Geothermal Reservoir Simulation Results in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy

                                            [
  "019:20"
]
                                        

                                            {
  "fn": "Teresa Jordan",
  "@type": "vcard:Contact",
  "hasEmail": "mailto:tej1@cornell.edu"
}
                                        

                                            true
                                        

                                            [
  {
    "@type": "dcat:Distribution",
    "title": "About Geothermal Reservoir Simulation Results Cornell DDU Project.docx",
    "format": "docx",
    "accessURL": "https://gdr.openei.org/files/1183/AboutGeothermalReservoirSimulationResultsCornellDDUProject.docx",
    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
    "description": "This file describes the content of a compressed file of reservoir modeling inputs and outputs. 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 3-3.5 km depth and 3.5-4 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. Detailed descriptions of the contents of this repository are provided below.

Reference:
Smith, J.D. and K.F. Beckers. (2020). Uncertainty and sensitivity analysis for geothermal reservoir performance and techno-economic assessments: A software package for GEOPHIRES. Proceedings World Geothermal Congress 2020. Reykjavik, Iceland, April 26-2."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Basement Reservoir Simulations FOLDER.zip",
    "format": "zip",
    "accessURL": "https://gdr.openei.org/files/1183/Basement_ReservoirSimulations.zip",
    "mediaType": "application/zip",
    "description": "This compressed file contains several folders with results of modeling heat production from and lifetime of a plausible geothermal reservoir located in crystalline basement rock. See also accompanying Resource "About Geothermal Reservoir Simulation Results Cornell DDU Project.docx".

Folder: Basement_ReservoirSimulations
a.	18 folders of the format: Run11_BasementDepth_ReservoirModelType_UncertainParameterType_SimulationLifetime_InjectionTemperature_FlowRate_FractureSpacing

These folders contain GEOPHIRES results for basement rock geothermal reservoir simulations: 9 folders are for 3 - 3.5 km depth scenarios, and 9 folders are for 3.5 - 4 km depth scenarios.

Folder name format:
The run number (11) is the same for these folders because they rely on the same probability distributions. 
The basement depth is either 3p5, corresponding to a reservoir from 3 – 3.5 km depth, or 4p0, corresponding to a reservoir from 3.5 – 4.0 km depth. 
The reservoir model type is mpf for multiple parallel fractures.
The uncertain parameter type is GeoEco for uncertainty in both geologic property parameters and economic and utilization parameters.
The simulation lifetime is 150 years
The injection temperatures are either 20, 30, or 50 °C
Flow rates are either 30, 50, or 70 kgs. 70 kgs uses wells with a larger pipe diameter than the other two flow rates.
Fracture spacing is 30 m.

For details about the contents of these folders, refer to the file: GEOPHIRES_OutputFileDescriptions.docx

b.	Folder: Run11_SummaryProbabilityPlots_Basement
Figures that summarize the probability results computed from each of the 18 simulations. Plots show the year when the probability is < 95% that the produced fluid will provide > X MWth heat, > T °C, or jointly provide > X MWth and > T °C."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Code FOLDER.zip",
    "format": "zip",
    "accessURL": "https://gdr.openei.org/files/1183/Code.zip",
    "mediaType": "application/zip",
    "description": "See also accompanying Resource "About Geothermal Reservoir Simulation Results Cornell DDU Project.docx".

Folder: Code
a.	PlottingFunctions.R
This code processes, analyzes, and plots GEOPHIRES output. 

The specific GEOPHIRES code that provides the output required as input to this R script is available on GitHub under 
commit f26e0aa6e1346e3e9b9ec3b244c6d6f313f037e3 . This commit was made by Jared Smith on Mon Jan 7 11:44:31 2019 to the UncertaintyAnalysis branch of the GEOPHIRES GitHub repository (https://github.com/kfbeckers/GEOPHIRES). This repository is currently private, and the license for the code is currently under review. If you require this code, please contact Jared Smith (jds485@cornell.edu).

