance for subsurface extraction/storage strategy innovation through enriching multi-fluids injection scenarios.

The Representative Elementary Volume (REV) concept, a cornerstone in porous system heterogeneity assessment, was initially conceived to determine the minimal domain volume suitable for homogenization and upscaling. However, the definition of REV and usability in continuum-scale models is vague. In this study, we conduct comprehensive REV analyses on multiple samples, encompassing a range of scalar and vector metrics. Our investigation probes the representativity of crucial medium characteristics, including porosity, permeability, and Euler density, alongside descriptors rooted in pore-network statistics, correlation functions, and persistence diagrams. We explore both deterministic and statistical REV sizes (dREV and sREV), facilitating a robust comparative assessment. Crucially, we introduce an novel methodology tailored for harnessing vector metrics, known for their ability to reveal intricate structural insights. Our results underscore the superiority of the sREV approach, particularly for low-content metrics, addressing inherent limitations of dREV in characterizing homogeneities in such cases. Furthermore, the sREV approach incorporates stationarity analysis into REV evaluation, ensuring result consistency between sREV and dREV under stationarity conditions. Encouragingly, our findings suggest that high-information-content metrics, notably correlation functions combined with persistence diagrams, have the potential to establish a universal REV for steady-state physical properties. This proposition warrants further verification through a comprehensive assessment and comparison of REV values across major physical properties. REV analysis plays a pivotal role not only in assessing medium properties but also in scrutinizing different descriptors of 3D images – we note that REV analysis and image/field stationarity analysis are ultimately the same techniques under the hood. The discussion based on obtained results and recent finding by other researchers advances the understanding of REV within porous media, introduces a versatile methodology with broader applications, and is expected to be useful in numerous fields including materials science, cosmology, machine learning, and more. We redefine the classical definition of REV by adding stationarity condition and upper/lower bounds on its volume. While for simplicity, in this work we shall mainly focus on porous media as immediately applicable to digital rock, petrophysics, hydrology and soil physics problems, the developed mythology can be applied to other material types - composites, biological tissues, granular matter, food engineering and numerous other types of matter.

Accurate estimation of contaminant transport in cementitious material using numerical tools plays a key role in the risk assessments of nuclear waste disposal. At the pore scale, the increase of microbial activity, such as microbially induced calcite precipitation on cementitious material, causes changes in solid surface topography, pore network geometry, and pore water chemistry, which affect contaminant transport at the core scale and beyond. Consequently, a meaningful estimation of contaminant migration in the subsurface requires a pore-scale investigation of the influence of microbial activity on transport processes. In this study, a pore-scale reactive transport model is presented to simulate the physicochemical processes resulting from microbially induced calcite precipitation on a cement surface. Numerical investigations focus on modeling the reactive transport in a two-dimensional flow-through cell. The model results are validated by experimental data showing an increase in pH and a decrease in calcium concentration due to microbially induced calcite precipitation. Our results show heterogeneous calcite precipitation under transport-limited conditions and homogeneous calcite precipitation under reaction-limited conditions, resulting in non-uniform and uniform changes in the material surface topography. Moreover, power spectral density analysis of the surface data demonstrates that microbially induced calcite precipitation affects the surface topography via both general changes over the entire frequency and local modifications in the high-frequency region. The sensitivity studies provide a comprehensive understanding of the evolution of surface topography due to the microbially induced calcite precipitation at the pore scale, thus contributing to an improved predictability of contaminant transport at the core scale and beyond.

Subterranean estuaries (STE) are hotspots of biogeochemical reactions. Here, dissolved constituents in waters of terrestrial and marine origin are transformed before they discharge to the coastal oceans. The involved biogeochemical reactions are complex and non-linear, calling for the application of numerical reactive transport modeling (RTM) to improve the process understanding. The aim of this study was to assess the roles of organic matter degradation and coupled secondary mineral reactions for the fate of dissolved species in STEs of sandy beaches. A comprehensive RTM approach was applied for this purpose, accounting for the effects of ion activities, pH, pe, redox reactions, mineral equilibria (calcite, goethite, siderite, iron sulfide, hydroxyapatite and vivianite) as well as surface complexation. Results show that the STE biogeochemistry and associated species fluxes are very sensitive to the assumed reaction network. For example, inorganic carbon and pH were largely controlled by calcite and siderite dynamics, and dissolved Fe²⁺ and HS^- were precipitated as goethite, siderite and/or iron sulfides. Moreover, PO₄^3- concentrations were affected by both the formation of vivianite or hydroxyapatite as well as surface complexation. This work helped to establish the relative importance of some of the major biogeochemical processes in the STE. However, further field studies are needed to understand which processes play a role in real-world STEs, including an exploration of the deep subsurface of STEs. Such field-based observations will improve our conceptual process understanding, which is key to developing well-constrained RTMs.

