Publications
2024
- T. Kim , W. S. Han , S. Yoon , P. K. Kang , J. Shin , and M. J. NamJournal of Hazardous Materials
A 3D high-resolution subsurface characteristic (HSC) numerical model to assess migration and distribution of subsurface DNAPLs was developed. Diverse field data, including lithologic, hydrogeologic, petrophysical, and fracture information from both in situ observations and laboratory experiments were utilized for realistic model representation. For the first time, the model integrates hydrogeologic characteristics of both porous (unconsolidated soil (US) and weathered rock (WR)) and fractured rock (FR) media distinctly affecting DNAPLs migration. This allowed for capturing DNAPLs behavior within US, WR, and FR as well as at the boundary between the media, simultaneously. In the 3D HSC model, hypothetical 100-year DNAPLs contamination was simulated, quantitatively analyzing its spatiotemporal distributions by momentum analyses. Twelve sensitivity scenarios examined the impact of WR and FR characteristics on DNAPLs migration, delineating significant roles of WR. DNAPLs primarily resided in WR due to low permeability and limited penetration into FR through sparse inlet fractures. The permeability anisotropy in WR was most influential to determine the DNAPLs fate, surpassing the impacts of FR characteristics, including rock matrix permeability, fracture aperture size, and fracture + rock mean porosity. This study first attempted to apply the field-data-based multiple geological media concept in the DNAPLs prediction model. Consequently, the field-scale effects of WR and media transitions, which have been often overlooked in evaluating DNAPLs contamination, were underscored.
2023
- H. Cao , S. Yoon , Z. Xu , L. Pyrak-Nolte , E. Breciani , and P. K. KangWater Resources Research
- L. Wang , S. Yoon , L. Zheng , T. Wang , X. Chen , and P. K. KangJournal of Hydrology
- S. Yoon , J. D. Hyman , W. S. Han , and P. K. KangJournal of Geophysical Research - Solid Earth
Understanding mechanistic causes of non-Fickian transport in fractured media is important for many hydrogeologic processes and subsurface applications. This study elucidates the effects of dead-end fractures on non-Fickian transport in three-dimensional (3D) fracture networks. Although dead-end fractures have been identified as low-velocity regions that could delay solute transport, the direct relation between dead-end fractures and non-Fickian transport has been elusive. We systematically generate a large number of 3D discrete fracture networks with different fracture length distributions and fracture densities. We then identify dead-end fractures using a novel graph-based method. The effect of dead-end fractures on solute residence time maximizes at the critical fracture density of the percolation threshold, leading to strong late-time tailing. As fracture density increases beyond the percolation threshold, the network connectivity increases, and dead-end fractures diminish. Consequently, the increase in network connectivity leads to a reduction in the degree of late-time tailing. We also show that dead-end fractures can inform about main transport paths, such as the mean tortuosity of particle trajectories. This study advances our mechanistic understanding of solute transport in 3D fracture networks.
- Z. Xu , H. Cao , S. Yoon , P. K. Kang , Y. -S. Jun , T. Keneafsey , J. M. Sheets , D. Cole , and L. Pyrak-NolteScientific Reports
Many challenges related to carbon-dioxide (CO2) sequestration in subsurface rock are linked to the injection of fluids through induced or existing fracture networks and how these fluids are altered through geochemical interactions. Here, we demonstrate that fluid mixing and carbonate mineral distributions in fractures are controlled by gravity-driven chemical dynamics. Using optical imaging and numerical simulations, we show that a density contrast between two miscible fluids causes the formation of a low-density fluid runlet that increases in areal extent as the fracture inclination decreases from 90∘ (vertical fracture plane) to 30∘. The runlet is sustained over time and the stability of the runlet is controlled by the gravity-driven formation of 3D vortices that arise in a laminar flow regime. When homogeneous precipitation was induced, calcium carbonate covered the entire surface for horizontal fractures (0∘). However, for fracture inclinations greater than 10∘, the runlet formation limited the areal extent of the precipitation to less than 15% of the fracture surface. These insights suggest that the ability to sequester CO2 through mineralization along fractures will depend on the fracture orientation relative to gravity, with horizontal fractures more likely to seal uniformly.
