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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Fracture Description of the HFTS-2 Slant Core, Delaware Basin, West Texas

Previous work in the Midland Basin Hydraulic Fracture Test Site project (HFTS1) has shown the value of core recovered from a stimulated volume in providing information on the geometry and extent of hydraulic fractures. This project (HFTS2) is in the Wolfcamp Formation of the Delaware Basin. A slant core through the stimulated volume was acquired above and below a stimulated well and the results of the fracture description are presented here. Here, nine, 3-inch-diameter whole cores from the slant well were examined for fractures prior to slabbing, together with a CT scan of the core. We used criteria developed during the HFTS1 project to identify hydraulic, natural, drilling-induced and core-handling fractures. Material collected from a few fracture faces was cleaned, sieved, and examined under a microscope to look for proppant. A total of 1261 fractures, including 500 hydraulic fractures, were described in 948 feet of core. Hydraulic fractures are not evenly distributed through the cores; they tend to occur in clusters. Many are remarkably planar, smooth, and featureless, while others have twist hackles, steps, plumose, and kinks. Natural, subvertical fractures, mostly less than 1 mm in width, sealed with blocky calcite, are oriented NE-SW (Set 1) and WNW-ESE (Set 2). Two Set 1 fractures have drusy cement on parted faces and were possibly open prior to drilling. A few subvertical sealed fractures with different orientations are also present. Bed-parallel natural fractures, most having fibrous cement (beef), and some showing top-to-north bed-parallel shear are present. Faults with normal/oblique movement were found in one part of the core. Drilling induced and core-handling breaks were identified in all cores, and were also noted to have reactivated some natural fractures. The results from this work will allow hydraulic fracture distribution relative to the stimulated well to be assessed. The number of fractures is generally greater than the number of perforations, but these can be compared for different stages and perforation clusters. Surface features provide information about the direction of hydraulic fracture propagation and about segmentation and bifurcation that might increase the number of fracture strands. Reactivation of natural fractures, including bedding-parallel fractures, occurs although the mechanism of parting is mostly unknown. The wider HFTS2 project will make use of this fracture description to improve hydraulic fracture modeling (geomechanics and engineering), to help explain pressure depletion and fiber optics observations (reservoir depletion and frac geometry), to help verify indirect fracture diagnostic techniques such as microseismic monitoring (geophysics), and to help calibrate horizontal well image logs.

58 GEOSCIENCES↗
DOE OSTI2025

Connecting In Situ Stress and Wellbore Deviation to Near-Well Fracture Complexity Using Phase-Field Simulations

The interactions among in situ stress, rock fabric, wellbore geometry, natural fractures, and other natural or man-made defects create highly complex fracture trajectories in the near-wellbore region, far more intricate than those in the far-field. These near-wellbore complexities are critical for the Utah FORGE project and Enhanced Geothermal Systems (EGS) in general. Frictional pressure loss in the near-wellbore region during stimulation can significantly influence the growth of far-field fractures, while pressure losses during circulation serve as a major source of energy dissipation. Near-wellbore fracture complexities are often observable through image logs, offering valuable insights into in situ stress characteristics. However, leveraging this information requires a high-fidelity model capable of capturing the interplay among the diverse factors influencing fracture behavior.

58 GEOSCIENCES↗
DOE OSTI2025

Fracture Network Quantification during CO2 Injection

This is the presentation prepared for the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗
DOE OSTI2025

Fracture Network Quantification during CO2 Injection

This is the conference paper accompanying an oral presentation at the ARMA 2025 (59th US Rock Mechanics/Geomechanics Symposium) Conference held in Santa Fe, New Mexico, June 8-11, 2025. Accurate mapping and quantification of these networks are essential to ensure the integrity of CO2 storage reservoirs, understand and reduce potential leakage, and maintain long-term environmental safety. This study presents a novel machine learning-driven approach, integrated with geomechanical analysis, to quantify fracture networks and assess their spatial distribution during CO2 injection. This paper combines microseismic monitoring data with principles of hydraulic diffusivity and geomechanical analysis to characterize reservoir scale fracture network. The novelty of our approach lies in its capacity to assimilate time-dependent pressure data and microseismicity into a cohesive framework, which not only identifies microseismic triggering fronts but also tracks fracture distribution during active injection. Besides, leveraging image log data and analysis our approach also provides another angle of the insights to solidate the fracture networks understanding and geomechanical impacts. Key results from our study include the detection of over 100 distinct fracture clusters across the injection site, with fracture orientations strongly correlated with the prevailing in-situ stress field.

