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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Machine Learning for Well Log Analysis in Uranium Mining

This project explores the use of Artificial Intelligence (AI) and Machine Learning (ML) techniques to automate well log analysis for uranium mining. Geophysical log data—spontaneous potential, resistivity, and gamma ray—were used to classify lithology, correlate well logs and identify roll front zonation patterns, which are critical for locating uranium ore bodies. Supervised ML algorithms such as eXtreme Gradient Boosting (XGBoost), Categorical Boosting (CatBoost), and Random Forest were trained to classify lithology with high accuracy. Gradient Boosting Machines (GBM), XGBoost, Random Forest, and Neural Networks were also used for role front zone identification. Moreover, a Fast Dynamic Time Warping (FastDTW) algorithm was employed for well log correlation. Additionally, sample lag was addressed using dynamic programming. Results demonstrate the potential of AI and ML to streamline well log analysis and enhance uranium exploration workflows.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2025

Interplay of superconducting, metallic, and crystalline states of composite fermions at 𝜈 = $\frac{1}{6}$ in wide quantum wells

Evidence for developing fractional quantum Hall effect (FQHE) at filling fraction 𝜈 = 1/6 and 1/8 was recently reported in wide GaAs quantum wells [Wang et al., Phys. Rev. Lett. 134, 046502 (2025)]. In this article, we theoretically investigate the nature of the state at 𝜈 = 1/6 as a function of the quantum well width and the density by considering composite-fermion (CF) crystals, CF Fermi sea, and various kinds of paired CF states. The 𝑓-wave paired state has the lowest energy among the paired CF states. However, for parameters of interest, the energies of the CF crystal, the CF Fermi liquid, and the 𝑓-wave paired CF state are too close to distinguish. We, therefore, predict that 𝑖𝑓 the FQHE at 𝜈 = 1/6 is experimentally confirmed, this state would be an 𝑓-wave paired state of CFs, which can be verified by measurement of its thermal Hall conductance. Exact diagonalization studies on clean systems with up to eight electrons show that the ground states at 𝜈 = 𝑛/(6⁢𝑛 ± 1) are incompressible for all widths and densities we have considered, and are well described by the corresponding Laughlin and Jain states. We propose a phase diagram for large quantum well widths and densities in which at zero disorder, incompressible FQHE states are stabilized at 𝜈 = 𝑛/(6⁢𝑛 ± 1) and 𝜈 = 1/6, but in between these fillings the CF crystal is stabilized. We also present a qualitative discussion on the effects of disorder and propose a schematic phase diagram based on it. With disorder, which creates a spatial variation in the filling factor, two regimes are identified: (i) for small disorder, when the incompressible states percolate at the special fillings, FQHE with quantized Hall plateaus and vanishing longitudinal resistance should occur; and (ii) for larger disorder, when the CF crystal percolates, the longitudinal resistance rises with decreasing temperature but the domains of FQHE liquid produce minima at the special filling factors. Here, experiments are consistent with the latter scenario. We also mention a possible connection of the phase diagram presented here to a puzzling behavior observed for the fractional quantum anomalous Hall effect in pentalayer graphene.

Composite fermions↗
DOE OSTI2024

A Workflow for Characterizing Legacy Wells as Potential Leakage Pathways for Integration to NRAP-Open-IAM

Carbon capture and storage is a crucial component of climate change mitigation strategies, involving the capture of carbon dioxide (CO2) from point sources and its injection into permeable subsurface formation. Many suitable CO2 storage sites coincide with legacy wells since the conditions that kept hydrocarbons in-situ for thousands of years are also ideal for storage of carbon dioxide. To protect underground sources of drinking water (USDW) during greenhouse gas injection, the Environmental Protection Agency (EPA) mandates area of review evaluations. These evaluations ensure that drinking water sources would not be contaminated by injected fluids. They include identification of legacy wellbores, integrity assessments, and implementing any necessary corrective action. Previous assessment approaches of legacy wells include high-level scoring of regional data and well construction and abandonment evaluation. This work describes a novel methodology that evaluates well construction and abandonment, ranks them based on complexity, and performs a risk assessment with NRAP-Open-IAM. A workflow of the methodology is presented, highlighting its capabilities and limitations.

