Utah FORGE 6-3629: Machine Learning and Seismology for Real-Time Decision-Making in Stimulation - 2026 Workshop Presentation
This is a presentation on Machine Learning and Seismology for Real-Time Decision-Making in Stimulation by the University of Utah, presented by Dr. No'am Dvory. The project is developing real-time seismic monitoring, machine-learning, and geomechanical risk assessment tools to support decision-making during geothermal stimulation operations at Utah FORGE. This presentation was featured at the Utah FORGE R&D Annual Workshop, held September 30-October 1, 2026. The workshop offered a valuable opportunity to review the progress of Research and Development projects funded under Solicitation 2022-2, which aim to improve our understanding of the key factors influencing Enhanced Geothermal System (EGS) reservoir and resource development.
Citation Formats
TY - DATA
AB - This is a presentation on Machine Learning and Seismology for Real-Time Decision-Making in Stimulation by the University of Utah, presented by Dr. No'am Dvory. The project is developing real-time seismic monitoring, machine-learning, and geomechanical risk assessment tools to support decision-making during geothermal stimulation operations at Utah FORGE. This presentation was featured at the Utah FORGE R&D Annual Workshop, held September 30-October 1, 2026. The workshop offered a valuable opportunity to review the progress of Research and Development projects funded under Solicitation 2022-2, which aim to improve our understanding of the key factors influencing Enhanced Geothermal System (EGS) reservoir and resource development.
AU - Dvory, No'am
DB - Geothermal Data Repository
DP - Open EI | National Laboratory of the Rockies
DO -
KW - geothermal
KW - energy
KW - Utah FORGE
KW - EGS
KW - Machine Learning
KW - Seismology
KW - Seismic Monitoring
KW - Real-Time
KW - 2026 Annual Workshop
KW - reservoir development
KW - machine-learning
KW - geomechanics
KW - risk assessment
KW - decision-making
KW - decision support
KW - traffic light
KW - fault characterization
KW - presentation
KW - report
KW - induced seismicity
KW - geothermal reservoir management
LA - English
DA - 2026/09/30
PY - 2026
PB - University Of Utah
T1 - Utah FORGE 6-3629: Machine Learning and Seismology for Real-Time Decision-Making in Stimulation - 2026 Workshop Presentation
UR - https://gdr.openei.org/submissions/1884
ER -
Dvory, No'am. Utah FORGE 6-3629: Machine Learning and Seismology for Real-Time Decision-Making in Stimulation - 2026 Workshop Presentation. University Of Utah, 30 September, 2026, Geothermal Data Repository. https://gdr.openei.org/submissions/1884.
Dvory, N. (2026). Utah FORGE 6-3629: Machine Learning and Seismology for Real-Time Decision-Making in Stimulation - 2026 Workshop Presentation. [Data set]. Geothermal Data Repository. University Of Utah. https://gdr.openei.org/submissions/1884
Dvory, No'am. Utah FORGE 6-3629: Machine Learning and Seismology for Real-Time Decision-Making in Stimulation - 2026 Workshop Presentation. University Of Utah, September, 30, 2026. Distributed by Geothermal Data Repository. https://gdr.openei.org/submissions/1884
@misc{GDR_Dataset_1884,
title = {Utah FORGE 6-3629: Machine Learning and Seismology for Real-Time Decision-Making in Stimulation - 2026 Workshop Presentation},
author = {Dvory, No'am},
abstractNote = {This is a presentation on Machine Learning and Seismology for Real-Time Decision-Making in Stimulation by the University of Utah, presented by Dr. No'am Dvory. The project is developing real-time seismic monitoring, machine-learning, and geomechanical risk assessment tools to support decision-making during geothermal stimulation operations at Utah FORGE. This presentation was featured at the Utah FORGE R\&D Annual Workshop, held September 30-October 1, 2026. The workshop offered a valuable opportunity to review the progress of Research and Development projects funded under Solicitation 2022-2, which aim to improve our understanding of the key factors influencing Enhanced Geothermal System (EGS) reservoir and resource development.},
url = {https://gdr.openei.org/submissions/1884},
year = {2026},
howpublished = {Geothermal Data Repository, University Of Utah, https://gdr.openei.org/submissions/1884},
note = {Accessed: 2026-11-10}
}
Details
Data from Sep 30, 2026
Last updated Oct 24, 2026
Submitted Oct 20, 2026
Organization
University Of Utah
Contact
No'am Dvory
Authors
Keywords
geothermal, energy, Utah FORGE, EGS, Machine Learning, Seismology, Seismic Monitoring, Real-Time, 2026 Annual Workshop, reservoir development, machine-learning, geomechanics, risk assessment, decision-making, decision support, traffic light, fault characterization, presentation, report, induced seismicity, geothermal reservoir managementDOE Project Details
Project Name Utah FORGE
Project Lead Lauren Boyd
Project Number EE0007080
