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

Publicly accessible License 

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.

About Appalachian Basin Temperature Depth Results Cornell DDU Project.docx

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156

Cornell DDU Appalachian Basin Temperatures.zip

The contents includes a set of illustrations of the modeled temperatures in the Appalachian Basin subsurface in depths slices between 1 and 5 km depth, and at the top o... more
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Final Report - Earth Source Heat A Cascaded Systems Approach to DDU of Geothermal Energy on the Cornell Campus

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Poster of Geothermal Resource and Reservoir Characterization.pdf

Poster illustrates basic subsurface information for the Cornell University proposed geothermal district heating system, inclusive of: depth to basement maps, the region... more
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Subsurface Geological Information and Models in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy

This purpose of this set of entries is to group together the materials and analytical methods used in the assessment of the natural rock properties within and surroundi... more

Citation Formats

Cornell University. (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]. Retrieved from https://dx.doi.org/10.15121/1632873.
Export Citation to RIS
Smith, Jared, and . 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., 29 Oct, 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. https://dx.doi.org/10.15121/1632873
Smith, Jared, and . 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. https://dx.doi.org/10.15121/1632873. https://gdr.openei.org/submissions/1182.
@div{oedi_1182, 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, and .}, 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}, url = {https://gdr.openei.org/submissions/1182}, journal = {}, number = , volume = , place = {United States}, year = {2019}, month = {10}}
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

tej1@cornell.edu

607.255.3596

Authors

Jared Smith

Cornell University

DOE 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

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