Wise, Jarrett↗
DOE OSTI2024

The Integration and Mapping of an Open-Source National Well Resource to Inform Geologic Carbon Storage Site Selection and Risk Prevention: The CO2-Locate Database

Geologic carbon storage (GCS) offers a way to capture and permanently store CO₂ from fossil fuel operations in underground geologic structures, aiding in the transition to a carbon-neutral energy economy. However, CO₂ injection sites can experience gas leakage through existing wells that penetrate storage reservoirs, making knowledge of well locations and characteristics crucial for permitting, infrastructure reusability, and risk assessment in GCS. Currently, public wellbore data from state, federal, and tribal entities are inconsistent and fragmented, with gaps and redundancies. To address this, the National Energy Technology Laboratory (NETL) developed CO2-Locate, an open-source, geospatial database and online application. CO2-Locate integrates over 50 data sources from federal, state, and tribal entities, creating a standardized national well database. Funded by the Bipartisan Infrastructure Law, the database is publicly available through the Energy Data eXchange (EDX) and viewable via the CO2-Locate web mapping application. This tool allows users to query, filter, and visualize well data to support GCS planning, permitting, and risk assessments. This presentation covers the methods used to create CO2-Locate, including data acquisition, processing, attribute mapping, and integration, much of which is automated for future updates. The web mapping application and its role in GCS site selection will also be discussed.

Tetteh, Daniel A.↗
DOE OSTI2025

Intrabasin Comparison of Produced Fluid From Hydraulically Fractured Wells in the Permian Region

The Permian Basin is the highest producing oil and gas reservoir in the United States. Hydrocarbon extraction methods in this region are often associated with frac hits, or interwell communication events where an established well is affected by the pumping of fracture fluid into a new well. Our previous work revealed a unique geochemical signal indicating the presence of frac hits in the Permian Basin. We returned to this area with the overall goal of expanding our understanding of the microbial and geochemical dynamics common in this region. To do so, we collected produced water from 25 unique sites across the Permian Basin, 10 of which had previously been characterized during an active frac hit with the rest being novel. For each sample, we measured the pH, alkalinity, geochemical composition, microbial load (qPCR), and microbial community composition (16S rRNA sequencing). Permian Basin produced water is characterized by higher sulfate and lower total dissolved solids (TDS) concentrations compared to other regions. Interestingly, wells impacted by frac hits have a geochemical profile that resembles that of fracture fluid, with both lowered sulfate and lowered TDS concentrations compared to unaffected wells in this region. Due to the year-long recovery window between sample collection periods, we anticipate that all of our data will be characterized by the typical high sulfate, low TDS concentrations.

environmental microbiology↗
DOE OSTI2025

Intrabasin Comparison of the Microbiology and Geochemistry of Produced Fluid From Hydraulically Fractured Wells in the Permian Region

The Permian Basin is the highest producing oil reservoir in the United States. Hydrocarbon extraction methods in this region are often associated with frac hits, or interwell communication events where an established well is affected by the pumping of fracture fluid into a new well. Our previous work revealed a geochemical signal indicating the presence of frac hits in the Permian Basin. We returned to this area with the goal of expanding our understanding of subsurface interactions common in this region. To do so, we collected produced water from 25 unique sites across the Permian Basin, 10 of which had previously been characterized during an active frac hit. For each sample, we measured the pH, alkalinity, geochemistry, microbial load, and microbial community composition. Permian Basin produced water is characterized by higher sulfate and lower total dissolved solids (TDS) concentrations compared to other regions. Interestingly, wells impacted by frac hits have a geochemical profile that resembles that of fracture fluid, with both lowered sulfate and lowered TDS concentrations compared to unaffected wells. Due to the year-long recovery window between sample collection periods, we anticipate that all our data will be characterized by the typical high sulfate, low TDS concentrations.

geochemistry↗
DOE OSTI2024

Thermal and Well Flow Performance of Closed-Loop Geothermal in the Wattenberg Area: Preprint

