{"@type": "dcat:Dataset", "DOI": "10.15121/2439748", "accessLevel": "public", "bureauCode": ["019:20"], "contactPoint": {"@type": "vcard:Contact", "fn": "Sean Lattice", "hasEmail": "mailto:slattis@egi.utah.edu"}, "dataQuality": true, "description": "This is a presentation on A Multi-Component Approach to Characterizing In-Situ Stress at the Utah FORGE Site: Laboratory Modelling and Field Measurements project by The University of Pittsburgh, presented by Andrew Bunger. The project characterizes the stress in the Utah FORGE EGS reservoir using three methods: \n\nMethod 1: Demonstrate complimentary laboratory rock-core stress estimation combined with Machine Learning approach for measuring in-situ stress from field sonic log data;\nMethod 2: Complete field based in-situ measurement (mini-frac); and\nMethod 3: Develop a mechanics-based method for connection near wellbore stress measurements to stresses away from the well-bore. \n\nThis presentation was featured in the Utah FORGE R&D Annual Workshop on August 14, 2024. ", "distribution": [{"@type": "dcat:Distribution", "accessURL": "https://gdr.openei.org/files/1640/PITTU%202-2439v2%20GMT20240814-185919_Recording_as_1920x1080.mp4", "description": "As part of the 2024 Utah FORGE R&D Workshop, this presentation offers the newest updates to the A Multi-Component Approach to Characterizing In-Situ Stress at the Utah FORGE Site: Laboratory Modelling and Field Measurements project from The University of Pittsburgh. The presentation follows a standard format, with a 20 minute presentation section followed by a 25 minute Q&A via Utah FORGE panelists and the presenters.", "format": "mp4", "mediaType": "application/octet-stream", "title": "Presentation Recording.mp4"}], "identifier": "https://data.openei.org/submissions/7710", "issued": "2024-09-04T06:00:00Z", "keyword": ["geothermal", "energy", "Utah FORGE", "in-situ stress", "Machine Learning", "Machine Learning for in-situ stress", "sonic logs", "mini-frac", "rock mechanics", "rock stress", "stress", "stress estimation", "video", "presentation"], "landingPage": "https://gdr.openei.org/submissions/1640", "license": "https://creativecommons.org/licenses/by/4.0/", "modified": "2024-09-06T17:37:10Z", "programCode": ["019:006"], "projectLead": "Lauren Boyd", "projectNumber": "EE0007080", "projectTitle": "Utah FORGE", "publisher": {"@type": "org:Organization", "name": "Energy and Geoscience Institute at the University of Utah"}, "spatial": "{\"type\":\"Polygon\",\"coordinates\":[[[-112.916367,38.483935],[-112.879748,38.483935],[-112.879748,38.5148],[-112.916367,38.5148],[-112.916367,38.483935]]]}", "title": "Utah FORGE 2-2439v2: Characterizing In-Situ Stress with Laboratory Modelling and Field Measurements - 2024 Annual Workshop Presentation"}