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At least 19 records

Permeability Prediction Using Vision Transformers

Accurate permeability predictions remain pivotal for understanding fluid flow in porous media, influencing crucial operations across petroleum engineering, hydrogeology, and related fields. Traditional approaches, while robust, often grapple with the inherent heterogeneity of reservoir rocks. With the advent of deep learning, convolutional neural networks (CNNs) have emerged as potent tools in image-based permeability estimation, capitalizing on micro-CT scans and digital rock imagery. This paper introduces a novel paradigm, employing vision transformers (ViTs)—a recent advancement in computer vision—for this crucial task. ViTs, which segment images into fixed-sized patches and process them through transformer architectures, present a promising alternative to CNNs. We present a methodology for implementing ViTs for permeability prediction, its results on diverse rock samples, and a comparison against conventional CNNs. The prediction results suggest that, with adequate training data, ViTs can match or surpass the predictive accuracy of CNNs, especially in rocks exhibiting significant heterogeneity. This study underscores the potential of ViTs as an innovative tool in permeability prediction, paving the way for further research and integration into mainstream reservoir characterization workflows.

58 GEOSCIENCES

Controlled Enzyme Cargo Loading in Engineered Bacterial Microcompartment Shells

Bacterial microcompartments (BMCs) are nanometer-scale organelles with a protein-based shell that serve to colocalize and encapsulate metabolic enzymes. They may provide a range of benefits to improve pathway catalysis, including substrate channeling and selective permeability. Several groups are working toward using BMC shells as a platform for enhancing engineered metabolic pathways. The microcompartment shell of Haliangium ochraceum (HO) has emerged as a versatile and modular shell system that can be expressed and assembled outside its native host and with non-native cargo. Further, the HO shell has been modified to use the engineered protein conjugation system SpyCatcher–SpyTag for non-native cargo loading. Here, we used a model enzyme, triose phosphate isomerase (Tpi), to study non-native cargo loading into four HO shell variants and begin to understand maximal shell loading levels. We also measured activity of Tpi encapsulated in the HO shell variants and found that activity was determined by the amount of cargo loaded and was not strongly impacted by the predicted permeability of the shell variant to large molecules. All shell variants tested could be used to generate active, Tpi-loaded versions, but the simplest variants assembled most robustly. We propose that the simple variant is the most promising for continued development as a metabolic engineering platform.

59 BASIC BIOLOGICAL SCIENCES

Comparison of dermal and inhalation routes of entry for organic chemicals

The quantitative comparison of the chemical concentration inside the body as the result of a dermal exposure versus an inhalation exposure is useful for assessing human health risks and deciding on an appropriate protective posture. In order to describe the relationship between dermal and inhalation routes of exposure, a variety of organic chemicals were evaluated. The types of chemicals chosen for the study were halogenated hydrocarbons, aromatic compounds, non-polar hydrocarbons and inhalation anesthetics. Both dermal and inhalation exposures were conducted in rats and the chemicals were in the form of vapors. Prior to the dermal exposure, rat fur was closely clipped and during the exposure rats were provided fresh breathing air through latex masks. Blood samples were taken during 4-hour exposures and analyzed for the chemical of interest. A physiologically based pharmacokinetic model was used to predict permeability constants (cm/hr) consistent with the observed blood concentrations of the chemical. The ratio of dermal exposure to inhalation exposure required to achieve the same internal dose of chemical was calculated for each test chemical. The calculated ratio in humans ranged from 18 for styrene to 1180 for isoflurane. This methodology can be used to estimate the dermal exposure required to reach the internal dose achieved by a specific inhalation exposure. Such extrapolation is important since allowable exposure standards are often set for inhalation exposures, but occupational exposures may be dermal.

Jepson, Gary W.