- W. Lee , S. Yoon , and P. K. KangPhysical Review Fluids
Fluid inertia is known to exert a dominant control over transport processes in fracture flows. In particular, recirculating flows readily arise in inertial rough fracture flows and have been shown to cause anomalous transport by trapping particles. However, understanding of the combined effects of fluid inertia and solute diffusion on reactive transport involving fluid-solid reactions has thus far been elusive. This study investigates reactive transport involving an irreversible fluid-solid bimolecular reaction for wide ranges of Reynolds (Re) and Péclet (Pe) numbers and elucidates how the interplay between inertia and diffusion effects controls the dynamics of reactive transport. Solute diffusion (Pe) controls mainly the total reaction amount, whereas fluid inertia (Re) governs the reaction dynamics by inducing complex flow structures such as flow channeling and recirculating flows. Specifically, recirculating flows are shown to facilitate fluid-solid reactions by increasing the residence time of particles near the fluid-solid interfaces, and such trapping effects increase as Pe increases. Further, flow channeling and recirculating flows exert dominant control over the transport of both reactants and products. We elucidate the reactive transport dynamics by analyzing particle trajectories and quantifying Lagrangian velocity statistics and reaction-related measures. Based on the improved understanding, we then propose an upscaled reactive transport model that incorporates Lagrangian velocity statistics and velocity-dependent reaction probability, and show that the upscaled model successfully captures reactive transport over wide ranges of Re and Pe.
- S. Yoon , S. Lee , J. Zhang , L. Zeng , and P. K. KangJournal of Hydrology
Groundwater contamination is an exacerbating global issue that severely threatens human health, and subsurface remediation thus has gained increased interest in recent years. To effectively remediate subsurface contaminated sites, one needs to identify the location of contaminant sources and characterize contaminant spreading. Groundwater contamination is often driven by multiple contaminant sources, making source identification problems challenging. Further, when the densities of dissolved contaminants and ambient groundwater differ, the resultant variable-density flows add complexity to the task of source identification. However, most previous studies are limited to a single source identification in a two-dimensional aquifer. This study presents a novel inversion method based on ensemble smoothing that identifies the locations of multiple contaminant sources in three-dimensional heterogeneous aquifer systems. A new covariance localization algorithm based on a clustering method is integrated into the inversion method, which improves the accuracy of multi-source identification. Using the proposed inversion framework, we successfully estimate the locations of multiple contaminant sources and three-dimensional permeability fields utilizing pressure and concentration data from monitoring wells. Further, we investigate and elucidate the effects of aquifer heterogeneity and variable-density flows on multiple source identification. We find that variable-density flow increases the data information contents and thus improves the inversion accuracy. This is the first-time demonstration of the effects of variable-density flow on the inversion accuracy of multi-source identification in three-dimensional heterogeneous aquifer systems.
2022
- J. Lee , W. S. Han , P. K. Kang , S. Yoon , S. Choung , J. Hwang , and J. ShinJournal of Hydrology
Understanding the long-term fate and transport of radiocesium (137Cs) through porous and fractured aquifers is critical for the risk assessment of nuclear accidents. In particular, characterizing 137Cs transport below a dam storing potable water is critical for assessing the risk of 137Cs migration. In this study, a 2D cross-sectional aquifer model was developed based on Paldang Reservoir in South Korea, and transport of desorbed 137Cs beneath a dam was investigated systematically. Various scenarios investigated 137Cs transport within the reported ranges of distribution coefficient (Kd) and local temperature conditions (basal heat flow and reservoir-bottom temperature) affecting the 137Cs desorption rate and hydrogeologic heterogeneity (hydraulic conductivity and fracture networks). The characteristics of the 137Cs plume represented by the average plume concentration and the migration rate of the mass center were assessed, and the health risk of chronic exposure for humans was predicted. In base-case (K=8.64×10-2 m/day and Kd=10 mL/g), approximately 0.06% of initially released 137Cs was transported downstream over 300 years; the maximum migration rate was 5.1×10-4 m/day, and a maximum annual radioactive dose was 4.5 mSv/y after 230 years. The notable effect of Kd on the migration rate (5.1×10-5–9.9×10-4 m/day) and annual dose (9.1×10-11–130 mSv/y) indicates that the Kd is a critical parameter that controls the transport of 137Cs in the subsurface aquifer. The effect of temperature on 137Cs transport was relatively insignificant, but it still had a noticeable effect, especially on the desorption rate. In addition, 50 realizations of heterogeneous K and Kd were generated to evaluate the influence of physical and chemical heterogeneity on 137Cs transport. The migration rate and annual dose of 137Cs plume showed large variability when K and Kd were correlated. Finally, 137Cs transport was evaluated in fractured aquifers and assessed the importance of fracture orientation and connectivity.
