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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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23 records · Page 2
All sourcesNASA NTRSDOE OSTI
DOE OSTI2019

Deep Direct-Use Feasibility Study Reservoir Productivity Uncertainty Analysis for the Tuscarora Sandstone, Morgantown, WV

This dataset contains figures that summarize the Tuscarora Sandstone core permeability data collected from the Preston 119 well in Preston County, WV, and summary results of a stochastic analysis that was used to estimate reservoir productivity for the currently unexplored Tuscarora Sandstone below Morgantown, West Virginia. Uncertainties in reservoir productivity considered the thickness of the reservoir, rock permeability, and fluid viscosity. A Monte Carlo analysis of these uncertain properties was used to predict reservoir flow productivity for the case of a matrix-dominated reservoir, and a fracture-dominated reservoir. These results are summarized in figures, spreadsheets, and maps.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Deep Direct-Use Feasibility Study Temperature-Depth Estimates for West Virginia University, Morgantown, WV

This dataset contains data spreadsheets and figures that summarize the results of a stochastic analysis of temperatures at depth below the West Virginia University campus in Morgantown, WV. These results are extracted from a study by Smith (2019), whose results are included in a GDR submission that provides rasters and shapefiles for the Appalachian Basin states of New York, Pennsylvania, and West Virginia (GDR submission #1182). Uncertainties considered included geologic properties, thermal properties, and uncertainty from geostatistical interpolation of the surface heat flow. A Monte Carlo analysis of these uncertain properties was used to predict temperatures at depth using a 1-D heat conduction model. For the pixel corresponding to West Virginia University, a .csv file containing the 10,000 temperature-depth profiles estimated from a Monte Carlo analysis is provided. Temperatures are provided for depths from 1-5 km in 0.5 km increments. These data are summarized in a figure containing violin plots that illustrates the probability of obtaining certain temperatures at depth for Morgantown.

15 GEOTHERMAL ENERGY↗
DOE OSTI2019

Deep Direct-Use Feasibility Study Numerical Modeling and Uncertainty Analysis using iTOUGH2 for West Virginia University

To reduce the geothermal exploration risk, a feasibility study is performed for a deep direct-use system proposed at the West Virginia University (WVU) Morgantown campus. This study applies numerical simulations to investigate reservoir impedance and thermal production. Because of the great depth of the geothermal reservoir, few data are available to characterize reservoir features and properties. As a result, the study focuses on the following three aspects: 1. model choice for predicting reservoir impedance and thermal breakthrough: after investigating three potential models (one single permeability model and two dual permeability models) for flow through fractured rock, it is decided to use single permeability model for further analysis; 2. well placement (horizontal vs. vertical) options: horizontal well placement seems to be more robust to heterogeneity and the impedance is more acceptable; 3. Prediction uncertainty: the most influential parameters are identified using a First-Order-Second-Moment uncertainty propagation analysis, and the uncertain range of the model predictions is estimated by performing a Monte Carlo simulation. Heterogeneity has a large impact on the perdition, therefore, is considered in the predictive model and uncertainty analysis. The numerical model results and uncertainty analysis are used for economic analysis. The dataset submitted here support the described study. Manuscript is submitted to Geothermics, will be linked once paper is accepted.

15 GEOTHERMAL ENERGY↗
DOE OSTI2020

Hawthorne Nevada Deep Direct-Use Feasibility Study - Data Used for Geothermal Resource Conceptual Modeling and Power Capacity Estimates

This data submission includes several data components that were used to develop a conceptual model and power capacity-estimates of two low-temperature geothermal resources that define geothermal prospect A at Hawthorne, Nevada. Data are sourced from a combination of legacy publicly-available data and more recent data acquisition conducted by the US Navy Geothermal Program Office (2008-2013) and the Great Basin Center for Geothermal Energy at the University of Nevada, Reno (2008-2010). Data sets include compiled fluid geochemistry data, down-hole temperature logs for wells in the vicinity of prospect A, 2 meter temperature survey data, temperature-spinner logs acquired in well HWAAD-2A, fracture picks from image log data acquired in wells HWAAD-2 and HWAAD-3, and X-Ray Diffraction (XRD) analyses on cuttings from wells HWAAD-2A and HWAAD-3. These data have been reviewed for errors and inconsistencies, but it is possible that few errors could still remain. The resource conceptual model and power capacity estimates are included in the final report to the US Department of Energy, and are presented in a manuscript by Ayling and Hinz. A link to the manuscript published in Geothermics is linked below in this submission.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Techno-Economic Simulation Results Using dGeo for EGS-Based District Heating in the Northeastern United States

This dataset presents the results of techno-economic simulations performed using the Distributed Geothermal Market Demand Model (dGeo) to evaluate the feasibility of Enhanced Geothermal Systems (EGS)-based district heating in the Northeastern United States. Developed by the National Renewable Energy Laboratory (NREL), dGeo is a geospatially resolved, bottom-up modeling framework designed to explore the deployment potential of geothermal distributed energy resources. The dataset, created as part of the Cornell EGS Ground-Truthing Project, provides census tract-level data that includes inputs and outputs such as thermal demand, road length, energy prices, geothermal system sizing, annual energy contributions from geothermal and natural gas peaking boilers, system capital costs (CAPEX), operation and maintenance costs (OPEX), and the levelized cost of heat (LCOH). Key simulation parameters include geothermal gradients, measured well depths, production temperatures, and district heating piping lengths based on S1400 neighborhood road lengths. The simulations assume a target bottom hole temperature of 80C and the development of new district heating networks in each census tract.

15 GEOTHERMAL ENERGY↗