CO2 storage and sequestration↗
DOE OSTI2020

Hyper Parameter Tuning in Neural Optical Image Categorizer for the E-log (NOICE

The Fermilab Accelerator Division Electronic logbook (E-log) is a record of all the activities and events in the Division for the past 10 years and more. The Elog search function is a valuable resource and the institutional memory of the accelerator complex. About 300,000 files are stored in the E-log, of which the vast majority are images attached to entries and comments. The visual information contained in the images is not presently searchable. The goal of team NOICE (Neural Optical Image Categorizer for the E-log) was to design a neural network able to produce label categories for these images for use by searches. The group developed a dataset and trained a convolutional neural network (CNN) with optimized hyperparameter. Final performance metrics are presented.

Njekeu, Terence Franck↗
DOE OSTI2020

(NOICE) Neural Optical Image Categorizer for the E-log

The Fermilab Accelerator Division Electronic logbook (E-log) is a record of all the activities and events in the Division for the past 10 years and more. The E-log search function is a valuable resource and the institutional memory of the accelerator complex. About 300,000 files are stored in the E-log, of which the vast majority are images attached to entries and comments. The visual information contained in the images is not presently searchable. The goal of team NOICE (Neural Optical Image Categorizer for the E-log) was to design a neural network able to produce label categories for these images for use by searches. The group developed a dataset and trained a convolutional neural network (CNN) with optimized hyperparameter

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Utah FORGE: Updated FMI Fracture Log from Well 16A(78)-32

This dataset consists of an Excel spreadsheet detailing the fracture picks from a reinterpretation of the formation micro-imaging (FMI) log from Utah FORGE well 16A(78)-32. The provided information details fracture location, geometry, and type. Also included here is a link to the original raw and processed FMI logs, as well as other data from the 2021 well logging.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Feasibility of source-free DAS logging for next-generation borehole imaging

Characterizing and monitoring geologic formations around a borehole are crucial for energy and environmental applications. However, conventional wireline sonic logging usually cannot be used in high-temperature environments nor is the tool feasible for long-term monitoring. We introduce and evaluate the feasibility of a source-free distributed-acoustic-sensing (DAS) logging method based on borehole DAS ambient noise. Our new logging method provides a next-generation borehole imaging tool. The tool is source free because it uses ever-present ambient noises as sources and does not need a borehole sonic source that cannot be easily re-inserted into a borehole after well completion for time-lapse monitoring. The receivers of our source-free DAS logging tool are fiber optic cables cemented behind casing, enabling logging in harsh, high-temperature environments, and eliminating the receiver repeatability issue of conventional wireline sonic logging for time-lapse monitoring. We analyze a borehole DAS ambient noise dataset to obtain root-mean-squares (RMS) amplitudes and use these amplitudes to infer subsurface elastic properties. We find that the ambient noise RMS amplitudes correlate well with anomalies in conventional logging data. The source-free DAS logging tool can advance our ability to characterize and monitor subsurface geologic formations in an efficient and cost-effective manner, particularly in high-temperature environments such as geothermal reservoirs. Further validation of the source-free DAS logging method using other borehole DAS ambient noise data would enable the new logging tool for wider applications.

58 GEOSCIENCES↗
DOE OSTI2022

Wabash CarbonSAFE. Geologic Analysis of the Potosi Dolomite Reservoir Interval and Potential Confining Units, at the Wabash #1 Well, Vigo Co., Indiana, Subtask 7.2, Technical Report

The Wabash CarbonSAFE project drilled the Wabash #1 stratigraphic test well (ID# 168045) at the Wabash Valley Resources (WVR) IGCC facility in Vigo County, Indiana, to evaluate the feasibility of commercial-scale CO 2 storage near the site. The Mt. Simon Sandstone was the initial target for storage evaluation and was found to have generally poor reservoir qualities in the Wabash #1 well. Focus was then placed on the secondary target, the Potosi Dolomite. For storage and containment evaluation an extensive suite of geophysical logs was collected throughout the borehole, and whole cores were obtained from the Mt. Simon Sandstone, Eau Claire Formation, and Maquoketa Group. The Maquoketa Group is identified as a regionally extensive secondary sealing interval above the Mt. Simon Sandstone and as a primary seal for the Potosi Dolomite storage complex. Due to concerns over potential lost circulation zones in the Potosi Dolomite during drilling, no core samples or Formation Micro Imager (FMI) logs were acquired in the Potosi Dolomite. However, cased hole well testing was performed over a 20 feet (6 m) interval within the Potosi Dolomite during which a fluid swab sample was obtained. Approximately 35 miles of 2D seismic information was acquired in the project area near Wabash #1 to aid in reservoir and caprock characterization. The highly porous and permeable zones in the Potosi Dolomite and lower Oneota Dolomite observed within the Wabash #1 well are, for the purpose of this report, considered the same reservoir package and referred to as the Potosi reservoir interval. This report presents a regional depositional context for the Potosi reservoir interval, the overlying confining zones in the Knox Group, and Maquoketa Group primary seal. This context is developed through detailed information obtained from the Wabash #1 well such as lithologic data collected from cuttings and core, geophysical logging, geomechanical analysis of core samples, and well testing and fluid sampling within the Potosi reservoir interval. Information discussed in this report was compiled as a basis for the development of static and dynamic geologic models of the Potosi Dolomite storage complex. The static and dynamic modeling of CO 2 injection in the Potosi reservoir interval are discussed in a separate report (Dessenberger et al., 2022) under the Wabash CarbonSAFE project.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

