| Name |
Format |
Description |
Link |
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57 |
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 of the crystalline basement. Also included is the necessary information to place the temperature data in a GIS application. The second major content set are files that model the temperature changes with depth below Cornell University. See also the accompanying Resource "About Appalachian Basin Temperature Depth Results from Cornell DDU Project."
1. Folder: AppalachianBasinTemperatureDepthMaps
a. 10 folders of the format AppBasinTemperature
Temperatures are for 1 to 5 km in 0.5 km increments, and also at the basement depth.
Each of these folders contain 9 files:
i. 4 files of the format Quantiles_Temperature
These files have extensions .dbf, .prj, .shp, and .shx, and provide the necessary information to plot the data in a GIS software application.
Attribute table columns:
POINT_X: the easting coordinate in NAD83 UTM 17N (m)
POINT_Y: the northing coordinate in NAD83 UTM 17N (m)
Qs: the estimated mean surface heat flow from Smith (2016). Available for download on the Geothermal Data Repository (Cornell University, 2016). (mW/m2)
QsErr: the estimated surface heat flow standard deviation from Smith (2016). Available for download on the Geothermal Data Repository (Cornell University, 2016). (mW/m2)
SurfTemp: the average annual ground surface temperature from Gass (1982). Available from the Southern Methodist University Geothermal Laboratory. (°C)
BasementDe: the depth to basement rock. Map available on the geothermal data repository (Cornell University, 2015). (m)
ROME_ID: Identifier for if the location is in the Rome Trough (1) or not (0)
COSUNA_ID: ID number for the COSUNA column region – short format.
COSUNAID2: ID number for the COSUNA column region – long format.
NAME: Name of the COSUNA column region
SedRadHeat: average heat generation rate assigned to all sedimentary rocks. (μW/m3)
QMantle: average mantle heat flow rate. Used for calculations in basement rock only. (mW/m2)
CharInd: the grid cell ID number as a character string.
TXkm_Q: The Qth quantile of the estimated temperature at X km depth, from Smith (2019). Note, temperature at the basement depth is labeled as TBas_Q. (°C)
ii. Temp1kmQuantiles.png
Maps of the temperature at 1 km depth. The data to make this file is in the Quantiles_Temperature attribute table. The coordinate system is NAD83 UTM 17N.
iii. TempXkmMean.tif and corresponding .aux file
A GeoTIFF file of the predicted mean temperature at X km depth, from Smith (2019).
iv. Temp1kmSD.tif and corresponding .aux file
A GeoTIFF file of the standard deviation of the predicted mean temperature at X km depth, from Smith (2019).
b. 4 files of the format MeanSDmapData
These files have extensions .dbf, .prj, .shp, and .shx, and provide the necessary information to plot the data in a GIS software application.
Attribute table columns:
The same as for Quantiles_Temperature file, except the temperature predictions are:
TXkm_m or TXkm_mn: The estimated mean temperature at X km depth, from Smith (2019). Note, temperature at the basement depth is labeled as TBas_m. (°C)
TXkm_s or TXkm_sd: The estimated standard deviation of the temperature at X km depth, from Smith (2019). Note, temperature at the basement depth is labeled as TBas_s. (°C)
2. Folder: IthacaCornellTemperatureDepthData
a. File: 644572_CornellTemperatureDepthReplicates.csv
File containing the 10,000 replicates of temperature-depth estimates for the pixel corresponding to Cornell University in the Appalachian Basin temperature-depth resource assessment by Smith (2019). The number 644572 is the pixel index number on the maps in the Appalachian Basin Temperature Depth Maps folder.
Columns:
rep: the replicate ID number, from 0 – 9999.
TXkm, TXp5 km, TBase: temperature estimated at X km, X.5 km, and basement depth, respectively.
b. File: IthacaTemperaturesAtDepth_AvgGrad.png
Violin plots of the temperatures at depth for Ithaca. Data for the violin plots are from the 644572_CornellTemperatureDepthReplicates.csv file. This figure also includes the average geothermal gradient in red.