A more recent commit is available on the Uncertainty Analysis branch of GEOPHIRES, which corrects for some plotting errors (e.g. labels, legend position, etc.). No quantitative analysis changes exist in this commit.
commit 2becc9217fd2ce1286f5dc2264799be67c01d6bb by Jared Smith on Tue Jul 30 12:13:17 2019

b.	Plots_TOUGH2_PostGEOPHIRES.R 
An R script to process and plot TOUGH2 results to make the figure Run10_TBR_TOUGH2_40yrs_20Cinj_ProdTempHeatPostGEOPHIRES.png

c.	ProbabilityLifetimePlots.R and ProbabilityLifetimePlots_Basement.R
R scripts to process, analyze, and plot GEOPHIRES output, as described in the SummaryProbabilityPlots sections for TBR and basement rock simulations, respectively.
"
  },
  {
    "@type": "dcat:Distribution",
    "title": "GEOPHIRES Input Parameter Descriptions.xlsx",
    "format": "xlsx",
    "accessURL": "https://gdr.openei.org/files/1183/GEOPHIRES_InputParameterDescriptions.xlsx",
    "mediaType": "application/vnd.openxmlformats-officedocument.spreadsheetml.sheet",
    "description": "Provides a list of all GEOPHIRES uncertainty analysis input parameters and their descriptions."
  },
  {
    "@type": "dcat:Distribution",
    "title": "GEOPHIRES Output File Descriptions.docx",
    "format": "docx",
    "accessURL": "https://gdr.openei.org/files/1183/GEOPHIRES_OutputFileDescriptions.docx",
    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
    "description": "Provides descriptions of all GEOPHIRES uncertainty analysis output folders and files."
  },
  {
    "@type": "dcat:Distribution",
    "title": "Monte Carlo GEOPHIRES in Parallel ReadMe.docx",
    "format": "docx",
    "accessURL": "https://gdr.openei.org/files/1183/MonteCarloGEOPHIRESinParallel_ForGeophiresv2.docx",
    "mediaType": "application/vnd.openxmlformats-officedocument.wordprocessingml.document",
    "description": "This is the ReadMe file describing files contained within the Code/GEOPHIRES-ModifiedForCornellDDU directory. This document also describes how to run the GEOPHIRES uncertainty analysis.

Additional descriptions of the code for uncertainty analysis of GEOPHIRES may be found within the World Geothermal Congress 2020 conference paper by Smith and Beckers (2020).

Smith, J.D. and K.F. Beckers. (2020). Uncertainty and sensitivity analysis for geothermal reservoir performance and techno-economic assessments: A software package for GEOPHIRES. Proceedings World Geothermal Congress 2020. Reykjavik, Iceland, April 26-2."
  },
  {
    "@type": "dcat:Distribution",
    "title": "TBR Reservoir Simulations FOLDER.zip",
    "format": "zip",
    "accessURL": "https://gdr.openei.org/files/1183/TBR_ReservoirSimulations.zip",
    "mediaType": "application/zip",
    "description": "This compressed folder contains results from modeling the thermal performance and lifetime of a potential geothermal reservoir located in a Trenton-Black River (TBR) hydrothermal dolomite system. Two alternate approaches to analyzing the performance were used, GEOPHIRES and TOUGH2, and contained folders present both sets of materials. See also accompanying Resource "About Geothermal Reservoir Simulation Results Cornell DDU Project."

Folder: Run10_TBR_GEOPHIRES
aa.	18 folders of the format: Run10_TBR_ReservoirModelType_UncertainParameterType_SimulationLifetime_InjectionTemperature_FlowRate_FractureSpacing

These folders contain GEOPHIRES results for Trenton-Black River (TBR) geothermal reservoir simulations: 9 folders are for the multiple parallel fractures reservoir model (mpf), and 9 folders are for the plug flow reservoir model (pf).

Folder name format:
The run number (10) is the same for these folders because they rely on the same probability distributions. 
The reservoir model type is mpf for multiple parallel fractures, or pf for plug flow.
The uncertain parameter type is GeoEco for uncertainty in both geologic property parameters and economic and utilization parameters.
The simulation lifetime is 40 years
The injection temperatures are either 20, 30, or 50 °C
Flow rates are either 30, 50, or 70 kgs. 70 kgs uses wells with a larger pipe diameter than the other two flow rates.
Fracture spacing is 20 m for the mpf models.

For details about the contents of these folders, refer to the file: GEOPHIRES_OutputFileDescriptions.docx

bb.	Folder: Run11_SummaryProbabilityPlots_Basement
Figures that summarize the probability results computed from each of the 18 simulations. Plots show the year when the probability is < 95% that the produced fluid will provide > X MWth heat, > T °C, or jointly provide > X MWth and > T °C.


b.	Folder: Run10_TBR_TOUGH2simsAndGeophires
aa.	Folder: TBR_TOUGH2sims
aaa.	3 folders of the format: TBR_Temperature
Temperatures are Cold5, Med, and Hot5 for the coldest 5th percentile, median, and hottest 5th percentile of the predicted temperatures at depth, respectively.

