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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Coupled Hydromechanical Modeling of Induced Seismicity From CO 2 Injection in the Illinois Basin

Injection of CO 2 for geologic carbon sequestration into deep sedimentary formations involves fluid pressure increases that engage hydromechanical processes that can cause seismicity by activation of existing faults. In this work, we use a coupled multiphase fluid flow and geomechanical simulator to model spatiotemporal fluid pressure and stress changes in order to study the poroelastic effect of CO 2 injection on faults in crystalline basement rock below the injection zone. The seismicity rate along features interpreted to be basement faults is modeled using Dieterich's rate-and-state earthquake nucleation model. The methodology is applied to microseismicity detected during CO 2 injection into the Mount Simon formation during the Illinois Basin—Decatur Project. The modeling accurately captures an observed reduction in seismicity rate when the injection in the second well was into a slightly shallower zone above the base of the Mount Simon formation. Moreover, the modeling shows that it is important to consider poroelastic stress changes, in addition to fluid pressure changes for accurately modeling of the observed seismicity rate.

58 GEOSCIENCES↗
DOE OSTI2025

Seasonality and Albedo Dependence of Cloud Radiative Forcing in the Upper Colorado River Basin

Mountains create and enhance their own clouds, which both scatter and absorb shortwave radiation from the sun and absorb and re-emit land surface and atmospheric longwave radiation. However, the impacts of clouds on the surface radiation balance in high elevation snowy mountain terrain are poorly explored. In this study, we use data collected by the SAIL field campaign and partner organizations in the upper elevations (2,880 m.a.s.l) of the Upper Colorado River Basin (UCRB) over a 21-month period from September 2021 to June 2023 to estimate Cloud Radiative Forcing (CRF) in the shortwave, longwave, and the net effect. Longwave warming effects dominate during the winter when snow albedos are high (0.8–0.9) and the background atmospheric precipitable water vapor is low (<0.5 cm), yielding a maximum monthly average net CRF of +34.7 W·m -2 , meaning that clouds increase the net radiation relative to clear skies during this time period. The sign of net CRF switches in the warm season as snow recedes, sun-angles increase, and the North American monsoon arrives, yielding a minimum monthly average net CRF of -47.6 W·m -2 with hourly minima of -600 W·m -2 . The sign of net CRF is typically positive, even at solar noon, when the surface is snow covered, except for a brief period over melting, low-albedo snow (0.5–0.6) impacted by dust impurities. Sensitivity tests elucidate the role of the surface albedo on the net CRF. The results suggest that net CRF will increase in magnitude and lead to a more persistent cooling effect on the surface net radiation budget as the snow cover declines.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Community structure – Ecosystem function relationships in the Congo Basin methane cycle depend on the physiological scale of function

Belowground ecosystem processes can be highly variable and difficult to predict using microbial community data. Here, we argue that this stems from at least three issues: (a) complex covariance structure of samples (with environmental conditions or spatial proximity) can make distinguishing biotic drivers a challenge; (b) communities can control ecosystem processes through multiple mechanisms, making the identification of these controls a challenge; and (c) ecosystem function assessments can be broad in physiological scale, encapsulating multiple processes with unique microbially mediated controls. In this work, we test these assertions using methane (CH 4 )-cycling processes in soil samples collected along a wetland-to-upland habitat gradient in the Congo Basin. We perform our measurements of function under controlled laboratory conditions and statistically control for environmental covariates to aid in identifying biotic drivers. We divide measurements of microbial communities into four attributes (abundance, activity, composition, and diversity) that represent different forms of community control. Lastly, our process measurements differ in physiological scale, including broader processes (gross methanogenesis and methanotrophy) that involve more mediating groups, to finer processes (hydrogenotrophic methanogenesis and high-affinity CH 4 oxidation) with fewer mediating groups. We observed that finer scale processes can be more readily predicted from microbial community structure than broader scale processes. In addition, the nature of those relationships differed, with broad processes limited by abundance while fine-scale processes were associated with diversity and composition. These findings demonstrate the importance of carefully defining the physiological scale of ecosystem function and performing community measurements that represent the range of possible controls on ecosystem processes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

