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

Smith, Jared

doi:10.15121/1593282

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

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Abstract

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.

Authors:

Smith, Jared

West Virginia University

Publication Date:: Wed Dec 18 23:00:00 EST 2019

Other Number(s):: 1192

DOE Contract Number:: EE0008105

Research Org.:: DOE Geothermal Data Repository; West Virginia University

Sponsoring Org.:: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Program (EE-2C)

Collaborations:: West Virginia University

Subject:: 15 GEOTHERMAL ENERGY; Appalachian Basin; Cornell; DDU; Deep Direct-Use; EGS; Monte Carlo analysis; Morgantown; WVU; depth data; geothermal; low-temperature; low-temperature geothermal; resource assessment; resource potential; temperature data; temperature-depth estimates; uncertainty analysis

OSTI Identifier:: 1593282

DOI:: https://doi.org/10.15121/1593282

Citation Formats


                    Smith, Jared. Deep Direct-Use Feasibility Study Temperature-Depth Estimates for West Virginia University, Morgantown, WV.  United States: N. p., 2019. 
        Web.  doi:10.15121/1593282.

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                    Smith, Jared. Deep Direct-Use Feasibility Study Temperature-Depth Estimates for West Virginia University, Morgantown, WV.  United States.  doi:https://doi.org/10.15121/1593282

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                    Smith, Jared. 2019.  
"Deep Direct-Use Feasibility Study Temperature-Depth Estimates for West Virginia University, Morgantown, WV".  United States.  doi:https://doi.org/10.15121/1593282.  https://www.osti.gov/servlets/purl/1593282. Pub date:Wed Dec 18 23:00:00 EST 2019

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@article{osti_1593282,

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

  author       = {Smith, Jared},

  abstractNote = {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.},

  doi          = {10.15121/1593282},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Wed Dec 18 23:00:00 EST 2019},

  month        = {Wed Dec 18 23:00:00 EST 2019}

}

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DOI: https://doi.org/10.15121/1593282

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