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Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments

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Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates.

This study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. This submission includes a list of papers, data releases, and presentations produced as part of this work.

Citation Formats

TY - DATA AB - Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates. This study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. This submission includes a list of papers, data releases, and presentations produced as part of this work. AU - Mordensky, Stanley P. A2 - Lipor, John J. A3 - DeAngelo, Jacob A4 - Burns, Erick R. A5 - Lindsey, Cary R. DB - Open Energy Data Initiative (OEDI) DP - Open EI | National Renewable Energy Laboratory DO - KW - geothermal KW - energy KW - PFA KW - hydrothermal KW - energy assessment KW - resource assessment KW - retrospective KW - machine learning KW - geoscience KW - western US KW - data-driven KW - bias reduction KW - favorability KW - mapping KW - EGS KW - low temp KW - processed data KW - resource KW - characterization LA - English DA - 2023/02/07 PY - 2023 PB - United States Geological Survey T1 - Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments UR - https://data.openei.org/submissions/7589 ER -
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Mordensky, Stanley P., et al. Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments. United States Geological Survey, 7 February, 2023, GDR. https://gdr.openei.org/submissions/1498.
Mordensky, S., Lipor, J., DeAngelo, J., Burns, E., & Lindsey, C. (2023). Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments. [Data set]. GDR. United States Geological Survey. https://gdr.openei.org/submissions/1498
Mordensky, Stanley P., John J. Lipor, Jacob DeAngelo, Erick R. Burns, and Cary R. Lindsey. Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments. United States Geological Survey, February, 7, 2023. Distributed by GDR. https://gdr.openei.org/submissions/1498
@misc{OEDI_Dataset_7589, title = {Publications and Datasets from Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments}, author = {Mordensky, Stanley P. and Lipor, John J. and DeAngelo, Jacob and Burns, Erick R. and Lindsey, Cary R.}, abstractNote = {Previous moderate- and high-temperature geothermal resource assessments of the western United States utilized data-driven methods and expert decisions to estimate resource favorability. Although expert decisions can add confidence to the modeling process by ensuring reasonable models are employed, expert decisions also introduce human and, thereby, model bias. This bias can present a source of error that reduces the predictive performance of the models and confidence in the resulting resource estimates.

This study aims to develop robust data-driven methods with the goals of reducing bias and improving predictive ability. This submission includes a list of papers, data releases, and presentations produced as part of this work.}, url = {https://gdr.openei.org/submissions/1498}, year = {2023}, howpublished = {GDR, United States Geological Survey, https://gdr.openei.org/submissions/1498}, note = {Accessed: 2025-05-03} }

Details

Data from Feb 7, 2023

Last updated Jul 25, 2023

Submitted May 1, 2023

Organization

United States Geological Survey

Contact

Stanley P. Mordensky

Authors

Stanley P. Mordensky

United States Geological Survey

John J. Lipor

Portland State University

Jacob DeAngelo

United States Geological Survey

Erick R. Burns

United States Geological Survey

Cary R. Lindsey

United States Geological Survey

Research Areas

DOE Project Details

Project Name Play-Fairway Retrospective Analysis with Emphasis on Developing Improved Hydrothermal Energy Assessments

Project Lead Mike Weathers

Project Number 24996

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