Utah FORGE 2-2439v2: Characterizing In-Situ Stress with Laboratory Modelling and Field Measurements - 2024 Annual Workshop Presentation

Description

This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the Utah FORGE Site: Laboratory Modelling and Field Measurements project by The University of Pittsburgh, presented by Andrew Bunger. The project characterizes the stress in the Utah FORGE EGS reservoir using three methods: Method 1: Demonstrate complimentary laboratory rock-core stress estimation combined with Machine Learning approach for measuring in-situ stress from field sonic log data; Method 2: Complete field based in-situ measurement (mini-frac); and Method 3: Develop a mechanics-based method for connection near wellbore stress measurements to stresses away from the well-bore. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 14, 2024.

Resources

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77 As part of the 2024 Utah FORGE R&D Workshop, this presentation offers the newest updates to the A Multi-Component Approach to Characterizing In-Situ Stress at the Utah FORGE Site: Laboratory Modelling and Field Measurements project from The University of Pittsburgh. The presentation follows a standard format, with a 20 minute presentation section followed by a 25 minute Q&A via Utah FORGE panelists and the presenters. https://gdr.openei.org/files/1640/PITTU%202-2439v2%20GMT20240814-185919_Recording_as_1920x1080.mp4

Tags

  • mini-frac
  • utah-forge
  • rock-stress
  • sonic-logs
  • stress-estimation
  • presentation
  • in-situ-stress
  • stress
  • machine-learning-for-in-situ-stress
  • video
  • machine-learning
  • geothermal
  • rock-mechanics
  • energy

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