Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation - 2024 Annual Workshop Presentation
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.
Citation Formats
TY - DATA
AB - 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.
AU - Dvory, No'am Zach
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO - 10.15121/2441432
KW - geothermal
KW - energy
KW - Utah FORGE
KW - University of Utah
KW - seismic
KW - AI
KW - machine learning
KW - data-driven decisions
KW - community saftey
KW - infrastructure protection
KW - proactive risk mitigation
KW - improved saftey
KW - immediate response
KW - stimulation
KW - fracing
KW - ground motion
KW - seismic hazards
KW - EGS
KW - video
KW - presentation
LA - English
DA - 2024/09/15
PY - 2024
PB - Energy and Geoscience Institute at the University of Utah
T1 - Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation - 2024 Annual Workshop Presentation
UR - https://doi.org/10.15121/2441432
ER -
Dvory, No'am Zach. Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation - 2024 Annual Workshop Presentation. Energy and Geoscience Institute at the University of Utah, 15 September, 2024, GDR. https://doi.org/10.15121/2441432.
Dvory, N. (2024). Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation - 2024 Annual Workshop Presentation. [Data set]. GDR. Energy and Geoscience Institute at the University of Utah. https://doi.org/10.15121/2441432
Dvory, No'am Zach. Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation - 2024 Annual Workshop Presentation. Energy and Geoscience Institute at the University of Utah, September, 15, 2024. Distributed by GDR. https://doi.org/10.15121/2441432
@misc{OEDI_Dataset_7722,
title = {Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation - 2024 Annual Workshop Presentation},
author = {Dvory, No'am Zach},
abstractNote = {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. },
url = {https://gdr.openei.org/submissions/1652},
year = {2024},
howpublished = {GDR, Energy and Geoscience Institute at the University of Utah, https://doi.org/10.15121/2441432},
note = {Accessed: 2025-05-24},
doi = {10.15121/2441432}
}
https://dx.doi.org/10.15121/2441432
Details
Data from Sep 15, 2024
Last updated Sep 17, 2024
Submitted Sep 15, 2024
Organization
Energy and Geoscience Institute at the University of Utah
Contact
Sean Lattice
801.581.3547
Authors
Original Source
https://gdr.openei.org/submissions/1652Research Areas
Keywords
geothermal, energy, Utah FORGE, University of Utah, seismic, AI, machine learning, data-driven decisions, community saftey, infrastructure protection, proactive risk mitigation, improved saftey, immediate response, stimulation, fracing, ground motion, seismic hazards, EGS, video, presentationDOE Project Details
Project Name Utah FORGE
Project Lead Lauren Boyd
Project Number EE0007080