INGENIOUS - Great Basin Regional Dataset Compilation

This is the regional dataset compilation for the INnovative Geothermal Exploration through Novel Investigations Of Undiscovered Systems (INGENIOUS) project. The primary goal of this project is to accelerate discoveries of new, commercially viable hidden geothermal systems while reducing the exploration and development risks for all geothermal resources. These datasets will be used in INGENIOUS as input features for predicting geothermal favorability throughout the Great Basin study area. Datasets consist of shapefiles, geotiffs, tabular spreadsheets, and metadata that describe: 2-meter temperature probe surveys, quaternary faults and volcanic features, geodetic shear and dilation models, heat flow, magnetotellurics (conductance), magnetics, gravity, paleogeothermal features (such as sinter and tufa deposits), seismicity, spring and well temperatures, spring and well aqueous geochemistry analyses, thermal conductivity, and fault slip and dilation tendency. For additional project information, see the INGENIOUS project site linked in the submission. Terms of use: These datasets are provided "as is", and the contributors assume no responsibility for any errors or omissions. The user assumes the entire risk associated with their use of these data and bears all responsibility in determining whether these data are fit for their intended use. These datasets may be redistributed with attribution (see citation information below). Please refer to the license information on this page for full licensing terms and conditions.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Historical and Future Extreme Event Indices for the Colorado River Basin

Extremes events are occurring more frequently and are projected to increase in the future. This data set includes extreme event indices that were generated for the Colorado River basin using data from the Variable Infiltration Capacity hydrologic model. VIC simulations were run using six CMIP5 earth system models (ESMs), two different time periods, (historical, 1970-1999) and future (2070-2099), and for one Representative Concentration Pathway (RCP 8.5). ESMs available are MPI-ESM-LR, MIROC-ESM, IPSL-CM5A-LR, GFDL-ESM2M, and GFDL-ESM2G. The different indicators include temperature (min/max, freezing days, heating days), precipitation (dry days, max), runoff (min, max), soil moisture (min, max), evapotranspiration (max), snow water equivalent (SWE, max), wind speeds (max), and pressure (min). Detailed information on the indicators, file names, and how they were calculated is included in the README.txt document. Data sets were used to calculate results are in related references Bennett et al. 2020 and Talsma et al. 2021. Details on the VIC model configuration is described in related references Bennett et al. 2018 and Bennett et al. 2017.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

CORECM Williston Basin Twin Butte and Hagel Coal Wells

Computed tomography and core logger data described in Technical Report "Computed Tomography Scanning and Petrophysical Measurements of Eastern Williston Basin Twin Buttes and Hagel Formations" by Paronish et al., 2024

Coal↗
DOE OSTI2024

Characterization for CO2 Storage from Coal-fired Power Facilities in the Black Warrior Basin of Alabama

The project Characterization for CO2 Storage from Coal-fired Power Facilities in the Black Warrior Basin of Alabama 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.

.las↗
DOE OSTI2022

Geochronology of Cambrian Sedimentary and Volcanic Rocks in the Illinois Basin: Defining the Illinois Aulacogen

The Wabash #1 well, drilled for the Wabash CarbonSAFE Project and located in Vigo County, Indiana, USA, was drilled in early 2020 as a stratigraphic test well to characterize and evaluate the basal Cambrian Mt. Simon Sandstone for carbon dioxide storage (TD=8750 ft; 2667 m). The Wabash #1 well is located along the eastern flank of a newly interpreted Cambrian aulacogen that occurs in western Indiana and eastern Illinois. Here we present 938 new detrital zircon U-Pb ages (LA-ICPMS) from early Cambrian sandstones sampled near the base of the well. A basalt lava flow was penetrated at ~8530 ft (2600 m) and has an 40 Ar/ 39 Ar age of 525.03 +/- 1.10 Ma, which represents the first known Cambrian crust in the Illinois Basin. The two sandstone samples from beneath the basalt are dominated by zircons derived from the Midcontinent Granite-Rhyolite terrane. The sandstone samples from above the basalt reflect a mixture of these locally derived Mazatzal and Granite-Rhyolite terrane zircons, but also distal Archean, Grenville, and Yavapai zircons. Each sample has small numbers of Cambrian zircons, which is consistent with those in basal Cambrian sandstones in other deep wells to the west. These early Cambrian detrital zircons and early Cambrian age of the basalt, combined with sediment thickness patterns permit the interpretation of the Illinois aulacogen, which formed during the final stage of Rodinian rifting.

