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 11: Examples and Case Studies
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Published:2017
"Examples and Case Studies", Data-Driven Reservoir Modeling, Shahab D. Mohaghegh
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Any modeling technology is only as good as its performance in the real world. Furthermore, new reservoir-modeling technologies should not be held to a higher standard than their predecessors. Top-down modeling (TDM) is no exception. A top-down model does not need to prove that it is better than numerical reservoir simulation and modeling. Such a claim has never been made. TDM needs to prove that it is a valid technology that is capable of developing a comprehensive reservoir model that enjoys internal consistency and has the potential to provide useful information (add value) about the field. The fact that TDM can achieve all its objectives in a short period of time and with many fewer dedicated resources (compared with any other reservoir-modeling technology) will demonstrate its value to the industry.
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