Machine Learning Application for Fracture Analysis: Use Case

Conference · Tue Oct 01 04:00:00 EDT 2024

DOI:https://doi.org/10.2172/2484041· OSTI ID:2484041

Liu, Guoxiang ^[1]; Kumar, Abhash ^[2]; Harbert, William ^[3]; Siriwardane, Hema ^[1]; Myshakin, Evgeniy ^[2]; Crandall, Dustin ^[1]; Cunha, Luciane ^[1]

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1. NETL
2. NETL Site Support Contractor, National Energy Technology Laboratory
3. Oak Ridge Institute for Science and Education (ORISE)

This is an invited talk for Alberta Energy Regulator, Canada, for machine learning applications for CCS, unconventional hydrocarbon, and frac-hit identification based on NETL recent activities (Virtual, October 1, 2024).

• Research Organization: National Energy Technology Laboratory (NETL), Pittsburgh, PA, Morgantown, WV, and Albany, OR (United States)
• Sponsoring Organization: USDOE Office of Fossil Energy and Carbon Management (FECM); USDOE Office of Fossil Energy and Carbon Management (FECM), Office of Carbon Management (FE-20)
• OSTI ID: 2484041
• Country of Publication: United States
• Language: English