58 GEOSCIENCES↗
DOE OSTI2026

Illinois Basin Regional DAC Hub TA-1: Feasibility (Phase-0) (Final Scientific/Technical Report)

The overall objective of this project was to complete a feasibility study for a Regional Direct Air Capture (DAC) Hub that encompasses Illinois, Indiana, and Kentucky. The geographic construct of this hub was based on the Illinois Basin – a geological area where at least seven (7) geological storage studies were conducted. The Hub was designed to assure a capacity to capture, store, and utilize at least 1,000,000 metric tons (tonnes) of CO2 from the atmosphere annually 1 metric tonnes per annum (MTA), starting from an initial capacity of 200,000 tonnes of CO2 per annum (KTA). The Hub also included:(1) clean energy providers to supply renewable energy to the DAC units; (2) geological storage facilities to inject and sequestrate the captured CO2; (3) CO2 utilization facilities that would uptake the captured CO2 and convert it into products; and (4) small business organizations that would assist in workforce development efforts for the region. This closeout report consolidates the tasks undertaken and accomplished as deliverables for the project. The project team had successfully completed all required tasks of phase 0a, confirming that the project is feasible based on the preliminary conceptual designs and operational requirements of the DAC systems. Of particular interest, the hub ownership structure was identified and was implemented in follow on projects that would transition the hub infrastructure to a build/operate phase.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Subsurface H 2 Storage: A Williston Basin Commercial-Scale Resource Study

Poster for the 2024 NETL Resource Sustainability Project Review Meeting, Pittsburgh, Pennsylvania, April 2-4, 2024. This poster presents a commercial‑scale assessment of subsurface hydrogen storage potential in the North Dakota portion of the Williston Basin, evaluating saline formations, depleted oil and gas reservoirs, and salt formations. The study integrates laboratory characterization, reservoir simulation, and basinwide analysis to assess storage capacity, injectivity, recovery, and risks related to geochemical, microbial, and wellbore interactions. Results support the feasibility of large‑volume, secure hydrogen storage and provide a framework to guide future hydrogen commercialization and infrastructure development.

08 HYDROGEN↗
DOE OSTI2021

Chemically Enabled CO 2 -Enhanced Oil Recovery in Multi-Porosity, Hydrothermally Altered Carbonates in the Southern Michigan Basin - Task 2 Topical Report

This attachment A is a detailed Topical Report for Task 2 (Advanced Field Characterization and Machine Learning Based Data Integration) under the project "Chemically Enabled CO 2 -Enhanced Oil Recovery in Multi-Porosity, Hydrothermally Altered Carbonates in the Southern Michigan Basin." The overall project activity and finding, including the field pilot testing of CO 2 injection are summarized in the companion Final Technical Report The Advanced Field Characterization and Machine Learning Based Data Integration task (Task 2) involved a systematic geologic characterization of the Trenton-Black River (TBR) play in the SMB which included the development of comprehensive datasets, advanced data analytics, risk assessment, and piggyback field characterization. These activities aimed to address the complex carbonate systems by evaluating the extent of fractures, dolomitization, facies, and reservoir properties with the primary objective of informing the static and dynamic modeling, field injection test, and providing input into the development strategy plan. The task was divided into four subtasks: • Subtask 2.1 – Data compilation, review, and analysis • Subtask 2.2 – Risk Assessment • Subtask 2.3 – Advanced Field Characterization • Subtask 2.4 – Integrated Physics-Based Machine Learning and Advanced Data Analytics

02 PETROLEUM↗
DOE OSTI2024

Metagenome-assembled genomes provide insight into the metabolic potential during early production of Hydraulic Fracturing Test Site 2 in the Delaware Basin