Each of these folders have similar file contents.
aaaa.	3 folders of the format: Prod_T20QXX
The X corresponds to the selected flow rate.
Within each of these folders there is a file with a .sim extension. This is the PetraSim runfile for the production scenario. It calls all of the other files within the folder for the simulation and visualization of the results. To see the results, load the SAVE file into PetraSim.

bbbb.	A .sim file, and other files required to set up the TOUGH2 initial conditions. The .sim file is the PetraSim runfile for establishing the initial conditions. It calls all of the other files within the folder for the simulation and visualization of the results. To see the results of the initial conditions used for the production scenarios, load the SAVE file into PetraSim.     

bbb.	Folder: TBR_Diagram_Hot5TempPressurePics
aaaa.	Folder: Pressure
Contains 9 figures of pressure change over time in the TOUGH2 reservoir simulation. Three times (4, about 20, and 40 years) are selected for each of 3 flow rates (30, 50, and 70 kg/s). The injection temperature is 20 °C. The reservoir initial conditions correspond to the hottest 5th percentile of the predicted temperatures at depth.

bbbb.	Folder: Temperature
Contains 9 figures of temperature change over time in the TOUGH2 reservoir simulation. Three times (4, about 20, and 40 years) are selected for each of 3 flow rates (30, 50, and 70 kg/s). The injection temperature is 20 °C. The reservoir initial conditions correspond to the hottest 5th percentile of the predicted temperatures at depth.

cccc.	File: TOUGH2TempsPressures_Hot5.ppt
Contains slides that aggregate the temperature and pressure figures into 9-panel plots.

bb.	Folder: TBR_GEOPHIRES
aaa.	9 folders of the format: Run10_TBR_TOUGH2_Eco_40yrs_20Cinj_FlowRate_InitialReservoirTemperature

These folders contain GEOPHIRES results for post-processing of the TOUGH2 simulations to account for production wellbore heat transfer.

Folder name format:
The run number (10) is the same for these folders because they rely on the same probability distributions. 
The uncertain parameter type is Eco for uncertainty in only economic and utilization parameters.
The simulation lifetime is 40 years
The injection temperature is 20 °C
Flow rates are either 30, 50, or 70 kgs. 70 kgs uses wells with a larger pipe diameter than the other two flow rates.
The initial reservoir temperature is either the coldest 5th percentile, median, or hottest 5th percentile (Cold5, Med, Hot5).

For details about the contents of these folders, refer to the file: GEOPHIRES_OutputFileDescriptions.docx

bbb.	Run10_TBR_TOUGH2_40yrs_20Cinj_ProdTempHeatPostGEOPHIRES.png
This figure summarizes the temperature and heat production results from post-GEOPHIRES simulation of the TOUGH2 results to account for production wellbore heat transfer.
"
  },
  {
    "@type": "dcat:Distribution",
    "title": "Final Report - Earth Source Heat A Cascaded Systems Approach to DDU of Geothermal Energy on the Cornell Campus",
    "format": "HTML",
    "accessURL": "https://gdr.openei.org/submissions/1180",
    "mediaType": "text/html",
    "description": "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."
"
  },
  {
    "@type": "dcat:Distribution",
    "title": "Subsurface Geological Information and Models in support of Feasibility Study of Direct District Heating for the Cornell Campus Utilizing Deep Geothermal Energy",
    "format": "HTML",
    "accessURL": "https://gdr.openei.org/submissions/1181",
    "mediaType": "text/html",
    "description": "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."
  },
  {
    "@type": "dcat:Distribution",
    "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",
    "format": "HTML",
    "accessURL": "https://gdr.openei.org/submissions/1182",
    "mediaType": "text/html",
    "description": "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."
  }
]
                                        

                                            [
  "Cornell",
  "Cornell University",
  "DDU",
  "GEOPHIRES",
  "Monte Carlo",
  "Monte Carlo analysis",
  "New York state",
  "PetraSIM",
  "TOUGH2",
  "Trenton-Black River",
  "direct use",
  "direct-use heating",
  "district heating",
  "economic value",
  "energy",
  "environmental value",
  "externality values",
  "geothermal",
  "heat pumps",
  "levelized cost of heat LCOH",
  "low-temperature geothermal",
  "reservoir simulation",
  "stochastic analysis",
  "techno-economic analysis",
  "uncertainty analysis"
]
                                        

                                            [
  "019:006"
]
                                        

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  "name": "Cornell University",
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