Expedition UT-GOM2-2 Methods

Methods used during the University of Texas (UT) Deepwater Hydrate Coring Expedition (UT-GOM2-2) include work done onboard the Helix Q4000 in the offshore Gulf of America (Gulf of Mexico), herein “the Gulf”, “dockside” in Salt Lake City, Utah, and some shore-based work in individual laboratories. The goal of this report is two-fold: to provide enough detail on the methods so they can be repeated by others; and to provide a reference document for the team to enhance cross-disciplinary understanding and knowledge. Methods include drilling operations, depth references and depth modification, downhole tool deployment, coring tool performance assessment, core processing, lithostratigraphy, biostratigraphy, as well as physical properties, including core logging and imaging, rock magnetism, dissolved methane concentration, hydrate saturation, microbiology, and geochemistry. An extensive amount of operational work and planning was required before mobilization of the expedition to permit, build mobile labs, and test downhole tools for deepwater drilling.

03 NATURAL GAS↗
DOE OSTI2020

Integration of Soft Data Into Geostatistical Simulation of Categorical Variables

Uncertain or indirect “soft” data, such as geologic interpretation, driller’s logs, geophysical logs or imaging, offer potential constraints or “soft conditioning” to stochastic models of discrete categorical subsurface variables in hydrogeology such as hydrofacies. Previous bivariate geostatistical simulation algorithms have not fully addressed the impact of data uncertainty in formulation of the (co) kriging equations and the objective function in simulated annealing (or quenching). This paper introduces the geostatistical simulation code tsim-s, which accounts for categorical data uncertainty through a data “hardness” parameter. In generating geostatistical realizations with tsim-s, the uncertainty inherent to soft conditioning is factored into both 1) the data declustering and spatial correlation functions in cokriging and 2) the acceptance probability for change of category in simulated quenching. The degree or sensitivity to which soft data conditions a realization as a function of hardness can be quantified by mapping category probabilities derived from multiple realizations. In addition to point or borehole data, arrays of data (e.g., as derived from a depth-dependency function, probability map, or “prior realization”) can be used as soft conditioning. The tsim-s algorithm provides a theoretically sound and general framework for integrating datasets of variable location, resolution, and uncertainty into geostatistical simulation of categorical variables. A practical example shows how tsim-s is capable of generating a large-scale three-dimensional simulation including curvilinear features.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

EGS Reservoir Modeling for Developing Geothermal District Heating at Cornell University: Preprint

Cornell University is pursuing development of an enhanced geothermal system (EGS) for providing heating to its main campus in Upstate New York. A ~10,000 ft (~3 km) deep vertical observation well ("CUBO") was drilled in 2022 to characterize the subsurface using wellbore logging, borehole imaging, fluid sampling, mini-frac tests, coring and drill cutting analysis. Down-hole temperatures measured at 3 km depth are about 80 degrees C, sufficiently high for direct-use heating. The well drilled through generally low porosity and low permeability Paleozoic sedimentary formations and into metamorphic basement rock, encountered at about 9,400 ft depth. Leveraging subsurface data obtained through CUBO, we investigated technical feasibility and design requirements of a doublet well system with horizontal laterals connected to a fracture network created through hydraulic fracturing. The EGS reservoir is sized to provide a nominal heat output in the range 5 to 10 MWth of continuous heating over a 15 year-lifetime with limited thermal drawdown. We applied the Gringarten Multiple parallel fracture model, the Cornell Discrete Fracture Simulator FOXFEM and the commercial simulator ResFrac to estimate required heat transfer area and design a potential hydraulic stimulation treatment. Reservoir simulations indicate that, depending on fluid flow rate and injection temperature, 2 to 3 km2 of effective fracture heat transfer area is required to supply the target heat output of 5 to 10 MWth over 15 years.