Demand for natural gas continues to climb in the United States, having reached a record monthly high of 104.9 billion cubic feet per day (Bcf/d) in November 2023. Hydraulic fracturing, a technique used to extract natural gas and oil from deep underground reservoirs, involves injecting large volumes of fluid, proppant, and chemical additives into shale units. This is followed by a “shut-in” period, during which the fracture fluid remains pressurized in the well for several weeks. The microbial processes that occur within the reservoir during this shut-in period are not well understood; yet, these reactions may significantly impact the structural integrity and overall recovery of oil and gas from the well. To shed light on this critical phase, we conducted an analysis of both pre-shut-in material alongside production fluid collected throughout the initial production phase at the Hydraulic Fracturing Test Site 2 (HFTS 2) located in the prolific Wolfcamp formation within the Permian Delaware Basin of west Texas, USA. Specifically, we aimed to assess the microbial ecology and functional potential of the microbial community during this crucial time frame. Prior analysis of 16S rRNA sequencing data through the first 35 days of production revealed a strong selection for a Clostridia species corresponding to a significant decrease in microbial diversity. Here, we performed a metagenomic analysis of produced water sampled on Day 33 of production. This analysis yielded three high-quality metagenome-assembled genomes (MAGs), one of which was a Clostridia draft genome closely related to the recently classified Petromonas tenebris. This draft genome likely represents the dominant Clostridia species observed in our 16S rRNA profile. Annotation of the MAGs revealed the presence of genes involved in critical metabolic processes, including thiosulfate reduction, mixed acid fermentation, and biofilm formation. These findings suggest that this microbial community has the potential to contribute to well souring, biocorrosion, and biofouling within the reservoir. Our research provides unique insights into the early stages of production in one of the most prolific unconventional plays in the United States, with important implications for well management and energy recovery.

natural gas↗
DOE OSTI2022

Integration of Electromagnetic Geophysics Forward Simulation in Coupled Flow and Geomechanics for Monitoring a Gas Hydrate Deposit Located in the Ulleung Basin, East Sea, Korea

We investigate the feasibility of electromagnetic (EM) geophysics methods to detect the dissociation of gas hydrate specifically from a gas hydrate deposit located in the Ulleung Basin, East Sea, Korea via an integrated flow-geomechanics-EM geophysics simulation. To this end, coupled flow and geomechanics simulation is first performed with the multiple porosity model employed, where a mixed formulation with the finite volume (FV) and finite element (FE) methods are taken for the flow and geomechanics, respectively. From the saturation and porosity fields obtained from the coupled flow and geomechanics, the electrical conductivity model is established for the EM simulation. Solving the partial differential equation of electrical diffusion which is linearized using the 3D finite element method (FEM), the EM fields are then computed. For numerical experiments, particularly two approaches in the configuration for the EM methods are compared in this contribution: the surface-to-surface and the surface-to-borehole methods. When the surface-to-surface EM method is employed, the EM is found to be less sensitive, implying low detectability. Especially for the short term of production, the low detectability is attributed to the similarity of electrical resistivity between the dissociated gas (CH4) and hydrate as well as the specific dissociation pattern within the intercalated composites of the field. On the other hand, when the surface-to-borehole EM method is employed, its sensitivity to capture the produced gas flow is improved, confirming its detectability in monitoring gas flow. Hence, the EM geophysics simulation integrated with coupled flow and geomechanics can be a potential tool for monitoring gas hydrate deposits.

depressurization↗
DOE OSTI2023

Structuring Nutrient Yields throughout Mississippi/Atchafalaya River Basin Using Machine Learning Approaches

