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Utah FORGE 2-2439v2: Characterizing In-Situ Stress with Laboratory Modelling and Field Measurements - 2024 Annual Workshop Presentation
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National Renewable Energy Laboratory (NREL) - view all
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Overview

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.

Machine LearningMachine Learning for in-situ stressUtah FORGEenergygeothermalin-situ stressmini-fracpresentationrock mechanicsrock stresssonic logsstressstress estimationvideo
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Dcat Issued2024-09-04T06:00:00Z
Dcat Modified2024-09-06T17:37:10Z
Dcat Publisher NameEnergy and Geoscience Institute at the University of Utah
Guidhttps://data.openei.org/submissions/7710
Harvest Object Ide74937a2-7b5b-4417-a014-c2c1cd3df4c8
Harvest Source Id4eb7107f-a2b1-40e3-b36a-8161aa98a56e
Harvest Source TitleOpenEI Data Portal
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