Machine Learning Application for CCUS and Fracture Analysis

Conference · Wed Jul 31 04:00:00 EDT 2024

DOI:https://doi.org/10.2172/2410848· OSTI ID:2410848

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

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1. NETL
2. NETL Site Support Contractor, National Energy Technology Laboratory

This is an invited guest speaker's presentation. The present covers three use cases by applying machine learning techniques. The use cases include fracture analysis for CCUS: IBDP study, multiple level of fracture network analysis and tool: HFTS1 study, Frac-Hit with Middleland Basin datasets from collaborations with Company A.

• 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), Office of Carbon Management (FE-20)
• OSTI ID: 2410848
• Country of Publication: United States
• Language: English