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Training dataset for the Generic Aquifer Component of NRAP-Open-IAM. Consists of the results of 62,500 STOMP-CO2 simulations of brine and CO2 leakage of varying rates and salinity into aquifers of varying thickness, depth, porosity, permeability, anisotropy and initial salinity. Described in report https://www.pnnl.gov/main/publications/external/technical_reports/PNNL-32590.pdf
Geological, geophysical, hydrogeological, and hydrological evidence indicates that feeder dikes to lava flows play a role as confining units in the groundwater flow system underlying the Pahute Mesa area of underground nuclear testing at the Nevada National Security Site (NNSS). Of geological significance, the Pahute Mesa testing area is largely situated within the Silent Canyon caldera, which includes both tuffs and lavas that were fed by (and are connected to) intrusive rock units such as feeder dikes prior to and during volcanic eruptions (Orkild et al., 1968; Byers et al., 1976). Groundwater modeling results presented in this report support extension of “pool-dam” and “breach scenario” concepts presented in Jackson and Fenelon (2018) and Jackson et al. (2021) to low-permeability intrusive confining units (ICUs) such as feeder dikes that are expected to dissect and ring the caldera. As laterally extensive, steeply-dipping, and sub-parallel planar structures, ICUs can be expected to further compartmentalize groundwater flow in the volcanic aquifers systems at Pahute Mesa beyond the stratigraphically-defined tuff confining units (TCUs). ICUs provide an explanation for changes in water levels before and after the Cheshire test, detonated 2/14/76 (USDOE, 2015), and the unusually high horizontal gradient southwest of Cheshire. These ICU concepts are supported by groundwater modeling results presented in this report. The evidence and groundwater modeling results indicate that the downgradient extent of radionuclide contamination in some areas of Pahute Mesa could be overestimated by ignoring the confining effects of ICUs. On the other hand, contaminant extent could be underestimated by not considering transient flow effects and/or the re-equilibrated flow field caused by breaching of an ICU by an underground nuclear test.
The present work investigates mechanisms of permeability impairment as a result of low-salinity fluid injection into brine-saturated porous media containing dispersible clays. Here, we present a computational fluid dynamics model at the pore-scale to simulate detachment, migration and straining of fine particles in porous media. The model uses an immersed boundary method to simulate the motion of clay fines in a fluid. In addition to the hydrodynamic forces, we model the Derjaguin-Landau-Verwey-Overbeek forces (DLVO) between clay fines and grains. Our simulations show the impact of the injected fluid's salinity and velocity on the concentration of clay fines retained on the grain surface. We see clay particles dislodging from the grain surface in clusters of up to 12 particles. Our simulation results also demonstrate clogging of narrow pore spaces by the detached particles from the grain surfaces.
Here, this paper describes a system-level risk assessment for the Shenhua CO 2 storage site, China, using the National Risk Assessment Partnership Integrated Assessment Model for Carbon Storage (NRAP-IAM-CS). Here, we begin by determining the optimal number of Monte Carlo (MC) simulations to achieve CO 2 and brine leakage result convergence. Then, we calculate mass CO 2 and brine leakage to the atmosphere and a hypothetical shallow aquifer. Finally, we assess the geochemical impacts in the event of leakage as if there were a shallow freshwater aquifer at the Shenhua site. Simulation results show that leakage results tend to stabilize after 300 Monte Carlo simulations. When the three wells on site are assigned a permeability of 10 -11 m 2 (representing significantly leaking wells), moderate CO 2 and brine leakages occur, and the percentage of CO 2 leakage exceeds the threshold value we set based on the Intergovernmental Panel on Climate Change (IPCC). This is, however, unlikely to be the case for the Shenhua site. For all the other scenarios, the CO 2 leakage is trivial although there is still the possibility of CO 2 leakage into the groundwater aquifer exceeding the 1% threshold over 1000 years, assuming constant legacy wellbore permeability. For the significantly leaking scenario, there is a 10% probability to have a moderate (2.7 × 10 7 m 3 ) leakage-affected volume in the shallow aquifer with the pH below 6.5, and a large (1.4 × 10 8 m 3 ) volume with the total dissolved solids (TDS) above 500 ppm, hence pH and TDS may be considered for site monitoring plans. Based on the simulation results, there is a very low probability of significant CO 2 /brine leakage through the existing wells at the Shenhua CO 2 storage site.
