Distinguished Lecturer - Maximize Financial Returns from Real-time Downhole Data

When:  Dec 8, 2020 from 11:00 AM to 12:00 PM (ET)
Title: Maximize Financial Returns from Real-time Downhole Data
Speaker: Prof. Xingru Wu,
University of Oklahoma

Time: Tuesday, Dec. 8, 2020, 11:00AM-12:00PM
Location: Zoom Meeting, Please see the registration information below.


Wells equipped with downhole sensors are used worldwide, particularly in frontier development areas such as deepwater offshore, for better production control and to minimize operational surprises. Operators use real-time technology in lieu of traditional production logging because of restrictions or operational costs. A significant amount of data can be collected in a real-time fashion from these sensors. This data is useless if it does not impact decisions in integrated reservoir management.

The key message from this talk is that knowledge obtained from the real-time data enables the optimization of well and reservoir performance through integrated surveillance programs. The surveillance involves capable people, managed processes, and cutting-edge technology balanced with cost and reliability. In addition to classical applications of the real-time data, we focus on how to add values to asset management via discussing the cutting edge processing subtle signals of pressure and temperature data and using tidal transmission functions.


An SPE member since 2000, Dr. Xingru Wu is an associate professor at the University of Oklahoma. His research interests include data analytics, reservoir mechanism modeling, and simulation, deepwater production and surveillance. He has published 80+ papers in journals and conference proceedings in these areas. He worked as a petroleum engineer at BP for 7 years and at CNOOC for 3 years. He obtained his PhD from the University of Texas at Austin in 2006, an MS from the University of Alaska Fairbanks in 2002, a BS from China University of Petroleum (East China) in 1997, all in petroleum engineering.

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United States
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Chang-Yu Hou