Data-driven Analytics for the Geological Storage of Co2

Data-driven analytics is enjoying unprecedented popularity among oil and gas professionals. A large number of reservoir engineering problems associated with geological storage of CO2 require development of numerical reservoir simulation models. The numerical models are used to understand the impact of injection of CO2 in saline aquifers, depleted oil and gas reservoirs, as well as CO2-EOR projects. This book discusses application of data-driven analytics to geological storage of CO2. It explains the technology that allows for uncertainty quantification and optimization of CO2 storage projects. It also deals with actual case studies from Australia and the United States.

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.