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.
Complete Metadata
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| description | 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. |
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"title": "Presentation Recording.mp4",
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| DOI | 10.15121/2001502 |
| identifier | https://data.openei.org/submissions/7623 |
| issued | 2023-09-08T06:00:00Z |
| keyword |
[
"2023",
"EGS",
"Machine Learning",
"Utah FORGE",
"annual workshop",
"boundary element method",
"deformation rate analysis",
"energy",
"far-field",
"geothermal",
"in-situ stress",
"laboratory experiments",
"mini-frac",
"modeling",
"near-field",
"rock-core stress estimation",
"sleeve frac packer",
"sonic-log data",
"stress characterization"
]
|
| landingPage | https://gdr.openei.org/submissions/1536 |
| license | https://creativecommons.org/licenses/by/4.0/ |
| modified | 2023-09-25T15:48:15Z |
| programCode |
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| projectLead | Lauren Boyd |
| projectNumber | EE0007080 |
| projectTitle | Utah FORGE |
| publisher |
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"name": "Battelle Memorial Institute",
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| title | Utah FORGE 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement - Workshop Presentation |