To meet performance requirements, the next generation of gas separation membranes will need both high gas permeability and selectivity, attainable if we could coax adsorbates to minimize random Brownian motion and produce direction-specific diffusion along a desired axis. In this atomistic modeling study, we detail how direction-specific diffusion of CO 2 can be achieved in chiral hexagonal boron nitride nanotubes (hBNNTs) by means of a non-Knudsen diffusion mechanism. Our findings detail how this mechanism of diffusion is driven by interactions with the tube walls and enables the CO 2 molecules to diffuse along the nanotube’s z-axis with minimized collisions and directional changes. hBNNTs with chiral indices exhibit CO 2 diffusion rates faster than non-chiral tubes of comparable and larger diameters. Of the hBNNTs studied, a (7,3) tube appears to be ideally sized (3.7 Å radius) exhibiting CO 2 diffusion that is 3.4 times faster than diatomic N 2 . Applying this mechanism of diffusion to hypothetical sheet membranes prepared with aligned chiral (7,3) hBNNTs results in membranes with a calculated CO 2 /N 2 permselectivity of 170 and a CO 2 permeability limit of nearly 1.35 ×10 7 Barrer, readily surpassing the Robeson upper bound for CO 2 /N 2 separations.
We describe a novel framework for estimating subsurface properties, such as rock permeability and porosity, from time-lapse observed seismic data by coupling full-waveform inversion (FWI), subsurface flow processes, and rock physics models. For the inverse modeling, we handle the back propagation of gradients by an intrusive automatic differentiation strategy that offers three levels of user control: (1) At the wave physics level, we adopted the discrete adjoint method in order to use our existing high-performance FWI code; (2) at the rock physics level, we used built-in automatic differentiation operators from the TensorFlow backend; (3) at the flow physics level, we implemented customized partial differential equation (PDE) operators for the multiphase flow equations. The three-level coupled inversion strategy strikes a good balance between computational efficiency and programming efforts, and when the gradients are chained together, it constitutes a coupled inverse system. Our numerical experiments demonstrate that the three-level coupled inverse problem is superior in terms of accuracy to a traditional decoupled inversion strategy. Additionally, our method is able to simultaneously invert for parameters in empirical relationships such as the rock physics models. Our proposed inverted model can be used for reservoir performance prediction and reservoir management/optimization purposes.
Summary Early thermal breakthrough in enhanced geothermal systems (EGS) due to the presence of preferential flow channels is a major challenge that endangers efficient and economic heat extraction in such systems. Previous studies mainly focused on adjusting circulation rates of the working fluid, which still leaves significant amounts of untapped heat behind. Currently, there is a lack of technologies for altering flow distribution within the fracture network to achieve uniform heat sweeping in the reservoir. This work presents a novel concept for making proppants to autonomously control fracture conductivity based on the surrounding temperature. Here, proppants with negative thermal expansion coefficients have demonstrated the capability for appropriate fracture conductivity adjustment as a function of temperature to achieve uniform flow across the fracture network. Particle-particle interactions governing such functions are explicitly modeled, and then the Lattice Boltzmann methods (LBM) is used to determine the potential impact of closure stress and temperature changes on the permeability of the proposed proppant packs. Microscale analyses are further used to determine the required material properties to achieve a certain improvement in the permeability of the proppant pack. Our analyses show an enhancement in permeability and the associated fracture conductivity by half of their initial values. Field-scale analysis further confirms the effectiveness of the proposed concept as 31.4% more heat can be extracted from EGS over 50 years of production when the proposed proppants are used. Such novel proppants may effectively delay thermal breakthrough, sweep heat from larger rock volumes, and elongate the life span of the EGS project.
Newly acquired magnetotelluric data and passive seismic data collected with tightly spaced geophone arrays are combined with historic drilling, active seismic, and potential fields data to generate 3-D permeability maps. A cooperative inversion methodology has been developed using active seismic, magnetotelluric, and gravity data in order to produce more robust velocity models for passive seismic data processing without requiring expensive 3-D active seismic surveys. The cooperative inversion estimates velocities from other geophysical data where no prior seismic velocity information is available at two geothermal sites in Nevada: San Emidio and Crescent Valley.