AnisONet: A deep neural operator-based anisotropic permeability upscaler from pore to Darcy scale

Directional permeability variations, which govern directional fluid flow in porous media with anisotropy, are important to accurately predict flow behavior, reactive transport, and fluid–solid interactions for various processes such as enhanced geothermal systems, energy storage devices, and biological systems. However, the intricate architecture of porous media makes it difficult to predict directional permeabilities. In this work, we present a novel machine learning (ML) framework, AnisONet, built upon an integration of a convolutional neural network, Swin transformer, and the deep operator network architecture, designed to predict anisotropic permeability and upscale predictions to larger spatial domains. First, AnisONet was evaluated with three classes of two-dimensional (2D) porous media, including synthetic circular and elliptical grains and natural sandstone grains from micro-computed tomography images. A lattice Boltzmann model (LBM) was used to calculate directional permeabilities at every 10° angle, producing 19 data points per image of porous media. AnisONet is then trained to predict permeability as a function of rotation angle. AnisONet showed strong predictive capability of directional permeability. Second, we tested our model for five upscaling cases with a large image size in the finite-element method (FEM) for 2D Darcy flow with various permeability tensor construction methods. Overall, upscaled permeability tensors in FEM simulations produce a reasonably good match with LBM results, highlighting the importance of selecting appropriate tensor formation strategies for accurate permeability upscaling. AnisONet, as a directional permeability estimator, could be further developed for more complex geometries, with the potential to develop a foundational ML model for various applications in porous media.

42 ENGINEERING

Numerical Modeling, Thermomechanical Testing, and NDE Procedures for Prediction of Microcracking Induced Permeability of Cryogenic Composites

Reusable Space Vehicles will include light cryogenic composite fuel tanks that must not leak excessively even after multiple launches. Damage in cryogenic composite fuel tanks induced during manufacturing and advanced by thermomechanical cycling can accelerate leakage of the propellant. Whether the leakage exceeds tolerable levels depends on many factors, including pressure gradients, microcrack density, other damage such as delamination, connectivity of the cracks, residual stresses from manufacture, service-induced stresses from thermal and mechanical loads, and composite lay-up. Although it is critical to experimentally characterize permeability during various thermal and mechanical load histories, optimal design depends on having analytical models that can predict the effect of various parameters on performance. Our broad goal is to develop such models that are experimentally validated by destructive and non-destructive evaluation means.

Noh, Jae

Fault Slip and Fluid Flow: Seismic Source Analysis to Assess Role of Multiple Slip Patches in Fault Permeability

The relationship between fault reactivation, microearthquakes (MEQs), and permeability evolution during fluid injection plays a critical role in energy harvesting and waste disposal. Recent studies have demonstrated the possibility of predicting fault permeability using cumulative seismic moments of MEQs quantitatively. To understand the underlying physical processes, we conduct fault reactivation experiments using Utah FORGE granitoid and analyze acoustic emission (AE) signals generated during stepwise increases in fluid injection pressure. Frequency analysis of thousands of calibrated AE signals reveals that fault reactivation produces multiple AE source patches with millimeter-scale radii—smaller than the sample fault radius. The cumulative area of the reactivated patches covers the fault multiple times over (∼10x–50x area) for each pressure step. These findings provide mechanistic insight that measured permeability enhancement is not driven by a single large slip event, but by the sequential and interacting activation of multiple slip patches that create a continuous flow pathway.

Nurshal, M. E. M. [Pennsylvania State University,

Facilitating Screening of MOFs for Mixed Matrix Membranes Using Machine Learning and the Maxwell Model

Metal organic framework (MOF)-based mixedmatrix membranes (MMMs), which embed MOF particles in polymer matrices, combine the advantages of polymeric and inorganic membranes. Multiple previous studies have used the Maxwell model together with molecular simulations and machine learning (ML) to predict the performance of MOF/polymer MMMs. However, the assumption of rigid MOF frameworks in molecular simulations limited the accuracy of the data used in the predictions, particularly in predicting molecular diffusivities. We developed a novel workflow integrating ML models with consideration of MOF flexibility to predict the permeability and selectivity of 131,722 MMMs for CO 2 /CH 4 , O 2 /N 2 and He/H 2 separations. The full range of achievable MMM performance within the Maxwell model was analyzed, and several promising MOFs were identified using this workflow. This approach offers an efficient tool for screening any polymer and MOF combination in gas separation applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH

Permeation of protons, potassium ions, and small polar molecules through phospholipid bilayers as a function of membrane thickness

