Geo Thermal Cloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources | Zendy

Velimir V. Vesselinov | Zendy; Daniel O’Malley | Zendy; Luke Frash | Zendy; Bulbul Ahmmed | Zendy; Adam Rupe | Zendy; Satish Karra | Zendy; Richard S. Middleton | Zendy; Boian S. Alexandrov | Zendy; Maruti Kumar Mudunuru | Zendy; Mark M. Mims | Zendy; Kevin W. Jameson | Zendy; Alex Sun | Zendy; Bridget R. Scanlon | Zendy; Amy Banerji | Zendy; Daniel M. Tartakovsky | Zendy; Roland N. Horne | Zendy; Zitong Zhou | Zendy; Conor Maguire | Zendy; Sam Skillman | Zendy; J.E. Scharer | Zendy

Open Access

Geo Thermal Cloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration, and Development of Hidden Geothermal Resources

Author(s) -

Velimir V. Vesselinov,

Daniel O’Malley,

Luke Frash,

Bulbul Ahmmed,

Adam Rupe,

Satish Karra,

Richard S. Middleton,

Boian S. Alexandrov,

Maruti Kumar Mudunuru,

Mark M. Mims,

Kevin W. Jameson,

Alex Sun,

Bridget R. Scanlon,

Amy Banerji,

Daniel M. Tartakovsky,

Roland N. Horne,

Zitong Zhou,

Conor Maguire,

Sam Skillman,

J.E. Scharer

Publication year - 2021

Publication title -

osti oai (u.s. department of energy office of scientific and technical information)

Language(s) - English

Resource type - Reports

DOI - 10.2172/1782607

Subject(s) - geothermal gradient , cloud computing , geothermal exploration , leverage (statistics) , martian , data science , computer science , earth science , field (mathematics) , data mining , environmental science , geothermal energy , machine learning , geology , mars exploration program , geophysics , physics , mathematics , pure mathematics , astronomy , operating system

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