Closed-loop geothermal systems provide an alternative to resource-constrained hydrothermal systems and stimulation-intensive enhanced geothermal systems. In this work, we apply the slender-body theory (SBT) model, to simulate the well flow and heat transfer performance of U-loop well designs drilled in the Wattenberg area of the Denver-Julesburg Basin. Three U-loop well patterns are investigated including a single, double, and multi-lateral design. The subsurface within area is characterized by deep, hot (> 200degreesC) igneous/metamorphic basement rock underlying multiple sedimentary formations. The lateral section(s) of the U-loop lies within a target depth of 6 km where temperatures are estimated to approach 300degreesC. As a base case, conduction-only heat transfer is investigated through simulations with the SBT model within U-loops with open-hole laterals that exchange heat directly with the hot dry rock using water as a working fluid. The utilization of supercritical CO2 as a heat transfer fluid is also considered. For each scenario, the system performance in terms of annual heat production and temperature profile over a 20-year project lifetime are assessed. Also, the levelized costs of heat and electricity (LCOH and LCOE) are determined using a top-down technoeconomic analysis model. The results show that the performance and cost optimized U-loop design is one having an injection-production well spacing of 1,000 meters with ten 50-meter-spaced laterals that traverse a subsurface system with a temperature gradient of 60degreesC/km. By injecting 20 degreesC-water at a rate of 60 kg/s through this loop, an average heat production of 19 MWth can be achieved, resulting in an LCOE and LCOH of $136/MWh and $1.53/GJ, respectively, over a 20-year project life.

closed-loop geothermal↗
DOE OSTI2025

Thermal and Well Flow Performance of Closed-Loop Geothermal in the Wattenberg Area

Closed-loop geothermal systems provide an alternative to resource-constrained hydrothermal systems and stimulation-intensive enhanced geothermal systems. In this work, we apply the slender-body theory (SBT) model, to simulate the well flow and heat transfer performance of U-loop well designs in the Wattenberg area of the Denver-Julesburg Basin. Three U-loop well patterns are investigated, including a single-, double-, and multi-lateral design. The subsurface within the area of interest is characterized by deep, hot (> 200 degrees C) igneous/metamorphic basement rock underlying multiple sedimentary formations. The lateral section(s) of the U-loop lie(s) within a target depth of 6 km, where temperatures are estimated to approach 300 degrees C. As a base case, conduction-only heat transfer is investigated through simulations with the SBT model within U-loops with open-hole laterals that exchange heat directly with the hot, dry rock using water as a working fluid. The utilization of supercritical CO2 as a heat transfer fluid is also considered. For each scenario, the system performance in terms of annual heat production and temperature profile over a 20-year project lifetime are assessed. Also, the levelized costs of heat and electricity (LCOH and LCOE) are determined using a top-down techno-economic analysis model. The results show that the performance- and cost-optimized U-loop design is one having an injection-production well spacing of 1,000 meters with ten 50-meter-spaced laterals that traverse a subsurface system with a temperature gradient of 60 degrees C/km. By injecting 20 degrees C-water at a rate of 60 kg/s through this loop, an average heat production of 19 MWth (i.e., 2.2 MWe net plant output) can be achieved, resulting in an LCOE and LCOH of $136/MWhe and $1.53/GJ, respectively, over a 20-year project life.

closed-loop geothermal↗
DOE OSTI2025

Distributed Fiber Optic Sensing for in-well hydraulic fracture monitoring

This study presents the results from in-well hydraulic fracture monitoring within a horizontal well in an unconventional reservoir utilizing Distributed Fiber Optic Sensing (DFOS). An in-house-developed Brillouin-based Distributed Strain Sensing (DSS) interrogator was deployed to obtain strain measurements, complemented by a commercial Raman-based Distributed Temperature Sensing (DTS) interrogator for temperature measurements and a commercial Rayleigh-based Low-Frequency Distributed Acoustic Sensing (LF-DAS) interrogator for strain-rate measurements. Examined over a ten-day period, the spatio-temporal distribution of temperature-compensated strain obtained from DSS and DTS revealed distinct signatures of the multi-stage hydraulic fracturing process. These signatures were analyzed with respect to fracture width growth and closure, residual strain effects, and fracture conductivity near the wellbore. Fracture widths within the fracture zone were estimated for individual stages. The findings were assessed with LF-DAS measurements for further evaluation. This work integrates DFOS-measured strain, temperature, and strain-rate data for monitoring in-well hydraulic fracturing, with the goal of supporting future studies in interpreting DFOS measurements for improved understanding of hydraulic fracturing in unconventional reservoirs.