district heating↗
DOE OSTI2025

EGS Reservoir Modeling for Developing Geothermal District Heating at Cornell University

Cornell University is pursuing development of an enhanced geothermal system (EGS) for providing heating to its main campus in Upstate New York. A ~10,000 ft (~3 km) deep vertical observation well ('CUBO') was drilled in 2022 to characterize the subsurface using wellbore logging, borehole imaging, fluid sampling, mini-frac tests, coring and drill cutting analysis. Down-hole temperatures measured at 3 km depth are about 80 degrees C, sufficiently high for direct-use heating. The well drilled through generally low porosity and low permeability Paleozoic sedimentary formations and into metamorphic basement rock, encountered at about 9,400 ft depth. Leveraging subsurface data obtained through CUBO, we investigated technical feasibility and design requirements of a doublet well system with horizontal laterals connected to a fracture network created through hydraulic fracturing. The EGS reservoir is sized to provide a nominal heat output in the range 5 to 10 MWth of continuous heating over a 15 year-lifetime with limited thermal drawdown. We applied the Gringarten Multiple parallel fracture model, the Cornell Discrete Fracture Simulator FOXFEM and the commercial simulator ResFrac to estimate required heat transfer area and design a potential hydraulic stimulation treatment. Reservoir simulations indicate that, depending on fluid flow rate and injection temperature, 2 to 3 km2 of effective fracture heat transfer area is required to supply the target heat output of 5 to 10 MWth over 15 years.

district heating↗
DOE OSTI2021

Significant H i and Metal Differences around the z = 0.83 Lens Galaxy toward the Doubly Lensed Quasar SBS 0909+532

We report a large difference in neutral hydrogen (H i) and metal column densities between the two sight lines probing opposite sides of the lensing galaxy at z {sub lens} = 0.83 toward the doubly lensed quasar SBS 0909+532. Using archival HST-STIS and Keck HIRES spectra of the lensed quasar images, we measure log N {sub H I} = 18.77 ± 0.12 cm{sup −2} toward the brighter image (A) at an impact parameter of r {sub A} = 3.15 kpc and log N {sub H I} = 20.38 ± 0.20 cm{sup −2} toward the fainter image (B) at an impact parameter of r {sub B} = 5.74 kpc. This difference by a factor of ∼41 is the highest difference between sight lines for a lens galaxy in which H i has been measured, suggesting patchiness and/or anisotropy on these scales. We estimate an average Fe abundance gradient between the sight lines to be ≥+0.35 dex kpc{sup −1}. The N {sub Fe II}/N {sub Mg II} ratios for the individual components detected in the Keck HIRES spectra have supersolar values for all components in sight line A and for 11 out of 18 components in sight line B, suggesting that Type Ia supernovae may have contributed to the chemical enrichment of the galaxy’s environment. Additionally, these observations provide complementary information to detections of cold gas in early-type galaxies and the tension between these and some models of cloud survival.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Deep Ensemble Confidence Levels for Multi-hot Categorization

NOICE (Neural Optical Image Categorizer for the Elog) is a small collaboration tasked with categorizing the images in the Fermilab Accelerator Division electronic logbook by using Artificial Intelligence. To do so, we manually categorized a subset of the images in the E-log into nine independent labels. Each image was then multi-hot-encoded into a nine-dimensional binary vector because each image could have more then one label.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

Training Restricted Boltzmann Machines With a D-Wave Quantum Annealer

Restricted Boltzmann Machine (RBM) is an energy-based, undirected graphical model. It is commonly used for unsupervised and supervised machine learning. Typically, RBM is trained using contrastive divergence (CD). However, training with CD is slow and does not estimate the exact gradient of the log-likelihood cost function. In this work, the model expectation of gradient learning for RBM has been calculated using a quantum annealer (D-Wave 2000Q), where obtaining samples is faster than Markov chain Monte Carlo (MCMC) used in CD. Training and classification results of RBM trained using quantum annealing are compared with the CD-based method. The performance of the two approaches is compared with respect to the classification accuracies, image reconstruction, and log-likelihood results. The classification accuracy results indicate comparable performances of the two methods. Image reconstruction and log-likelihood results show improved performance of the CD-based method. It is shown that the samples obtained from quantum annealer can be used to train an RBM on a 64-bit “bars and stripes” dataset with classification performance similar to an RBM trained with CD. Though training based on CD showed improved learning performance, training using a quantum annealer could be useful as it eliminates computationally expensive MCMC steps of CD.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Site Characterization of the Highest-Priority Geologic Formations for CO2 Storage in Wyoming