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https://gdr.openei.org/files/1182/CornellDDU_AppBasinTemps.zip |
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33 |
Poster illustrates basic subsurface information for the Cornell University proposed geothermal district heating system, inclusive of: depth to basement maps, the regional stratigraphic framework that is the basis for predicting depths to rock units below Ithaca, NY; characteristic porosity logs and their spatial variability; the depths below Ithaca of four plausible geothermal reservoir targets within the sedimentary rocks; geothermal gradients at individual nearby boreholes and their uncertainty; and predicted temperatures at depth below Cornell.
The poster was created late in 2018, and modified after two theses were completed in 2019. |
https://gdr.openei.org/files/1182/2019_SmithEtAl_GeothermalForIthaca_d8.pdf |
|
21 |
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 surrounding two potential reservoirs. |
https://gdr.openei.org/submissions/1181 |
|
10 |
The file lists the contents of the zipped file CornellDDU_AppBasinTemps. The datasets describe the stochastic analysis of temperatures at depth throughout the Appalachian Basin parts of New York, Pennsylvania, and West Virginia, and more specifically below the Cornell campus. This dataset improves on results presented several years ago by including the uncertainties associated with geologic properties and thermal properties. See also the accompanying Resource "About Appalachian Basin Temperature Depth Results Cornell DDU Project. docx."
1. Folder: AppalachianBasinTemperatureDepthMaps
2. Folder: IthacaCornellTemperatureDepthData
References |
https://gdr.openei.org/files/1182/AboutAppalachianBasinTemperatureDepthResultsCornellDDUProject.docx |
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21 |
The purpose of this document is to describe the contents contained within Geothermal Data Repository (GDR) node of the National Geothermal Data System (NGDS) that serves as the final report for the project "Earth Source Heat: A Cascaded Systems Approach to DDU of Geothermal Energy on the Cornell Campus".
Abstract: Cornell completed a comprehensive evaluation of the potential for Earth Source Heat (ESH), Cornell's specific application of Deep Direct Use (DDU) geothermal energy, to create viable heat energy for its Ithaca, NY campus district heating system. The study included assessment of the natural rock properties within and surrounding two potential reservoirs, coupled to the assessment of the thermal energy needs for a district heating system capable of supplying 20% of Cornell's building heating load. The feasibility and benefits of such a district heating system at the specific location of Cornell University's Ithaca, NY campus are evaluated from the perspectives of economic cost, environmental benefits, and economic benefits in the region external to Cornell University. The economic cost is expressed as the Levelized Cost of Heat, and comparison to the existing inexpensive fossil fuel system.
The submission includes descriptions of the assumptions, analyses, data, and models that were combined to reach conclusions regarding the feasibility of a Cornell Campus project.
A shortened, descriptive title for the project is "Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy."
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https://gdr.openei.org/submissions/1180 |
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21 |
This dataset contains input data, code, ReadMe files, output data, and figures that summarize the results of a stochastic analysis of geothermal reservoir production from two potential geothermal reservoirs that were evaluated for the Cornell University Deep Direct-Use project. These potential reservoirs are the Trenton-Black River (TBR) from 2.27-2.3 km depth, and basement rocks from 3.0-3.5 km depth and 3.5-4.0 km depth. Several utilization scenarios consisting of different injection fluid temperatures and flow rates were evaluated for each reservoir. Uncertainty in geologic properties, thermal properties, economic costs, and utilization efficiencies were evaluated using a Monte Carlo analysis of the reservoir simulations. Some reservoir simulations of the TBR were completed using the TOUGH2 software, as implemented in PetraSIM. The PetraSIM run files and associated data are provided with this submission. All other reservoir simulations were completed using the GEOPHIRES software, with some modifications to complete the uncertainty analyses. ReadMe files that describe additions to GEOPHIRES, the GEOPHIRES input data, and the output data are all provided, and references are provided to the code repository. Figures that summarize the reservoir heat production, temperature drawdown, and the probability of meeting targeted building heating demands with the produced heat and fluid temperatures are provided. |
https://gdr.openei.org/submissions/1183 |