2021
- S. Yoon , and P. K. KangTransport in Porous Media
Mxing and reaction in rough channel flows govern various applications in engineering and natural processes such as microfluidic mixers and fracture flows, where channel wall roughness and flow inertia can vary widely. The combined effects of channel roughness and flow inertia induce complex flow structures such as recirculating flows; along with diffusion-reaction processes, leading to a wide range of reactive transport behaviors. Currently, we lack a mechanistic understanding of mixing-induced reactive transport in rough channel flows. To establish a comprehensive understanding of bimolecular reactive transport in rough channel flows, we conduct a simulation-based study with varying channel roughness, Reynolds number (Re), and Péclet number (Pe). The simulation results reveal the distinctive effects of roughness, inertia (Re), and diffusion (Pe) on reactive transport. It is found that first passage time distributions between conservative and reactive tracers are significantly different, especially in mixing-limited pre-asymptotic regimes. The interplay between roughness and inertia leads to complex flow structures, which determines a spatially heterogeneous fluid stretching field. We show that the fluid stretching field together with solute diffusion leads to a spatially non-uniform chemical reactivity field, and the non-uniform chemical reactivity explains the distinguishing transport behaviors between conservative and reactive tracers. Further, we characterize the non-uniform reactivity with a reaction probability model that is parameterized with Lagrangian velocity magnitudes. Finally, we upscale reactive transport by incorporating the velocity-dependent reaction model into a spatial Markov model.
- S. Yoon , M. Dentz , and P. K. KangJournal of Fluid Mechanics
We study the reactive displacement of two miscible fluids in channel flows and establish a quantitative link between fluid stretching and chemical reactivity. At the mixing interface, the two fluids react according to the instantaneous irreversible bimolecular reaction A+B→ C. We simulate the advection–diffusion–reaction problem using a random walk based reactive particle method that is free of numerical dispersion. The relative contributions of stretching and diffusion to mixing-limited reaction is controlled by changing the Péclet number, and the channel roughness is also systematically varied. We observe optimal ranges of fluid stretching that maximize reactivity, which are captured by a Lagrangian stretching measure based on an effective time period that honours the stretching history. We show that the optimality originates from the competition between the enhanced mixing by fluid stretching and the mass depletion of the reactants. We analytically derive the spatial distribution of reaction products using a lamellar formulation and successfully predict the optimal ranges of fluid stretching, which are consistent across different levels of channel roughness. These findings provide a mechanistic understanding of how the interplay between fluid stretching, diffusion and channel roughness controls mixing-limited reactions in rough channel flows, and show how reaction hot spots can be predicted from the concept of optimal fluid stretching.
- S. Yoon , and P. K. KangPhysical Review Fluids
We study how the complex interplay between channel roughness, inertia, and diffusion controls tracer transport in rough channel flows. We first simulate flow and tracer transport over wide ranges of channel roughness, Reynolds number (Re), and Péclet number (Pe) observable in nature. Pe exerts a first-order control on first-passage time distributions, and the effect of roughness on the tracer transport becomes evident as Re increases. The interplay between the roughness and Re causes recirculating flows, which intensify or suppress anomalous transport depending on Pe. At infinite Pe, the late-time scaling follows a universal power-law scaling, which is explained by conducting a scaling analysis. With extensive numerical simulations and stochastic modeling, we show that the roughness, inertia, and diffusion effects are encoded in Lagrangian velocity statistics represented by velocity distribution and velocity correlation. We successfully reproduce anomalous transport using an upscaled stochastic model that honors the key Lagrangian velocity statistics.
