He has authored more than 170 technical papers and carried out more than 60 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 machine learning and data mining. He has been honored by the US 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 US Secretary of Energy’s Technical Advisory Committee on Unconventional Resources (2008-2014). He represented the United States in the International Standard Organization (ISO) on Carbon Capture and Storage (2014-2016).
Chapter 4: Data-Driven Technologies
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Published:2017
"Data-Driven Technologies", Data-Driven Reservoir Modeling, Shahab D. Mohaghegh
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Data-driven technologies are a set of new techniques that rely on data rather than our current understanding of the physical phenomena in order to build models, solve problems, and make recommendations and help us make decisions. In the context of reservoir engineering and reservoir modeling, data are also referred to as facts. This is based on the assumption that the measurements made in the field actually represent facts about the reservoir and the state of the fluid flow in it. It is well understood that measurements include noise and that noise, as an integrated part of the collected data, can be handled.
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