Data-Driven Analytics for the Geological Storage of CO2

Shahab Mohaghegh

ISBN 10: 0367734389 / ISBN 13: 9780367734381

Edité par Taylor & Francis Ltd Dez 2020, 2020

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Neuware.

N° de réf. du vendeur 9780367734381

Détails bibliographiques

• Titre: Data-Driven Analytics for the Geological Storage of CO2
• Éditeur: Taylor & Francis Ltd Dez 2020
• Date de parution: 2020
• Langue: anglais
• ISBN à 10 chiffres: 0367734389
• ISBN à 13 chiffres: 9780367734381
• Reliure: Taschenbuch
• État de l'article: Neu
• Dimensions: 234 L x 156 H x 0 P (en millimètres) 234 millimètres de largeur par 156 millimètres de hauteur par 0 millimètres de profondeur
• Poids: 453 grammes

A propos de ce titre

Synopsis

Data-driven analytics is enjoying unprecedented popularity among oil and gas professionals. Many reservoir engineering problems associated with geological storage of CO2 require the development of numerical reservoir simulation models. This book is the first to examine the contribution of artificial intelligence and machine learning in data-driven analytics of fluid flow in porous environments, including saline aquifers and depleted gas and oil reservoirs. Drawing from actual case studies, this book demonstrates how smart proxy models can be developed for complex numerical reservoir simulation models. Smart proxy incorporates pattern recognition capabilities of artificial intelligence and machine learning to build smart models that learn the intricacies of physical, mechanical and chemical interactions using precise numerical simulations. This ground breaking technology makes it possible and practical to use high fidelity, complex numerical reservoir simulation models in the design, analysis and optimization of carbon storage in geological formations projects.

À propos de l?auteur

Shahab D. Mohaghegh, a pioneer in the application of Artificial Intelligence and Data Mining in the Exploration and Production industry, is the president and CEO of Intelligent Solutions, Inc. (ISI) and Professor of Petroleum and Natural Gas Engineering at West Virginia University. He holds B.S., MS, and PhD degrees in petroleum and natural gas engineering.

He has authored more than 150 technical papers and carried out more than 50 projects for NOCs and IOCs. He is a SPE Distinguished Lecturer and has been featured in the Distinguished Author Series of SPE's Journal of Petroleum Technology (JPT) four times. He is the founder of Petroleum Data-Driven Analytics, SPE's Technical Section dedicated to data mining. He has been honoured by the U.S. Secretary of Energy for his technical contribution in the aftermath of the Deepwater Horizon (Macondo) incident in the Gulf of Mexico and was a member of the U.S. Secretary of Energy's Technical Advisory Committee on Unconventional Resources (2008-2014). He represents the United States in the International Standard Organization (ISO) on Carbon Capture and Storage.