To minimize the eutrophication pressure along the Gulf of Mexico or reduce the size of the hypoxic zone in the Gulf of Mexico, it is important to understand the underlying temporal and spatial variations and correlations in excess nutrient loads, which are strongly associated with the formation of hypoxia. This study’s objective was to reveal and visualize structures in high-dimensional datasets of nutrient yield distributions throughout the Mississippi/Atchafalaya River Basin (MARB). For this purpose, the annual mean nutrient concentrations were collected from thirty-three US Geological Survey (USGS) water stations scattered in the upper and lower MARB from 1996 to 2020. Eight surface water quality indicators were selected to make comparisons among water stations along the MARB over the past two decades. Principal component analysis (PCA) was used to comprehensively evaluate the nutrient yields across thirty-three USGS monitoring stations and identify the major contributing nutrient loads. The results showed that all samples could be analyzed using two main components, which accounted for 81.6% of the total variance. The PCA results showed that yields of orthophosphate (OP), silica (SI), nitrate–nitrites (NO 3 -NO 2 ), and total suspended sediment (TSS) are major contributors to nutrient yields. It also showed that land-planted crops, density of population, domestic and industrial discharges, and precipitation are fundamental causes of excess nutrient loads in MARB. These factors are of great significance for the excess nutrient load management and pollution control of the Mississippi River. It was found that the average nutrient yields were stable within the sub-MARB area, but the large nitrogen yields in the upper MARB and the large phosphorus yields in the lower MARB were of great concern. t-distributed stochastic neighbor embedding (t-SNE) revealed interesting nonlinear and local structures in nutrient yield distributions. Clustering analysis (CA) showed the detailed development of similarities in the nutrient yield distribution. Moreover, PCA, t-SNE, and CA showed consistent clustering results. This study demonstrated that the integration of dimension reduction techniques, PCA, and t-SNE with CA techniques in machine learning are effective tools for the visualization of the structures of the correlations in high-dimensional datasets of nutrient yields and provide a comprehensive understanding of the correlations in the distributions of nutrient loads across the MARB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Comparison of Machine Learning-Based Predictive Models of the Nutrient Loads Delivered from the Mississippi/Atchafalaya River Basin to the Gulf of Mexico

Predicting nutrient loads is essential to understanding and managing one of the environmental issues faced by the northern Gulf of Mexico hypoxic zone, which poses a severe threat to the Gulf’s healthy ecosystem and economy. The development of hypoxia in the Gulf of Mexico is strongly associated with the eutrophication process initiated by excessive nutrient loads. Due to the complexities in the excessive nutrient loads to the Gulf of Mexico, it is challenging to understand and predict the underlying temporal variation of nutrient loads. The study was aimed at identifying an optimal predictive machine learning model to capture and predict nonlinear behavior of the nutrient loads delivered from the Mississippi/Atchafalaya River Basin (MARB) to the Gulf of Mexico. For this purpose, monthly nutrient loads (N and P) in tons were collected from US Geological Survey (USGS) monitoring station 07373420 from 1980 to 2020. Machine learning models—including autoregressive integrated moving average (ARIMA), gaussian process regression (GPR), single-layer multilayer perceptron (MLP), and a long short-term memory (LSTM) with the single hidden layer—were developed to predict the monthly nutrient loads, and model performances were evaluated by standard assessment metrics—Root Mean Square Error (RMSE) and Correlation Coefficient (R). The residuals of predictive models were examined by the Durbin–Watson statistic. The results showed that MLP and LSTM persistently achieved better accuracy in predicting monthly TN and TP loads compared to GPR and ARIMA. In addition, GPR models achieved slightly better test RMSE score than ARIMA models while their correlation coefficients are much lower than ARIMA models. Moreover, MLP performed slightly better than LSTM in predicting monthly TP loads while LSTM slightly outperformed for TN loads. Furthermore, it was found that the optimizer and number of inputs didn’t show effects on the LSTM performance while they exhibited impacts on MLP outcomes. This study explores the capability of machine learning models to accurately predict nonlinearly fluctuating nutrient loads delivered to the Gulf of Mexico. Further efforts focus on improving the accuracy of forecasting using hybrid models which combine several machine learning models with superior predictive performance for nutrient fluxes throughout the MARB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

CORE-CM Williston Basin Carbon Ore, Rare Earth, and Critical Minerals

Fact sheet on the Carbon Ore, Rare Earth and Critical Minerals (CORE-CM) Initiative, an Energy & Environmental Research Center and U.S. Department of Energy project. Includes information on the importance of critical minerals and utilizing lignite from the Williston Basin.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

CORE-CM Williston Basin Carbon Ore, Rare Earth, and Critical Minerals

Fact sheet on the Carbon Ore, Rare Earth and Critical Minerals (CORE-CM) Initiative, an Energy & Environmental Research Center and U.S. Department of Energy project. Includes information on the importance of critical minerals and utilizing lignite from the Williston Basin.

01 COAL, LIGNITE, AND PEAT↗