Background Irritable bowel syndrome (IBS) is one of the most common functional gastrointestinal disorder. Traditionally, early life stress (ELS) is predisposed to IBS in adult. However, whether ELS induces IBS in early life remains unclear. Methods Separated cohort studies were conducted in neonatal male pups of C57BL/6 mice by maternal separation (MS) model. MS and non-separation mice were scheduled to be evaluated for prime IBS-phenotypes, including visceral hypersensitivity, intestinal motility, intestinal permeability, and anxiety-like behavior. Ileal contents and fecal samples were collected and analyzed by 16S rRNA gene sequencing and bacterial community analyses. Subcellular structures of intestinal epithelial, such as epithelial tight junctions and mitochondria, were observed under transmission electron microscopy. Results MS induced visceral hypersensitivity and decreased total intestinal transit time from childhood to adulthood. In addition, MS induced intestinal hyperpermeability and anxiety-like behavior from adolescence to adulthood. Besides, MS affected intestinal microbial composition from childhood to adulthood. Moreover, MS disrupted intestinal mitochondrial structure from childhood to adulthood. Conclusion The study showed for the first time that MS induced IBS from early life to adulthood in mice. The disrupted intestinal mitochondrial structure and the significant dysbiosis of intestinal microbiota in early life may contribute to the initiation and progress of IBS from early life to adulthood.
The Center for Understanding Subsurface Signals and Permeability is a new U.S. Department of Energy Earthshot Center focused on understanding and predicting the long-term evolution of permeability in enhanced geothermal systems. The center will use a highly instrumented testbed within the Sanford Underground Research Facility to conduct field scale experiments that elucidate and test capabilities to simulate geochemical-geomechanical interactions and permeability evolution. Here we demonstrate initial developments using previously collected electrical resistivity tomography (ERT) monitoring data with high-performance multi-physics modelling advancements to inform the optimal location of two new monitoring boreholes. Specifically, ERT monitoring data collected during shear stimulation testing shows marked responses to changes in stress during borehole pressurization. We demonstrate how the same response is being simulated, ultimately to train a machine-learning algorithm to estimate rock properties and enable enhanced prediction of stress and strain responses anticipated during future testing campaigns.
Reactive transport models (RTMs) are essential tools that simulate the coupling of advective, diffusive, and reactive processes in the subsurface, but their complexity makes them difficult to understand, develop and improve without accompanying statistical analyses. Although global sensitivity analysis (SA) can address these issues, the computational cost associated with most global SA techniques limits their use with RTMs. In this study, we apply distance-based generalized sensitivity analysis (DGSA), a novel and computationally efficient method of global SA, to a floodplain-scale RTM and compare DGSA results to those from local SA. Our test case focuses on the impact of 17 uncertain environmental parameters on spatially and temporally variable redox conditions within a floodplain aquifer. The input parameters considered include flow and diffusion rates, geochemical reaction rates, and the spatial distribution of sediment facies. Sensitivity was evaluated for three distinct components of the model response, encompassing both multidimensional and categorical output. Parameter rankings differ between local SA and DGSA, due to nonlinear effects of individual parameters and interaction effects between parameters. DGSA results show that fluid residence time, which is controlled by aquifer permeability, generally exerts a stronger control on redox conditions than do geochemical reaction rates. Sensitivity indices also demonstrate that sulfate reduction is key for establishing and maintaining reducing conditions throughout the aquifer. Furthermore, these results provide insights into the key drivers of heterogeneous redox processes within floodplain aquifers, as well as the main sources of uncertainty when modeling complex subsurface systems.
While induced bank filtration is a proven method for facilitating sustainable drinking water production, it is at risk from surface water contaminations (e.g., pathogens). Induced bank filtration and pathogen transport in groundwater have been studied extensively. However, long-term studies that consider real-world conditions are missing. These conditions include seasonal changes to environmental conditions and waterworks operations. Therefore, to analyze the effect of seasonal changes on the transport of human pathogenic viruses and their indicators in induced bank filtration, concentrations of adenoviruses and pathogen indicators were monitored over 16 months at an active bank filtration plant at the Rhine River, in Düsseldorf (Germany). Based on this data, a 2D groundwater model was created in PFLOTRAN that simulated flow, heat transport, conservative transport of chloride and the resulting electrical conductivity, reactive transport of oxygen and nitrate, and colloid-based transport of coliforms, somatic coliphages, and adenoviruses. The results show that reduced travel time was the key factor determining periods with a low removal of coliforms and somatic coliphages in the aquifer. Travel time was controlled by river level variations during rainy seasons, and the waterworks extraction rates during dry seasons. Further, for adenovirus transport, travel distance in the subsurface appeared to be the key factor, while travel time had no significant impact. Coliform removal increased when the colmation layer permeability decreased, while coliphage and adenovirus removal was unaffected by the colmation layer permeability. Seasonal changes in temperature and oxygen content did not significantly impact the removal of coliphages and adenoviruses in groundwater. Denitrifying conditions correlated with a lowered coliform removal, but the modelling could not establish a connection between denitrifying conditions and coliform removal. Our study showed that removal of pathogens and pathogen indicators at induced bank filtration plants varies greatly in time and space (e.g., for coliforms from 1 to 4 log-levels at 20m travel distance), and that adenovirus transport differs considerably from transport of coliforms and somatic coliphages.
