Utah FORGE 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement - Workshop Presentation
This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the U.S DOE FORGE EGS Site: Laboratory, Modeling and Field Measurement project by Battelle [Columbus, OH], presented by Mark Kelley. The project's objective was to characterize stress in the Utah FORGE EGS reservoir using three methods: a laboratory rock-core stress estimation combined with a Machine Learning approach for estimation of in-situ stress from field sonic-log data, a field based in-situ measurement (min-frac) approach, and a modeling approach. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 7, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.
Citation Formats
TY - DATA
AB - This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the U.S DOE FORGE EGS Site: Laboratory, Modeling and Field Measurement project by Battelle [Columbus, OH], presented by Mark Kelley. The project's objective was to characterize stress in the Utah FORGE EGS reservoir using three methods: a laboratory rock-core stress estimation combined with a Machine Learning approach for estimation of in-situ stress from field sonic-log data, a field based in-situ measurement (min-frac) approach, and a modeling approach. This presentation was featured in the Utah FORGE R&D Annual Workshop on September 7, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.
AU - Kelley, Mark
A2 - Bunger, Andrew
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO - 10.15121/2001502
KW - geothermal
KW - energy
KW - annual workshop
KW - 2023
KW - Utah FORGE
KW - EGS
KW - Machine Learning
KW - in-situ stress
KW - stress characterization
KW - mini-frac
KW - rock-core stress estimation
KW - sonic-log data
KW - modeling
KW - laboratory experiments
KW - deformation rate analysis
KW - boundary element method
KW - sleeve frac packer
KW - far-field
KW - near-field
LA - English
DA - 2023/09/08
PY - 2023
PB - Battelle Memorial Institute
T1 - Utah FORGE 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement - Workshop Presentation
UR - https://doi.org/10.15121/2001502
ER -
Kelley, Mark, and Andrew Bunger. Utah FORGE 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement - Workshop Presentation. Battelle Memorial Institute, 8 September, 2023, GDR. https://doi.org/10.15121/2001502.
Kelley, M., & Bunger, A. (2023). Utah FORGE 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement - Workshop Presentation. [Data set]. GDR. Battelle Memorial Institute. https://doi.org/10.15121/2001502
Kelley, Mark and Andrew Bunger. Utah FORGE 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement - Workshop Presentation. Battelle Memorial Institute, September, 8, 2023. Distributed by GDR. https://doi.org/10.15121/2001502
@misc{OEDI_Dataset_7623,
title = {Utah FORGE 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement - Workshop Presentation},
author = {Kelley, Mark and Bunger, Andrew},
abstractNote = {This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the U.S DOE FORGE EGS Site: Laboratory, Modeling and Field Measurement project by Battelle [Columbus, OH], presented by Mark Kelley. The project's objective was to characterize stress in the Utah FORGE EGS reservoir using three methods: a laboratory rock-core stress estimation combined with a Machine Learning approach for estimation of in-situ stress from field sonic-log data, a field based in-situ measurement (min-frac) approach, and a modeling approach. This presentation was featured in the Utah FORGE R\&D Annual Workshop on September 7, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.},
url = {https://gdr.openei.org/submissions/1536},
year = {2023},
howpublished = {GDR, Battelle Memorial Institute, https://doi.org/10.15121/2001502},
note = {Accessed: 2025-05-02},
doi = {10.15121/2001502}
}
https://dx.doi.org/10.15121/2001502
Details
Data from Sep 8, 2023
Last updated Sep 25, 2023
Submitted Sep 15, 2023
Organization
Battelle Memorial Institute
Contact
Sean Lattis
Authors
Original Source
https://gdr.openei.org/submissions/1536Research Areas
Keywords
geothermal, energy, annual workshop, 2023, Utah FORGE, EGS, Machine Learning, in-situ stress, stress characterization, mini-frac, rock-core stress estimation, sonic-log data, modeling, laboratory experiments, deformation rate analysis, boundary element method, sleeve frac packer, far-field, near-fieldDOE Project Details
Project Name Utah FORGE
Project Lead Lauren Boyd
Project Number EE0007080
