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Utah FORGE 2-2439v2: Reports on Stress Prediction and Modeling for Well 16B(78)-32 - May 2025
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National Renewable Energy Laboratory (NREL) - view all
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Last updated4 days ago
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Overview

These two reports from the University of Pittsburgh document related efforts under Utah FORGE Project 2-2439v2 to estimate in-situ stresses in well 16B(78)-32 using laboratory data, machine learning models, and physics-based simulations. One report focuses on developing and validating stress prediction models using ultrasonic velocity experiments on core samples and applying those models to sonic log data. The other report uses those near-field predictions as input to a thermo-poro-mechanical model to estimate far-field stress profiles under various thermal and pore pressure conditions.

16B16B78-32EGSIn-Situ StressUltrasonic VelocityUtahUtah FORGEdeep learningenergyfar-field stressfinite element modelgeothermalgeothermal reservoirmachine learningmodelingsonic logsstress anisotropystress predictionstress profilingtechnical reportthermo-poro-mechanicaltrue triaxial testing
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KeyValue
Dcat Issued2025-06-05T06:00:00Z
Dcat Modified2025-06-09T19:47:36Z
Dcat Publisher NameUniversity of Pittsburgh
Guidhttps://data.openei.org/submissions/8431
Harvest Object Ide04ffcc8-d3fc-4354-95d1-16f9e430fe32
Harvest Source Id4eb7107f-a2b1-40e3-b36a-8161aa98a56e
Harvest Source TitleOpenEI Data Portal
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