Geological, geophysical, hydrogeological, and hydrological evidence indicates that feeder dikes to rhyolitic lava flows may play a role as confining units in the groundwater flow system underlying the Pahute Mesa (PM) area of underground nuclear testing at the Nevada National Security Site (NNSS) (Figure 1). Of geological significance, the PM testing area is largely situated within the Silent Canyon caldera complex (SCCC), which includes both tuffs and lavas that were fed by (and are connected to) intrusive rock units such as feeder dikes prior to and during volcanic eruptions (Orkild et al., 1968; Byers et al., 1976a). Groundwater modeling results presented in this report support extension of “pool-dam” and “breach scenario” concepts presented in Jackson and Fenelon (2018) and Jackson et al. (2021) to low-permeability intrusive confining units (ICUs) such as feeder dikes that are expected to dissect and ring silicic calderas. As laterally extensive, steeply-dipping, and sub-parallel planar structures, ICUs may further compartmentalize groundwater flow in some areas of the volcanic aquifer system at PM. ICUs may explain unusually high horizontal hydraulic gradient southwest of Cheshire. Breaching of an ICU within which the Cheshire test was emplaced may explain changes in water levels before and after the Cheshire test was detonated in the U-20n emplacement hole on 2/14/76 (USDOE, 2015b). This analysis of the effects of ICUs on groundwater flow at PM addresses a need to evaluate uncertainty in the conceptual model or structural aspects of hydrologic source term (HST) or corrective action unit (CAU) models for groundwater flow and contaminant transport (FFACO, 1996, as amended). At Cheshire and possibly other test locations at PM, downgradient extent of radionuclide contamination may be overpredicted by not including the confining effects of ICUs. On the other hand, contaminant extent may be underpredicted by not considering transient flow effects and/or the re-equilibrated flow field caused by breaching of an ICU by an underground nuclear test. Near Cheshire, the effects of ICUs may be most apparent and impactful to the groundwater flow system at PM because of an unusual combination of thickness, extent, and frequency of dikes transecting the saturated CHLFA4 aquifer and feeding into the overlying unsaturated rhyolite lava of Windy Wash. Chapters 2, 3, and 4 present geological, geophysical, hydrogeological, and hydrological evidence for ICUs at PM. Chapters 5 and 6 examine effects of ICUs on groundwater flow including analysis by groundwater modeling.
Here, to elucidate the impact of local interfaces on mass-transport resistance and overall cell performance of low-loaded proton-exchange-membrane fuel cells (PEMFCs), we present a multiscale modeling framework incorporating a novel modified agglomerate model. The model considers three distinct Pt-electrolyte interfaces: Pt on the carbon surface covered by either ionomer or water film and Pt inside carbon nanopores. Detailed mass-transport voltage-loss breakdowns reveal that coupled agglomerate-interface-scale mass transport dominates the mass-transport loss. The ionomer poisons the exterior-Pt surface through suppressing O 2 adsorption and intrinsic ORR activity, leading to low current-density performance. Conversely, interior-Pt interface enhances the kinetic performance but limits high current-density performance due to its low interfacial permeability. The exterior-Pt/water interface demonstrates superior kinetic performance and mass transport, though its practical implementation requires ensuring proton transport. By coupling the multiscale CL properties with ink parameters, the model identifies an optimal I to C ratio of approximately 0.5, a moderate value where the ionomer content is sufficient to guarantee proton transport without fully covering the Pt surface and forming large agglomeration, thus allowing the utilization of the Pt-water interface and avoiding high mass-transport loss. Overall, the model helps unravel limiting phenomena across different operating regimes and provides routes for optimizing performance.