Permeability and effective dispersion tensors are critical parameters to characterize flow and transport in porous media at the continuum scale. Homogenization theory defines a framework in which such effective properties are first computed from solving a closure problem in a repeating unit cell of the periodic microstructure and then used in a macroscopic formulation for efficient computation. The closure problem is formulated as a local boundary value problem subjected to global constraints, which guarantee the uniqueness of the solution and can be difficult to satisfy for complex geometries and at high flow conditions. These constraints also ensure that pore-scale pressure, velocity, and concentration fields can be accurately reconstructed from the closure variable. Building on previous work, here we present a framework that allows to satisfy global constraints associated to both the permeability and the dispersion closure problems by introducing two artificial time scales. The algorithm, called ${\tau }^2$-SIMPLE, computes both permeability and effective dispersion given an arbitrarily complex geometry and flow condition. This algorithm is demonstrated to be accurate for both 2D and 3D geometries across varying flow conditions, and thus it can be used to quickly characterize effective properties from porous media images in many applications.

Hydrodynamic simulations in shallow water environments require careful consideration of the Wetting and Drying (WD) processes, which poses challenges to accurately modeling moving boundaries. This study introduces a novel method called the flow resistance method (FRM), which builds upon the foundation of the Negative-Depth Method (NDM) to tackle the intricacies of the moving boundary problem. Inspired by the Navier-Stokes/Brinkman (NSB) model from porous media theory, FRM incorporates a continuous function related to additional flow resistance that is proportional to the flow velocity. This approach facilitates a seamless transition between the exposed bed and fluid area wherein the additional flow resistance becomes 0 within the fluid area and approaches infinity in the exposed bed. Consequently, FRM adeptly and implicitly manages the moving boundary problem, causing a rapid decay of flow velocity to 0 in the exposed bed. In order to test the performance of FRM, four typical numerical experiments were conducted, along with an examination of a real-life case. Accuracy, robustness, and computational efficiency were assessed as key performance indicators. The simulations demonstrate that FRM adeptly tracks the moving water front, yielding precise results. Furthermore, when compared to established methods such as the Element Removal Method (ERM) and NDM, FRM exhibits broader applicability and achieves significant enhancements in the key performance indicators. These findings underscore the promising potential and broad applications of FRM in the field.

Underground hydrogen (H${}_2$) storage in saline aquifers is a viable solution for large-scale H${}_2$ storage. Due to its remarkably low viscosity and density, the flow of H${}_2$ within saline aquifers exhibits strong instability, which needs to be thoroughly investigated to ensure safe operations at the storage site. For the first time, we develop a lattice Boltzmann model tailored for pore-scale simulations of the H${}_2$-brine system under typical subsurface storage conditions. The model captures the significant contrast of fluid properties between H${}_2$ and brine, and it offers the flexibility to adjust the contact angle to suit varying wetting conditions. We show that the snap-off is enhanced in a system with a high capillary number and a small contact angle. These conditions lead to a low recovery factor, which is unfavorable for H${}_2$ production from the aquifer. Moreover, the relative permeability curves, computed from the simulation results, exhibit distinct behaviors for H${}_2$ and brine. In the case of the wetting phase, the relative permeability can be quantified using the quadratic expression, whereas for the non-wetting phase, the relative permeability exhibits a nearly linear behavior, and saturation alone appears insufficient to characterize the relative permeability at large saturations of non-wetting phase. This implies that different formula for liquid and gas phases may be employed for continuum-scale simulations.

Understanding flow and transport in multiscale porous media is challenging due to the presence of a wide range of pore sizes. Recent imaging advances offer high-resolution characterization of the multiscale pore structures. However, simulating flow and transport in 3D digital images requires models to represent both the resolved and sub-resolution pore structures. We develop a hybrid pore-network-continuum modeling framework. The hybrid framework treats the smaller pores below the image resolution as a continuum using the Darcy-scale formalism and explicitly represents the larger pores resolved in the images employing a pore network model. We validate the hybrid model against direct numerical simulations for single-phase flow and solute transport and further demonstrate its applicability for simulating two-component gas transport in a shale rock sample. The results indicate that the new hybrid model represents the flow and transport process in multiscale porous media while being much more computationally efficient than direct numerical simulation methods for the range of simulated conditions.