2020
- S. Yoon , S. Lee , J. R. Williams , and P. K. KangAdvances in Water Resources
Predicting variable-density flow and transport in aquifers is critical for the management of many coastal saline aquifers. Accurate characterization of hydrogeological parameters is critical for prediction, and the characterization is often conducted by assimilating data into models. However, few studies have investigated the underlying physics controlling the value-of-information (VOI) of data for aquifer characterization. In this study, we show how a greater understanding of the underlying physics controlling pressure and concentration data coupling can lead to improved characterization. In variable-density flow, the key physics that controls the VOI of pressure and concentration data is the non-linear coupling between flow and transport via fluid density which causes the pressure field to experience transient changes according to the evolution of salinity distribution. We first demonstrate the coupling between pressure and concentration data using information theory, and then systematically investigate how the variable-density flow impacts the VOI of these data in relation to permeability estimation. Using an ensemble Kalman filter, we estimate the permeability field of saline aquifer systems in two scenarios of data usage: pressure data only, and pressure and concentration data jointly. This study demonstrates that, regardless of the data usage scenario, the maximum VOI of data is obtained when free convection and forced convection are balanced. We further show that the advantage of joint inversion of pressure and concentration data decreases as the coupling effect between flow and transport increases. Finally, we study how the level of permeability field heterogeneity affects the coupling, which in turn controls VOI of pressure and concentration data.
2017
- S. Yoon , J. R. Williams , R. Juanes , and P. K. KangAdvances in Water Resources
The injection and storage of freshwater in saline aquifers for the purpose of managed aquifer recharge is an important technology that can help ensure sustainable water resources. As a result of the density difference between the injected freshwater and ambient saline groundwater, the pressure field is coupled to the spatial salinity distribution, and therefore experiences transient changes. The effect of variable density can be quantified by the mixed convection ratio, which is a ratio between the strength of two convection processes: free convection due to the density differences and forced convection due to hydraulic gradients. We combine a density-dependent flow and transport simulator with an ensemble Kalman filter (EnKF) to analyze the effects of freshwater injection rates on the value-of-information of transient pressure data for saline aquifer characterization. The EnKF is applied to sequentially estimate heterogeneous aquifer permeability fields using real-time pressure data. The performance of the permeability estimation is analyzed in terms of the accuracy and the uncertainty of the estimated permeability fields as well as the predictability of breakthrough curve arrival times in a realistic push-pull setting. This study demonstrates that injecting fluids at a rate that balances the two characteristic convections can maximize the value of pressure data for saline aquifer characterization.
2016
- S. Yoon , Z. M. Alghareeb , and J. R. WilliamsSPE Journal
Subsurface flow modeling is an indispensable task for reservoir management, but the associated computational cost is burdensome because of model complexity and the fact that many simulation runs are required for its applications such as production optimization, uncertainty quantification, and history matching. To relieve the computational burden in reservoir flow modeling, a reduced-order modeling procedure based on hyper-reduction is presented. The procedure consists of three components: state reduction, constraint reduction, and nonlinearity treatment. State reduction based on proper orthogonal decomposition (POD) is considered, and the impact of state reduction, with different strategies for collecting snapshots, on accuracy and predictability is investigated. Petrov–Galerkin projection is used for constraint reduction, and a hyper-reduction that couples the Petrov–Galerkin projection and a gappy reconstruction is applied for the nonlinearity treatment. The hyper-reduction method is a Gauss–Newton framework with approximated tensors (GNAT), and the main contribution of this study is the presentation of a procedure for applying the method to subsurface flow simulation. A fully implicit oil/water two-phase subsurface flow model in 3D space is considered, and the application of the proposed hyper-reduced-order modeling procedure achieves a runtime speedup of more than 300 relative to the full-order method, which cannot be achieved when only constraint reduction is adopted.
2013
- D. Veneziano , and S. YoonWater Resources Research
2010
- S. Yoon , W. Cho , J.-H. Heo , and C. E. KimStochastic Environmental Research and Risk Assessment
This study develops a full Bayesian GEV distribution estimation method (BAYBETA), which contains a semi-Bayesian framework of generalized maximum likelihood estimator (GMLE), to make full use of several advantages of the Bayesian approach especially in uncertainty analysis. For the full Bayesian framework, the optimal hyperparameter of beta prior distribution on the shape parameter of the GEV distribution is found as (6.4990, 8.7927) through simulation-based analysis. In a performance comparison analysis, the performances of BAYBETA, which adopts beta(6.4990, 8.7927) as prior density on the shape parameter of the GEV distribution, are almost the same as or slightly better than GML, outperforming MOM, ML, and LM in terms of root mean square error (RMSE) and bias when the shape parameter is negative. Also, a case study of two hydrologic extreme value data shows that the traditional uncertainty analysis using asymptotic approximation of ML and GML has limitations in describing the uncertainty in high upper quantiles, while the proposed full Bayesian estimation method BAYBETA provides a consistent and complete description of the uncertainty.