Several potential CO 2 storage reservoirs have been found to have insufficient porosity and permeability to support cost effective commercial-scale injection. As a result, the use of hydraulic fracturing to enhance injectivity and storage capacity of CO 2 storage reservoirs was explored. Previous modeling studies indicate that fracturing can increase storage capacity by modest to significant amounts (10%–35%), depending on model assumptions. Simulations completed as part of this study confirm that for a range of horizontal well lengths, number of fractures, fracture geometries, and fracture properties, injectivity is improved and capacity increases by 13%–71% over the base case unfractured vertical well. Intuitively, increasing the well length and number of fractures had a corresponding impact on increased capacity. Here, fracture area (i.e., the fracture height multiplied by its width) was an important parameter for increasing capacity but the specific geometry (e.g., the ratio of height-to-width) was unimportant. The most important aspect that affected capacity was the ability of a fracture to connect high permeability horizontal zones in the reservoir. This would allow a single well to access both layers, thereby maximizing total storage capacity of the reservoir while likely leading to an overall increase of the CO 2 footprint, which is an important consideration for Class VI UIC permitting. The results of this work demonstrate that hydraulic fracturing is an attractive option to consider when faced with an underperforming geologic carbon storage site that is at risk of causing a project to fail.
Angstrom-scale proton-selective pores in atomically thin 2D materials present fundamentally new opportunities for advancing proton exchange membranes (PEMs). Vanadium Redox Flow Batteries (VRFBs) for grid-scale energy storage require PEMs with high areal proton conductance (>1 S cm −2 ) and minimal vanadium ion (VO 2+ ) crossover. However, state-of-the-art Nafion 212 membranes (N212 ≈50 µm thick), suffer from persistent VO 2+ crossover reducing performance and efficiency. Here, a layered PEM is demonstrated, comprising monolayer CVD graphene with Angstrom-scale proton-selective pores introduced via Ar plasma, integrated with an ultra-thin ≈300 nm polybenzimidazole (PBI) layer and sandwiched between two Nafion 211 (25 µm thick) layers. The layered architecture facilitates scalable membrane fabrication by mitigating defects while processing and facile stacking of graphene layers allows stochastic non-selective defect isolation enabling exceptionally low VO 2+ crossover (selectivity (H + areal conductance / VO 2+ permeability) ≈6709 × 10 6 S min cm −4 ), with proton conductance >8 S cm −2 . Systematic transport experiments supported by resistance-based transport modelling elucidate the role of defect size, defect isolation, and sealing, as well as layering/stacking, to enable orders of magnitude (>671× over N212) improvements in selectivity, along with areal proton conductance >8 S cm −2 . This work highlights the potential of atomic-scale proton-selective defect engineering in 2D materials, in conjunction with facile stacking and layering of materials as strategies for scalable, high-performance advances in PEMs for energy, electrochemical, and separation applications beyond VRFBs.
A recent article in Science by Culp, Kumar, Gomez, and colleagues introduces a new approach to characterizing reverse osmosis thin film composite membranes to provide critical insights into understanding how polymer membrane microstructure affects water permeability. Such approaches offer a degree of microstructure characterization that has up until now been unavailable to the membrane science community. Here, combined with modeling of water diffusion coefficient in the polymer membrane itself, this effort has begun to answer decades-old questions about how polyamide reverse osmosis membranes function.
Hydrogen production from serpentinization of ultramafic rocks represents a promising natural pathway for generating carbon-free energy, yet its kinetics and controlling factors remain incompletely understood. A key challenge in advancing serpentinization research lies in the heterogeneity of porosity and permeability in rocks, which leads to nonuniform fluid velocity fields, as well as uncertainties in estimating reactive surface area and identifying appropriate mineral reaction equilibria. Additional complexities arise from the role of dissolved SiO 2 , Fe 2+ /Fe 3+ partitioning, and the limited effect of pH variations within the strongly alkaline regime on hydrogen yields. These challenges hinder straightforward extrapolation from laboratory tests to practical applications of hydrogen production from natural rocks. Here, in this work, we address these questions using a simulation-based reactive transport modeling framework calibrated against controlled laboratory experiments reported elsewhere. The model couples geochemical kinetics, multiphase flow, and mineralogical feedbacks, enabling systematic evaluation of how surface area, dissolved silica concentration, Fe redox state, temperature, and pressure govern serpentinization and H2 generation. We find that surface area exerts the strongest control on reaction rates and hydrogen yields, while Fe 2+ /Fe 3+ ratios act as secondary modulators. Elevated dissolved silica concentrations suppress hydrogen production but accelerate serpentine precipitation, whereas increasing pH beyond 12 within the strongly alkaline regime produces only marginal gains. Finally, we demonstrate that integrating targeted experiments with calibrated simulations offers a powerful and efficient approach for predicting hydrogen yields and assessing parameter trade-offs in industrial-scale applications. This integration can substantially reduce the experimental burden while improving predictive capability, thereby enhancing both the mechanistic understanding and the practical feasibility of hydrogen production from serpentinization.