Utah FORGE 6-3629: Application of Machine Learning, Geomechanics, and Seismology for Real-Time Decision Making Tools During Stimulation - 2024 Annual Workshop Presentation
L o a d i n g
Organization
National Renewable Energy Laboratory (NREL) - view all
Update frequencyunknown
Last updated4 days ago
Format
OverviewAIEGSUniversity of UtahUtah FORGEcommunity safteydata-driven decisionsenergyfracinggeothermalground motionimmediate responseimproved safteyinfrastructure protectionmachine learningpresentationproactive risk mitigationseismicseismic hazardsstimulationvideo
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.
Additional Information
KeyValue
Dcat Issued2024-09-15T06:00:00Z
Dcat Modified2024-09-17T15:57:44Z
Dcat Publisher NameEnergy and Geoscience Institute at the University of Utah
Guidhttps://data.openei.org/submissions/7722
Harvest Object Idd5adeafb-9e0b-44e2-ad5d-d5616b56c9a2
Harvest Source Id4eb7107f-a2b1-40e3-b36a-8161aa98a56e
Harvest Source TitleOpenEI Data Portal