Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications

Publicly accessible License 

To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group -- a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed-loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and supercritical CO2) while varying seven continuous independent parameters of interest (mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying Python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the techno-economic analysis script are provided.

This data submission will contain results from the Closed Loop Geothermal Working Group study that are within the public domain, including publications, simulation results, databases, and computer codes.

GeoCLUSTER is a Python-based web application created using Dash, an open-source framework built on top of Flask that streamlines the building of data dashboards. GeoCLUSTER provides users with a collection of interactive methods for streamlining the exploration and visualization of an HDF5 dataset. The GeoCluster app and database are contained in the compressed file geocluster_vx.zip, where the "x" refers to the version number. For example, geocluster_v1.zip is Version 1 of the app. This zip file also contains installation instructions.

**To use the GeoCLUSTER app in the cloud, click the link to "GeoCLUSTER on AWS" in the Resources section below. To use the GeoCLUSTER app locally, download the geocluster_vx.zip to your computer and uncompress this file. When uncompressed this file comprises two directories and the geocluster_installation.pdf file. The geo-data app contains the HDF5 database in condensed format, and the GeoCLUSTER directory contains the GeoCLUSTER app in the subdirectory dash_app, as app.py. The geocluster_installation.pdf file provides instructions on installing Python, the needed Python modules, and then executing the app.

Citation Formats

TY - DATA AB - To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group -- a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed-loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and supercritical CO2) while varying seven continuous independent parameters of interest (mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying Python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the techno-economic analysis script are provided. This data submission will contain results from the Closed Loop Geothermal Working Group study that are within the public domain, including publications, simulation results, databases, and computer codes. GeoCLUSTER is a Python-based web application created using Dash, an open-source framework built on top of Flask that streamlines the building of data dashboards. GeoCLUSTER provides users with a collection of interactive methods for streamlining the exploration and visualization of an HDF5 dataset. The GeoCluster app and database are contained in the compressed file geocluster_vx.zip, where the "x" refers to the version number. For example, geocluster_v1.zip is Version 1 of the app. This zip file also contains installation instructions. **To use the GeoCLUSTER app in the cloud, click the link to "GeoCLUSTER on AWS" in the Resources section below. To use the GeoCLUSTER app locally, download the geocluster_vx.zip to your computer and uncompress this file. When uncompressed this file comprises two directories and the geocluster_installation.pdf file. The geo-data app contains the HDF5 database in condensed format, and the GeoCLUSTER directory contains the GeoCLUSTER app in the subdirectory dash_app, as app.py. The geocluster_installation.pdf file provides instructions on installing Python, the needed Python modules, and then executing the app. AU - Beckers, Koenraad A2 - Horne, Roland A3 - Augustine, Chad A4 - Pauley, Laura A5 - Hollett, Doug A6 - Adams, Andy A7 - Blankenship, Doug A8 - Frone, Zach A9 - Porse, Sean A10 - Baek, Seunghwan A11 - Balestra, Paolo A12 - Bernat, Anastasia A13 - Bettin, Giorgia A14 - Bran-Anleu, Gabriela A15 - Kucala, Alec A16 - Kyanjo, Brian A17 - Marshall, Theron A18 - Martinez, Mario A19 - McLing, Travis A20 - Parisi, Carlo A21 - Subia, Sam A22 - Vasyliv, Yaroslav A23 - White, Mark DB - Geothermal Data Repository DP - Open EI | National Renewable Energy Laboratory DO - 10.15121/1972213 KW - geothermal KW - energy KW - closed loop KW - Closed Loop Geothermal Working Group KW - GeoCLUSTER KW - u-shape configuration KW - coaxial configuration KW - water working fluid KW - sCO2 working fluid KW - LCOH KW - LCOE KW - applicaiton KW - hdf5 KW - database KW - installation KW - CLGWG KW - hot-dry rock KW - hdr KW - code KW - python KW - DASH KW - subsurface KW - simulation KW - modeling KW - economic KW - coaxial KW - u-shaped KW - configuration LA - English DA - 2023/02/03 PY - 2023 PB - Pacific Northwest National Laboratory T1 - Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications UR - https://doi.org/10.15121/1972213 ER -
Export Citation to RIS
Beckers, Koenraad, et al. Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications. Pacific Northwest National Laboratory, 3 February, 2023, Geothermal Data Repository. https://doi.org/10.15121/1972213.
Beckers, K., Horne, R., Augustine, C., Pauley, L., Hollett, D., Adams, A., Blankenship, D., Frone, Z., Porse, S., Baek, S., Balestra, P., Bernat, A., Bettin, G., Bran-Anleu, G., Kucala, A., Kyanjo, B., Marshall, T., Martinez, M., McLing, T., Parisi, C., Subia, S., Vasyliv, Y., & White, M. (2023). Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications. [Data set]. Geothermal Data Repository. Pacific Northwest National Laboratory. https://doi.org/10.15121/1972213
Beckers, Koenraad, Roland Horne, Chad Augustine, Laura Pauley, Doug Hollett, Andy Adams, Doug Blankenship, Zach Frone, Sean Porse, Seunghwan Baek, Paolo Balestra, Anastasia Bernat, Giorgia Bettin, Gabriela Bran-Anleu, Alec Kucala, Brian Kyanjo, Theron Marshall, Mario Martinez, Travis McLing, Carlo Parisi, Sam Subia, Yaroslav Vasyliv, and Mark White. Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications. Pacific Northwest National Laboratory, February, 3, 2023. Distributed by Geothermal Data Repository. https://doi.org/10.15121/1972213
@misc{GDR_Dataset_1473, title = {Closed Loop Geothermal Working Group: GeoCLUSTER App, Subsurface Simulation Results, and Publications}, author = {Beckers, Koenraad and Horne, Roland and Augustine, Chad and Pauley, Laura and Hollett, Doug and Adams, Andy and Blankenship, Doug and Frone, Zach and Porse, Sean and Baek, Seunghwan and Balestra, Paolo and Bernat, Anastasia and Bettin, Giorgia and Bran-Anleu, Gabriela and Kucala, Alec and Kyanjo, Brian and Marshall, Theron and Martinez, Mario and McLing, Travis and Parisi, Carlo and Subia, Sam and Vasyliv, Yaroslav and White, Mark}, abstractNote = {To better understand the heat production, electricity generation performance, and economic viability of closed-loop geothermal systems in hot-dry rock, the Closed-Loop Geothermal Working Group -- a consortium of several national labs and academic institutions has tabulated time-dependent numerical solutions and levelized cost results of two popular closed-loop heat exchanger designs (u-tube and co-axial). The heat exchanger designs were evaluated for two working fluids (water and supercritical CO2) while varying seven continuous independent parameters of interest (mass flow rate, vertical depth, horizontal extent, borehole diameter, formation gradient, formation conductivity, and injection temperature). The corresponding numerical solutions (approximately 1.2 million per heat exchanger design) are stored as multi-dimensional HDF5 datasets and can be queried at off-grid points using multi-dimensional linear interpolation. A Python script was developed to query this database and estimate time-dependent electricity generation using an organic Rankine cycle (for water) or direct turbine expansion cycle (for CO2) and perform a cost assessment. This document aims to give an overview of the HDF5 database file and highlights how to read, visualize, and query quantities of interest (e.g., levelized cost of electricity, levelized cost of heat) using the accompanying Python scripts. Details regarding the capital, operation, and maintenance and levelized cost calculation using the techno-economic analysis script are provided.

