Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation - 2024 Annual Workshop Presentation

Dataset · Sun Sep 15 04:00:00 EDT 2024

DOI:https://doi.org/10.15121/2441432· OSTI ID:2441432

Dvory, No'am Zach ^[1]

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1. Energy and Geoscience Institute at the University of Utah

This is a presentation on the Cutting Edge Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation by the University of Utah, presented by No'am Zach Dvory. This video slide presentation, by the University of Utah, discussed the technical objectives of developing a real-time decision-making platform to enhance seismic monitoring and risk management during stimulation activities. This presentation was featured in the Utah FORGE R&D Annual Workshop on August 15, 2024.

• Research Organization: DOE Geothermal Data Repository; Energy and Geoscience Institute at the University of Utah
• Sponsoring Organization: USDOE Office of Energy Efficiency and Renewable Energy (EERE), Renewable Power Office. Geothermal Technologies Program (EE-4G)
• Contributing Organization: Energy and Geoscience Institute at the University of Utah
• DOE Contract Number: EE0007080
• OSTI ID: 2441432
• Report Number(s): 1652
• Availability: [e-mail]
• Country of Publication: United States
• Language: English

Related Subjects

15 GEOTHERMAL ENERGY
AI
EGS
University of Utah
Utah FORGE
community saftey
data-driven decisions
energy
fracing
geothermal
ground motion
immediate response
improved saftey
infrastructure protection
machine learning
presentation
proactive risk mitigation
seismic
seismic hazards
stimulation
video