Utah FORGE 2-2439: A Multi-Component Approach to Characterizing In-Situ Stress: Laboratory, Modeling and Field Measurement - Workshop Presentation
- Battelle Memorial Institute
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.
- Research Organization:
- DOE Geothermal Data Repository; Battelle Memorial Institute
- Sponsoring Organization:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Program (EE-4G)
- Contributing Organization:
- Battelle Memorial Institute
- DOE Contract Number:
- EE0007080
- OSTI ID:
- 2001502
- Report Number(s):
- 1536
- Availability:
- GDRHelp@ee.doe.gov
- Country of Publication:
- United States
- Language:
- English
Similar Records
Utah FORGE 2-2404: Application of Advanced Techniques for Determination of Reservoir-Scale Stress State at Utah FORGE - Workshop Presentation
Utah FORGE 2-2446: Closing the Loop Between In-situ Stress Complexity and EGS Fracture Complexity - Workshop Presentation
Related Subjects
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