Two mechanisms have been proposed to account for solute permeation of lipid bilayers. Partitioning into the hydrophobic phase of the bilayer, followed by diffusion, is accepted by many for the permeation of water and other small neutral solutes, but transient pores have also been proposed to account for both water and ionic solute permeation. These two mechanisms make distinctively different predictions about the permeability coefficient as a function of bilayer thickness. Whereas the solubility-diffusion mechanism predicts only a modest variation related to bilayer thickness, the pore model predicts an exponential relationship. To test these models, we measured the permeability of phospholipid bilayers to protons, potassium ions, water, urea, and glycerol. Bilayers were prepared as liposomes, and thickness was varied systematically by using unsaturated lipids with chain lengths ranging from 14 to 24 carbon atoms. The permeability coefficient of water and neutral polar solutes displayed a modest dependence on bilayer thickness, with an approximately linear fivefold decrease as the carbon number varied from 14 to 24 atoms. In contrast, the permeability to protons and potassium ions decreased sharply by two orders of magnitude between 14 and 18 carbon atoms, and leveled off, when the chain length was further extended to 24 carbon atoms. The results for water and the neutral permeating solutes are best explained by the solubility-diffusion mechanism. The results for protons and potassium ions in shorter-chain lipids are consistent with the transient pore model, but better fit the theoretical line predicted by the solubility-diffusion model at longer chain lengths.

NASA Program Exobiology

Prediction of Thermal Protection System Material Permeability and Hydraulic Tortuosity Factor Using Direct Simulation Monte Carlo

Carbon preforms used in Thermal Protection System (TPS) materials are 80 to 90% porous, allowing for boundary layer and pyrolysis gases to flow through the porous regions. The bulk material properties such as permeability and hydraulic tortuosity factor affect the transport of the boundary layer gases. The use of Direct Simulation Monte Carlo along with the Klinkenberg permeability formulation allows us to compute the continuum permeability and Knudsen correction factor for flow in the transition regime. In this work, we have computed the permeability for two types of carbon preforms, namely, Morgan Felt and FiberForm, and assessed the effect of orientation on the permeability. Since both the materials are anisotropic, the permeability was found to depend on orientation, wherein, the materials are more permeable in the in-plane orientation than the through-thickness orientation. The through-thickness orientation was also more tortuous compared to the in-plane material orientation. Compared to Morgan Felt, FiberForm is less permeable, in both, through thickness and in-plane directions.

Jambunathan, Revathi

Compressibility and permeability of particulated non-recyclable municipal solid waste

Biofuels from non-recyclable municipal solid waste (NMSW) stand at the forefront of energy sustainability. However, their widespread adoption is hampered by persistent material handling issues stemming from the variability in NMSW material properties. An enhanced understanding of particulated NMSW properties, particularly compressibility and permeability, is essential to address the feedstock handling challenges and optimize the handling equipment. This study measures the compressibility and gas permeability of five streams of NMSW materials (i.e., rigid plastics, cardboard, thin film, paper, and foam) and their mixtures under different stress conditions. The results highlight the significant variability in compressibility and gas permeability among different streams, as well as the impacts of particle sizes. A semi-empirical model capable of predicting the gas permeability of NMSW mixtures is established and validated. Here, the results also highlight that reduced NMSW particle size helps promote consistency in NMSW feedstock’s physical and mechanical properties, which is favored for handling equipment design in waste-to-energy recovery facilities.

09 BIOMASS FUELS

Evaluating the Transport Mechanism for Lignocellulosic Inhibitors in Zymomonas mobilis

