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
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.
Citation Formats
TY - DATA
AB - 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.
AU - Smith, Jared
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO - 10.15121/1632873
KW - geothermal
KW - energy
KW - Cornell University
KW - low-temperature geothermal
KW - reservoir simulation
KW - uncertainty analysis
KW - thermal data
KW - district heating
KW - direct-use heating
KW - DDU
KW - Appalachian Basin
KW - New York state
KW - techno-economic analysis
KW - levelized cost of heat LCOH
KW - externality values
KW - environmental value
KW - Monte Carlo analysis
KW - Monte Carlo
KW - economic
KW - EA
KW - heat pump
KW - ghp
KW - shapefile
KW - raster
KW - Cornell
KW - geospatial data
LA - English
DA - 2019/10/29
PY - 2019
PB - Cornell University
T1 - 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
UR - https://doi.org/10.15121/1632873
ER -
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. Cornell University, 29 October, 2019, GDR. https://doi.org/10.15121/1632873.
Smith, J. (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. [Data set]. GDR. Cornell University. https://doi.org/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. Cornell University, October, 29, 2019. Distributed by GDR. https://doi.org/10.15121/1632873
@misc{OEDI_Dataset_7316,
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.},
url = {https://gdr.openei.org/submissions/1182},
year = {2019},
howpublished = {GDR, Cornell University, https://doi.org/10.15121/1632873},
note = {Accessed: 2025-05-05},
doi = {10.15121/1632873}
}
https://dx.doi.org/10.15121/1632873
Details
Data from Oct 29, 2019
Last updated Sep 2, 2021
Submitted Nov 6, 2019
Organization
Cornell University
Contact
Teresa Jordan
607.255.3596
Authors
Original Source
https://gdr.openei.org/submissions/1182Research Areas
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, geospatial dataDOE Project Details
Project Name EARTH SOURCE HEAT: A CASCADED SYSTEMS APPROACH TO DDU OF GEOTHERMAL ENERGY ON THE CORNELL CAMPUS
Project Lead Arlene Anderson
Project Number EE0008103