58 GEOSCIENCES↗
DOE OSTI2025

Dynamic Life Cycle Assessment for Evaluating the Global Warming Potential of Geothermal Energy Production Using Inactive Oil and Gas Wells for District Heating in Tuttle, Oklahoma

Repurposing abandoned oil and gas infrastructure for geothermal energy production has great potential to reduce greenhouse gas (GHG) emissions. This study quantified the life cycle global warming potential of geothermal energy production using four inactive oil and gas wells repurposed for district heating in Tuttle, Oklahoma. A cradle-to-grave prospective life cycle assessment was performed to compare GHG emissions between the geothermal district heating system and conventional natural gas-fired heating system from 2020 to 2050. For initial implementation of the geothermal system, we investigated two approaches: 1) repurposing abandoned infrastructure from a nearby oil and gas well site, and 2) production and injection well drillings including new construction of a central heat exchange station. Environmental impacts from the geothermal system were estimated for five scenarios where a natural gas peaking boiler is incorporated to supply peak heat demand. The prospective results indicated that cumulative reduction in GHG emissions from transitioning to the geothermal district heating system increase over time as a function of future renewable resource penetration and technological advancements within electricity, fuel, and steel production. Over 30 years, the global warming potential associated with the district heating demand will have been reduced by up to 24 % with the repurposed system. These results imply that repurposing existing oil and gas infrastructure for geothermal energy systems of district heating will bring future climate benefits.

abandoned oil and gas wells↗
DOE OSTI2024

Applying colloidal silica suspensions injection and sequential gelation to block vertical water flow in well annulus: laboratory testing on rheology, gelation, and injection

We evaluated the application of silica suspension injection and sequential gelation to block vertical water flow in the annuli of long-screened wells. First, we studied the viscosity, rheological behavior, and gelation performance of colloidal silica suspensions in batch tests. Then, we tested the injection of silica suspensions and the water flow blocking efficiency of the later formed silica gel in column and bench-scale sandbox experiments. Micron-sized fumed powder silica suspensions and nanosized silica suspensions recovered from geothermal fluids were tested in this work. Fumed silica suspensions showed shear thinning, while nanosized silica suspensions exhibited Newtonian flow behavior. During the gelation process, the nanosized silica suspension changed from a Newtonian fluid to a shear thinning fluid while increasing its overall viscosity. At comparable concentrations, the nanosized silica suspensions have much lower viscosity than that of the fumed silica suspensions. Increases in the Na + concentration and silica particle concentration in these suspensions shortened the gelation time. Silica suspension gelation in sand columns completely blocked the water flow and sustained the injection pressure up to 50 psig (344.7 kPa). A silica suspension was successfully injected into the target zone in the annulus of a bench-scale sandbox mimicking long-screened wells in the field. The silica gel formed in the annulus effectively blocked chemical transport through the gelled zone. Our research reveals that a process using silica suspension injection and sequential gelation technology is promising for blocking the vertical water flow and chemical transport through the filter pack in targeted zones within the annulus of long-screened well systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Utah FORGE: Wells 16A(78)-32 and 16B(78)-32 Stimulation Program Report - May 2024

This dataset consists of a comprehensive report documenting the stimulation program conducted in May 2024 on Utah FORGE wells 16A(78)-32 and 16B(78)-32. It includes detailed accounts of operational and scientific objectives, stimulation methodologies, and testing outcomes. The report describes the hydraulic fracturing activities, equipment setups, proppant and fluid usage, and the execution of a nine-hour circulation test. It also includes observations from seismic and fiber optic monitoring systems, providing data on microseismic activity and fracture propagation. Detailed parameters for each stimulation stage are provided, alongside operational challenges and solutions. The dataset includes analyses of injection and production rates, well temperatures, and pressure data, supported by graphical illustrations and logs.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Utah FORGE: Well 16A(78)-32 Hydraulic Fracturing Stage 8 Crosswell Strain FDI and Microseismic Presentations - April 2024