The conversion of lignocellulosic biomass to biofuels and bioproducts is limited by small inhibitory molecules generated during the pretreatment process. The diverse compounds within the cell wall hydrolysate including aldehydes, carboxylic acids, phenolics, and alcohols inhibit microbial growth by disrupting microbial membranes. Although Zymomonas mobilis combines high ethanol productivity with hopanoid-rich membranes that confer solvent tolerance, hydrolysate compounds still inhibit microbial growth. One proposed mitigation strategy is to pump these molecules out through active transport processes, reducing direct toxicity. However, if passive permeation rates are high, active transport would create a futile cycle where the exported molecules diffuse back in, creating a net drag on fitness. To investigate this hypothesis, we measure the passive permeation for thirty-three lignocellulose derived compounds using atomistic molecular dynamics simulations with enhanced sampling. Permeability coefficients determined spanned more than eight orders of magnitude driven largely by the balance between hydrophobicity and polarity. Hydrophobic inhibitors such as aromatic acids, aldehydes, and short chain alcohols readily partitioned into the membrane and showed high permeability consistent with rapid passive influx and strong toxicity. Most polar molecules have lower but still appreciable permeation rates, with only the most polar sugars having low permeabilities. By integrating these predictions together with hydrolysate composition information, we find that most of these molecules are so permeable that futile cycles where passive permeation overwhelms efflux is highly likely. These findings provide a predictive framework for strain engineering, highlighting that, for highly permeable inhibitors, reducing extracellular inhibitor concentrations through hydrolysate detoxification, pretreatment optimization, or dilution may be necessary to mitigate futile cycling and improve microbial productivity in industrial biorefineries.

Zymomonas mobilis

Prediction and Analysis of Utah FORGE Injection Activities using a Coupled Thermo-hydro-mechanical and Earthquake (THM+E) Modeling Workflow

A coupled thermo-hydro-mechanical (THM) numerical workflow that is capable of modeling seismic slip is critical for the successful development of enhanced geothermal systems (EGS). By integrating key physical processes, this workflow enables accurate simulation of temperature and pressure diffusions, stress changes, and induced seismicity. As a result, it serves as a vital tool for predicting induced seismicity and optimizing reservoir stimulation strategies. The Utah FORGE (Frontier Observatory for Research in Geothermal Energy) project, located near Milford, Utah, is a U.S. Department of Energy initiative aimed at advancing EGS technology. In April 2024, eight new stimulation stages (Stages 3R-10) were conducted in well 16A (injection well) subsequent to the first series of stimulation (Stages 1-3) performed in April, 2022. To monitor the induced seismicity, geophones were deployed in wells 58-32, 56-32, and 78B-32, while fiber optic cables were also installed in wells 16B, 78-32, and 78B-32 to collect microseismic data and detect frac hits Preliminary analyses of microseismic catalogs and fiber optic data suggest that the stimulated fractures in Stages 3R–6 closely align with that generated during Stage 3, indicating that the new stimulations were likely reactivating the previously stimulated fracture. To better understand the underlying process, a comprehensive modeling approach that can accurately capture thermal, hydrological, mechanical, and seismic responses is essential. In this work, we propose and utilize a coupled thermo-hydro-mechanical and earthquake (THM+E) simulation workflow to numerically investigate the stimulation activities on well 16A. The specific objective is to confirm whether the new stimulation stages (Stages 3R–6) reactivated fractures previously stimulated during Stage 3. For this purpose, we perform THM+E simulations individually for Stages 3, 3R, 4, and 5, incorporating the discrete fracture networks (DFNs) created by the plane-fitting technique based on the microseismic catalogs. The simulation workflow consists of two separate models: a THM model and an earthquake model, coupled in a one-way manner. Detailed descriptions of the workflow are provided in Section 3. Simulation results are presented in terms of injection pressure, permeability evolution, and predicted seismic catalogs, which are then compared with field data for further analyses. This report is structured as follows. In Section 2, we present detailed analyses of the field data and propose the hypothesis that the new stimulation stages (Stages 3R–6) were probably reactivating the previously stimulated fractures in Stage 3. In Section 3, we introduce the coupled THM+E workflow and the problem setup to validate our hypothesis, followed by the simulation results for each stage in Section 4. Meanwhile, discussions are included to analyze the model predictions and their comparison with field data. Lastly, we conclude the report and outline future plans in Section 5.