This data submission will contain results from the Closed Loop Geothermal Working Group study that are within the public domain, including publications, simulation results, databases, and computer codes.

GeoCLUSTER is a Python-based web application created using Dash, an open-source framework built on top of Flask that streamlines the building of data dashboards. GeoCLUSTER provides users with a collection of interactive methods for streamlining the exploration and visualization of an HDF5 dataset. The GeoCluster app and database are contained in the compressed file geocluster_vx.zip, where the "x" refers to the version number. For example, geocluster_v1.zip is Version 1 of the app. This zip file also contains installation instructions.

**To use the GeoCLUSTER app in the cloud, click the link to "GeoCLUSTER on AWS" in the Resources section below. To use the GeoCLUSTER app locally, download the geocluster_vx.zip to your computer and uncompress this file. When uncompressed this file comprises two directories and the geocluster_installation.pdf file. The geo-data app contains the HDF5 database in condensed format, and the GeoCLUSTER directory contains the GeoCLUSTER app in the subdirectory dash_app, as app.py. The geocluster_installation.pdf file provides instructions on installing Python, the needed Python modules, and then executing the app.}, url = {https://gdr.openei.org/submissions/1473}, year = {2023}, howpublished = {Geothermal Data Repository, Pacific Northwest National Laboratory, https://doi.org/10.15121/1972213}, note = {Accessed: 2025-04-23}, doi = {10.15121/1972213} }
https://dx.doi.org/10.15121/1972213

Details

Data from Feb 3, 2023

Last updated May 4, 2023

Submitted Feb 3, 2023

Organization

Pacific Northwest National Laboratory

Contact

Mark White

509.372.6070

Authors

Koenraad Beckers

National Renewable Energy Laboratory

Roland Horne

Stanford University

Chad Augustine

National Renewable Energy Laboratory

Laura Pauley

Pennsylvania State University

Doug Hollett

Melroy-Hollett Technology

Andy Adams

U.S. DOE EERE Geothermal Technologies Office

Doug Blankenship

U.S. DOE EERE Geothermal Technologies Office

Zach Frone

U.S. DOE EERE Geothermal Technologies Office

Sean Porse

U.S. DOE EERE Geothermal Technologies Office

Seunghwan Baek

Pacific Northwest National Laboratory

Paolo Balestra

Idaho National Laboratory

Anastasia Bernat

Pacific Northwest National Laboratory

Giorgia Bettin

Sandia National Laboratories

Gabriela Bran-Anleu

Sandia National Laboratories

Alec Kucala

Sandia National Laboratories

Brian Kyanjo

Boise State University

Theron Marshall

Idaho National Laboratory

Mario Martinez

Sandia National Laboratories

Travis McLing

Idaho National Laboratory

Carlo Parisi

Idaho National Laboratory

Sam Subia

Sandia National Laboratories

Yaroslav Vasyliv

Sandia National Laboratories

Mark White

Pacific Northwest National Laboratory

DOE Project Details

Project Name Closed Loop Geothermal Working Group

Project Lead Zachary Frone

Project Number 37432

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