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Geothermal Play Fairway Analysis for Low-Temperature Resources in the Denver Basin

Publicly accessible License 

This dataset is part of an effort to highlight the advantages of incorporating low-temperature (< 150 C) geothermal resource evaluation into the implementation of combined heat and power (CHP), and geothermal direct use (GDU) technologies (e.g., space heating and/or cooling). For this Denver Basin example, resource favorability maps were created to identify potentially favorable areas for further geothermal exploration and are provided here. Favorability was based on three types of data: (1) geologic, (2) economic, and (3) risk. This raw data is also provided below. Geologic data include bottom-hole temperatures (BHT) from oil and gas wells, water co-production volumes from oil and gas wells, well groundwater levels, hot spring locations, temperatures, and chemistries, faults, and earthquakes. Economic feasibility data include population, thermal energy demand, infrastructure, and roads. Risk data (which includes data on excluded areas) include flood plains, protected lands (e.g. wildlife conservation areas, national parks).

The included report describes this project in detail, covering workflows, relevant datasets, Python code, and both common and composite maps used to create low-temperature geothermal resource favorability maps for the Denver Basin, which extends across Colorado, Nebraska, and Wyoming. The figures in this report include: maps of the original datasets; maps of transformed data and derived parameters (such as the geothermal gradient or thermal conductivity); results of uncertainty analyses; results of data completeness (using the GeoRePORT tool); examples of the data combination and processing (using the geoPFA Python library, which is introduced in the attached report); favorability maps for each criteria; and a final combined favorability map. This project is designed to facilitate future deployment of CHP and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources in sedimentary basins.

Citation Formats

National Renewable Energy Laboratory. (2023). Geothermal Play Fairway Analysis for Low-Temperature Resources in the Denver Basin [data set]. Retrieved from https://dx.doi.org/10.15121/2448432.
Export Citation to RIS
Davalos-Elizondo, Estefanny, Taverna, Nicole, Gold, Abra, Menon, Karthik, and Trainor-Guitton, Whitney. Geothermal Play Fairway Analysis for Low-Temperature Resources in the Denver Basin. United States: N.p., 30 Sep, 2023. Web. doi: 10.15121/2448432.
Davalos-Elizondo, Estefanny, Taverna, Nicole, Gold, Abra, Menon, Karthik, & Trainor-Guitton, Whitney. Geothermal Play Fairway Analysis for Low-Temperature Resources in the Denver Basin. United States. https://dx.doi.org/10.15121/2448432
Davalos-Elizondo, Estefanny, Taverna, Nicole, Gold, Abra, Menon, Karthik, and Trainor-Guitton, Whitney. 2023. "Geothermal Play Fairway Analysis for Low-Temperature Resources in the Denver Basin". United States. https://dx.doi.org/10.15121/2448432. https://gdr.openei.org/submissions/1671.
@div{oedi_6205, title = {Geothermal Play Fairway Analysis for Low-Temperature Resources in the Denver Basin}, author = {Davalos-Elizondo, Estefanny, Taverna, Nicole, Gold, Abra, Menon, Karthik, and Trainor-Guitton, Whitney.}, abstractNote = {This dataset is part of an effort to highlight the advantages of incorporating low-temperature (< 150 C) geothermal resource evaluation into the implementation of combined heat and power (CHP), and geothermal direct use (GDU) technologies (e.g., space heating and/or cooling). For this Denver Basin example, resource favorability maps were created to identify potentially favorable areas for further geothermal exploration and are provided here. Favorability was based on three types of data: (1) geologic, (2) economic, and (3) risk. This raw data is also provided below. Geologic data include bottom-hole temperatures (BHT) from oil and gas wells, water co-production volumes from oil and gas wells, well groundwater levels, hot spring locations, temperatures, and chemistries, faults, and earthquakes. Economic feasibility data include population, thermal energy demand, infrastructure, and roads. Risk data (which includes data on excluded areas) include flood plains, protected lands (e.g. wildlife conservation areas, national parks).

The included report describes this project in detail, covering workflows, relevant datasets, Python code, and both common and composite maps used to create low-temperature geothermal resource favorability maps for the Denver Basin, which extends across Colorado, Nebraska, and Wyoming. The figures in this report include: maps of the original datasets; maps of transformed data and derived parameters (such as the geothermal gradient or thermal conductivity); results of uncertainty analyses; results of data completeness (using the GeoRePORT tool); examples of the data combination and processing (using the geoPFA Python library, which is introduced in the attached report); favorability maps for each criteria; and a final combined favorability map. This project is designed to facilitate future deployment of CHP and GDU by providing data, tools, and a workflow applicable to low-temperature geothermal resources in sedimentary basins. }, doi = {10.15121/2448432}, url = {https://gdr.openei.org/submissions/1671}, journal = {}, number = , volume = , place = {United States}, year = {2023}, month = {09}}
https://dx.doi.org/10.15121/2448432

Details

Data from Sep 30, 2023

Last updated Oct 1, 2024

Submitted Sep 27, 2024

Organization

National Renewable Energy Laboratory

Contact

Estefanny Davalos-Elizondo

Authors

Estefanny Davalos-Elizondo

National Renewable Energy Laboratory

Nicole Taverna

National Renewable Energy Laboratory

Abra Gold

National Renewable Energy Laboratory

Karthik Menon

National Renewable Energy Laboratory

Whitney Trainor-Guitton

National Renewable Energy Laboratory

Research Areas

DOE Project Details

Project Name Geothermal Heating and Cooling Geospatial Datasets and Analysis

Project Lead Jeff Winick

Project Number 39678

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