Smart Proxy Modeling: Artificial Intelligence and Machine Learning in Numerical Simulation

Author:   Shahab D. Mohaghegh
Publisher:   Taylor & Francis Ltd
ISBN:  

9781032151144


Pages:   190
Publication Date:   27 October 2022
Format:   Hardback
Availability:   In Print   Availability explained
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Smart Proxy Modeling: Artificial Intelligence and Machine Learning in Numerical Simulation


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Author:   Shahab D. Mohaghegh
Publisher:   Taylor & Francis Ltd
Imprint:   CRC Press
Weight:   0.400kg
ISBN:  

9781032151144


ISBN 10:   1032151145
Pages:   190
Publication Date:   27 October 2022
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

1. Artificial Intelligence and Machine Learning. 2. Numerical simulation and modeling. 3. Proxy modeling. 4. Smart Proxy Modeling for numerical reservoir simulation. 5. Smart Proxy Modeling for computational fluid dynamics (CFD).

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Author Information

Shahab D. Mohaghegh, a pioneer in the application of Artificial Intelligence and Machine Learning in the Exploration and Production industry, is Professor of Petroleum and Natural Gas Engineering at West Virginia University (WVU) and the president and CEO of Intelligent Solutions, Inc. (ISI). He is the director of WVU-LEADS (Laboratory for Engineering Application of Data Science). Including more than 30 years of research and development in the petroleum engineering application of Artificial Intelligence and Machine Learning, he has authored three books (Shale Analytics – Data Driven Reservoir Modeling – Application of Data-Driven Analytics for the Geological Storage of CO2), more than 230 technical papers and carried out more than 60 projects for independents, NOCs and IOCs. He is a SPE Distinguished Lecturer (2007 and 2020) and has been featured four times as the Distinguished Author in SPE’s Journal of Petroleum Technology (JPT 2000 and 2005). He is the founder of SPE’s Technical Section dedicated to AI and machine learning (Petroleum Data-Driven Analytics, 2011). He has been honored by the U.S. Secretary of Energy for his AI-based technical contribution in the aftermath of the Deepwater Horizon (Macondo) incident in the Gulf of Mexico (2011) and was a member of U.S. Secretary of Energy’s Technical Advisory Committee on Unconventional Resources in two administrations (2008-2014). He represented the United States in the International Standard Organization (ISO) on Carbon Capture and Storage technical committee (2014-2016).

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