15 GEOTHERMAL ENERGY

Understanding Fracture Aperture and Permeability Evolution due to Carbonate Mineralization Utilizing 3D Printing

Caprock formations are a crucial part of subsurface-engineered systems. Composed largely of shale, caprocks act as natural barriers that prevent the upward migration of fluids, thereby ensuring the containment of stored substances in subsurface formations. Fractures in these formations are potential leakage pathways for stored fluids. Mineral precipitation reactions in these fractures, particularly calcite, can significantly restrict the fluid permeability, reducing leakage potential. However, predictive capabilities of mineral precipitation in fractures and associated permeability evolution are limited due to a lack of fundamental understanding of such reactions in natural samples, complicated by mineral heterogeneity and the complexity of the fracture structure. In this study, 3D-printed fracture samples are used to understand the impact of carbonate mineralization on fracture aperture and permeability evolution. Samples were printed using a digital light processing (DLP) 3D printer and commercial liquid resin. Calcite precipitation was first tested on printed 2D films before conducting plug flow column experiments aimed to understand fracture permeability changes due to mineral precipitation. Contact angle measurement and Fourier transform infrared (FTIR) spectroscopy on printed 2D films show evidence of a substantial amount of surface energy for calcite nucleation and precipitation. Surface topography analysis of printed fractured surfaces reveals comparable values, highlighting the high replicability of the printed samples. During the column experiments, the permeability reduces exponentially due to a decrease in fracture aperture. Reductions in fracture aperture estimated from effluent concentration and 3D X-ray computed tomography (CT) show comparable results. Moreover, 3D X-ray CT images suggest the impact of local flow velocities on precipitation. The insights gained from this research contribute to a deeper understanding of the permeability evolution due to carbonate mineralization in caprock formations.

3D printing

Modeling of membrane processes for air revitalization and water recovery

Gas-separation and reverse-osmosis membrane models are being developed in conjunction with membrane testing at NASA JSC. The completed gas-separation membrane model extracts effective component permeabilities from multicomponent test data, and predicts the effects of flow configuration, operating conditions, and membrane dimensions on module performance. Variable feed- and permeate-side pressures are considered. The model has been applied to test data for hollow-fiber membrane modules with simulated cabin-air feeds. Results are presented for a membrane designed for air drying applications. Extracted permeabilities are used to predict the effect of operating conditions on water enrichment in the permeate. A first-order reverse-osmosis model has been applied to test data for spiral wound membrane modules with a simulated hygiene water feed. The model estimates an effective local component rejection coefficient under pseudosteady-state conditions. Results are used to define requirements for a detailed reverse-osmosis model.

Lange, Kevin E.

Hydrogen transport in iron and steel

The permeabilities of protium, deuterium, and tritium in foil specimens of Marz grade iron, 4130 steel, Armco iron, HP-9-4-20, and T-1 steels were studied at hydrogen pressures between 0.02 and 0.5 MPa over the temperature range 260-700 K. The permeability was measured by a pressure-rise method, deuterium counting with a detector, and radioactivity counting. Good agreement is found between the measurement techniques used. It is shown that the permeabilities of protium, deuterium, and tritium in iron and T-1 steel at temperatures as low as 260 K are in good agreement with the equation proposed by Gonzalez (1967). However, the permeabilities of HP-9-4-20 and 4130 steel to hydrogen are typically lower than predicted. The isotope effect on hydrogen permeability of HP-9-4-20, 4130 and T-1 steels, and high-purity iron can be estimated by an inverse square root of mass correction.

Louthan, M. R., Jr.

Characterization of Showerhead Performance At Low Pressure

The overall objective of this work is to characterize the flow to rough showerheads by deriving pressure drop versus velocity correlations to at can be then used in reactor scale simulations where the showerhead is approximated as a porous medium. At relatively low Reynolds numbers (less than 1-10 based on the hole length scale) and in the absence of slip flow, Darcy's Law, grad P = mu U/k, can be used to express the relation between the pressure drop and velocity where @mu@ is the fluid viscosity and it is the permeability that can be theoretically predicted as k= e R^2 /8, where e is the porosity. However, at sufficiently small hole diameters and decreased pressures (less than 5 Torr), the Knudsen number based on showerhead tube radius increases, and the flow may be in a transition regime. Different expressions have been proposed to account for this effect in the permeability by expressing k as a function of either pressure or Knudsen number. But at even higher Knudsen numbers, the pressure drop - velocity dependence is non-linear, and Darcy's Law no longer holds such that a permeability cannot be defined. The direct simulation Monte Carlo method is used along side conventional CFD techniques to determine the extent to which the CFD technique is appropriate and helps to derive correlations for the more rarefied cases of interest in these showerhead flows.

Hash, David B.