This is a pair of PowerPoint presentations from Neubrex Energy Services (US), LLC. The presentations review work done in April 2024 on crosswell strain fracture driven interactions (FDI) and microseismic event monitoring during hydraulic fracturing in stage 8 of Utah FORGE well 16A(78)-32. Well 16B(78)-32 was the monitoring well and was where the data for these presentations were collected.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Utah FORGE: RESMAN Well 16A(78)-32 and 16B(78)-32 Stimulation and Circulation Tracer Test Results - 2024

This dataset contains tracer test results from stimulation and circulation experiments conducted on the Utah FORGE wells 16A(78)-32 and 16B(78)-32 during 2024. The data was collected by RESMAN Energy Technology and includes detailed tracer analysis from flowback, short- and extended-duration circulation tests, and reinjection sampling. Sampling included analysis of tracers during different stages of testing in April, August, and September 2024. The dataset is accompanied by an interpretation report and contains time-series tracer concentration data with identification of test phases and sampling conditions. It includes results for flowback from well 16A, commingling effects with water from well 16B, tracer data from short and extended circulation tests, and reinjection tracer corrections for the August/September test. Users should be aware that proprietary tracer methodologies were applied, and they should consult the interpretation report for insights into experimental procedures and data contextualization.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

High conductivity coherently strained quantum well XHEMT heterostructures on AlN substrates with delta doping

Polarization-induced two-dimensional electron gases (2DEGs) in AlN/GaN/AlN quantum well high-electron-mobility transistors on ultrawide bandgap AlN substrates offer a promising route to advance microwave and power electronics with nitride semiconductors. The electron mobility in thin GaN quantum wells embedded in AlN is limited by high internal electric field and the presence of undesired polarization-induced two-dimensional hole gases (2DHGs). To enhance the electron mobility in such heterostructures on AlN, previous efforts have resorted to thick, relaxed GaN channels with dislocations. In this work, we introduce n-type compensation δ-doping in a coherently strained single-crystal (Xtal) AlN/GaN/AlN heterostructure to counter the 2DHG formation at the GaN/AlN interface, and simultaneously lower the internal electric field in the well. This approach yields a δ-doped XHEMT structure with a high 2DEG density of ∼3.2×1013 cm−2 and a room temperature (RT) mobility of ∼855 cm2/Vs, resulting in the lowest RT sheet resistance 226.7 Ω/□ reported to date in coherently strained AlN/GaN/AlN HEMT heterostructures on the AlN platform.

Physics↗
DOE OSTI2024

Deploying a Publicly Available and Living National Oil and Gas Well Geodatabase: CO2-Locate: A Dynamic Database & Tool

Emission mitigation and safe geologic carbon storage require an understanding of local wellbore infrastructure, yet well data are siloed across many entities. Addressing this challenge, the National Energy Technology Laboratory published CO2-Locate, an integrated and dynamic national wellbore geodatabase. CO2-Locate offers up to date well data spanning more than 40 federal, state, and tribal entities, as well as spatially summarized insights designed to support commercial, regulatory, and research communities as they strive to curb climate change through a national energy transition.

Pfander, Isabelle↗
DOE OSTI2024

Well-Log Derived Geomechanical Analysis of Microseismicity in the Mt. Simon Saline Aquifers (Illinois Basin - Decatur Project)

The Illinois Basin Decatur Project (IBDP) successfully demonstrated the safe geologic storage of carbon dioxide at a commercial scale. Within the IBDP project three deep wells (injection (CCS1), monitoring (VW1), geophysical (GM1)) were competed and geophysical logs were recorded. During injection and post-injection periods microseismic monitoring was conducted to create a miscoseismic catalog. The correlations between microseimic attributes and geomechanical well logs define major geomechanical drivers of microseismic expression to understand a reservoir response to CO2 injection in geological context. Utilizing standard sonic and density well logs, the dynamic elastic moduli were calculated and employed to correlate with microseismic pseudo-logs. A multi-dimensional Mu-rho and Lambda-rho (MRLR) hyperdimensional plots display of meaningful data and uncovered subtle relationships between elastic properties of sandstones and the seismological attributes of recorded microseismicity.

Myshakin, Evgeniy↗