The project Site Characterization of the Highest-Priority Geologic Formations for CO2 Storage in Wyoming is one of 9 site characterization projects that were implemented as part of ARRA (American Recovery and Reinvestment Act). Data from this project was used to improve resolution of data in NATCARB in the area of study. Data related to this study has already been incorporated in NATCARB Atlas. The Wyoming Carbon Underground Storage Project (WY-CUSP) consisted of CO2 storage site characterization and evaluation, focusing on Wyoming’s most promising CO2 storage reservoirs (the Pennsylvanian Weber/Tensleep Sandstone and Mississippian Madison Limestone) and premier CO2 storage site (Rock Springs Uplift). Results from the WY-CUSP project suggest the two reservoirs could store up to 17,000 million tons of CO2. The WY-CUSP team drilled a stratigraphic test well and acquired a 3-D seismic survey covering 25 square miles of the Rock Springs Uplift site. The team retrieved 916 feet of core from the 12,810-foot-deep well, along with a complete log suite, borehole images, fluid samples, and other data. Project partners (1) provided continuous visual documentation of the core, including grain size, mineralogy, facies distribution, and porosity; (2) performed continuous permeability and velocity scans of selected reservoir intervals; and (3) chemically analyzed the fluid samples. WY-CUSP scientists integrated seismic attributes with observations from log suites, a VSP survey, core, fluid samples, and laboratory analyses, including continuous permeability scans. From these integrations, researchers constructed 3-D spatial distribution volumes of reservoir and seal properties that represent geological heterogeneity at the targeted CO2 storage site. The WY-CUSP team used this data to perform new CO2 plume migration simulations. Baker Hughes, Inc., completed a series of small-scale, in-situ water injectivity measurements. A database was formed when observations, analyses, and experiments from the stratigraphic test well were integrated. Correlation of these data allowed petrophysical parameters to be extrapolated from the test well out into the storage domain (5x5 mile 3-D seismic survey volume). This resulted in an improved, realistic understanding of performance assessments for potential CO2 storage scenarios. The WY-CUSP team worked on (1) improving CO2 storage resource estimates, (2) establishing long-term integrity and permanence of confining layers, (3) designing a profitable strategy for pressure management, and (4) evaluating the utilization of stored CO2 at the Rock Spring Uplift. Finally, Baker Hughes developed a microseismic baseline for the test site using in-bore geophones to complete field operations.

3-D seismic↗
DOE OSTI2020

Hexagonal boron nitride: Epitaxial growth and device applications

As a newest family member of the III-nitrides, BN is considered amongst the remaining frontiers in wide energy bandgap semiconductors with potentials for technologically significant applications in deep UV (DUV) optoelectronics, solid-state neutron detectors, electron emitters, single photon emitters, switching/memory devices, and super-capacitors. It was shown that it is possible to produce h-BN epilayers with high hexagonal phase purity, UV transparency, and film stoichiometry by employing nitrogen-rich growth conditions. The quasi-2D nature of h-BN supports unusually strong optical transitions near the band edge and a large exciton binding energy on the order of 0.7 eV. Since the isotope of B-10 has a large capture cross-section for thermal neutrons, h-BN is an ideal material for the fabrication of solid-state neutron detectors for special nuclear materials detection, well and geothermal logging, and medical imaging applications. Freestanding B-10 enriched h-BN (h- 10 BN) epilayers with varying thicknesses up to 200 μm have been successfully synthesized by metal organic chemical vapor deposition (MOCVD) as of this writing. By utilizing the conductivity anisotropy nature of h-BN, 1 cm 2 lateral detectors fabricated from 100 μm thick h-10BN epilayers have demonstrated a detection efficiency of 59% for thermal neutrons, which is the highest on record among all solid-state neutron detectors as of today. It was noted that high growth temperatures, long growth times and the use of sapphire substrate tend to incorporate oxygen related impurities into h- 10 BN epilayers, which strongly impacted the carrier mobility-lifetime (μτ) products and charge collection efficiencies of h- 10 BN neutron detectors. As the h-BN material technology further develops, improved carrier mobilities and μτ products will allow the fabrication of h-BN devices with enhanced performance.

42 ENGINEERING↗