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Title: Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy

Abstract

This dataset contains shapefiles and rasters that summarize the results of a stochastic analysis of temperatures at depth in the Appalachian Basin states of New York, Pennsylvania, and West Virginia. This analysis provides an update to the temperature-at-depth maps provided in the Geothermal Play Fairway Analysis of the Appalachian Basin (GPFA-AB) Thermal Quality Analysis (GDR repository 879: https://gdr.openei.org/submissions/879). This dataset improves upon the GPFA-AB dataset by considering several additional uncertainties in the temperature-at-depth calculations, including geologic properties and thermal properties. A Monte Carlo analysis of these uncertain properties and the GPFA-AB estimated surface heat flow was used to predict temperatures at depth using a 1-D heat conduction model. In this data submission, temperatures are provided for depths from 1-5 km in 0.5 km increments. The mean, standard deviation, and selected quantiles of temperatures at these depths are provided as shapefiles with attribute tables that contain the data. Rasters are provided for the mean and standard deviation data. Figures and maps that summarize the data are also provided. For the pixel corresponding to Cornell University, Ithaca, NY, a .csv file containing the 10,000 temperature-depth profiles estimated from the Monte Carlo analysis is provided. These data are summarized in a figure containingmore » violin plots that illustrate the probability of obtaining certain temperatures at depths below Cornell.« less

Authors:
ORCiD logo
Publication Date:
Other Number(s):
1182
DOE Contract Number:  
EE0008103
Product Type:
Dataset
Research Org.:
USDOE Geothermal Data Repository (United States); Cornell Univ., Ithaca, NY (United States)
Sponsoring Org.:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Program (EE-4G)
Subject:
15 Geothermal Energy
Keywords:
geothermal; energy; Cornell University; low-temperature geothermal; reservoir simulation; uncertainty analysis; thermal data; district heating; direct-use heating; DDU; Appalachian Basin; New York state; techno-economic analysis; levelized cost of heat LCOH; externality values; environmental value; Monte Carlo analysis; Monte Carlo; economic; EA; heat pump; ghp; shapefile; raster; Cornell
OSTI Identifier:
1632873
DOI:
https://doi.org/10.15121/1632873

Citation Formats

Smith, Jared. Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy. United States: N. p., 2019. Web. doi:10.15121/1632873.
Smith, Jared. Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy. United States. doi:https://doi.org/10.15121/1632873
Smith, Jared. 2019. "Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy". United States. doi:https://doi.org/10.15121/1632873. https://www.osti.gov/servlets/purl/1632873. Pub date:Tue Oct 29 00:00:00 EDT 2019
@article{osti_1632873,
title = {Appalachian Basin Temperature-Depth Maps and Structured Data in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy},
author = {Smith, Jared},
abstractNote = {This dataset contains shapefiles and rasters that summarize the results of a stochastic analysis of temperatures at depth in the Appalachian Basin states of New York, Pennsylvania, and West Virginia. This analysis provides an update to the temperature-at-depth maps provided in the Geothermal Play Fairway Analysis of the Appalachian Basin (GPFA-AB) Thermal Quality Analysis (GDR repository 879: https://gdr.openei.org/submissions/879). This dataset improves upon the GPFA-AB dataset by considering several additional uncertainties in the temperature-at-depth calculations, including geologic properties and thermal properties. A Monte Carlo analysis of these uncertain properties and the GPFA-AB estimated surface heat flow was used to predict temperatures at depth using a 1-D heat conduction model. In this data submission, temperatures are provided for depths from 1-5 km in 0.5 km increments. The mean, standard deviation, and selected quantiles of temperatures at these depths are provided as shapefiles with attribute tables that contain the data. Rasters are provided for the mean and standard deviation data. Figures and maps that summarize the data are also provided. For the pixel corresponding to Cornell University, Ithaca, NY, a .csv file containing the 10,000 temperature-depth profiles estimated from the Monte Carlo analysis is provided. These data are summarized in a figure containing violin plots that illustrate the probability of obtaining certain temperatures at depths below Cornell.},
doi = {10.15121/1632873},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {10}
}