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

Shahab D. Mohaghegh

ISBN 10: 1032151153 / ISBN 13: 9781032151151

Verlag: Taylor & Francis Ltd, 2024

Beschreibung

New copy - Usually dispatched within 4 working days. 453.

Bestandsnummer des Verkäufers B9781032151151

Bibliografische Details

• Titel: Smart Proxy Modeling: Artificial Intelligence and Machine Learning in Numerical Simulation
• Verlag: Taylor & Francis Ltd
• Erscheinungsjahr: 2024
• Sprache: Englisch
• ISBN-10: 1032151153
• ISBN-13: 9781032151151
• Einband: Paperback / softback
• Zustand: New
• Gewicht: 453 Gramm

Über diesen Titel

Inhaltsangabe

Smart proxy models provide an opportunity to replicate numerical simulations with very high accuracy and can be run on a laptop within a few minutes. This book focuses on smart proxy modeling and teaches readers to develop smart proxy models using artificial intelligence and machine learning.

Über die Autorin bzw. den Autor

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).