David Zhen Yin is the Postdoctoral Researcher working on the Stanford-Chevron Collaboration Project at SCERF. He uses Bayesian Evidential Learning to directly forecast and quantify uncertainty for oil/gas reservoirs at the appraisal stage.
Prior to joining SCERF, David was a Research Associate at Edinburgh Time-Lapse Project at Heriot-Watt Institute of Petroleum Engineering in Scotland, leading a research project in collaboration with Statoil from 2016 to 2018. He developed the “WELL2SEIS” technique that efficiently integrate 4D seismic with reservoir engineering data to improve reservoir models. This technique has been applied to seven North Sea projects, and has become Statoil’s standard in-house technology. During this period, he was also a Reservoir Technology Consultant at Statoil Research Center in Bergen, Norway. David developed broad experience in working with complex projects involving the industry as well as broad knowledge about the fields.
David obtained his PhD in Reservoir Geophysics from Heriot-Watt University, UK, in 2016, and B.Eng (Petroleum Engineering) from China University of Petroleum in 2011. His research interests include Bayesian Evidential Learning, reservoir modelling and updating, uncertainty quantification, time-lapse reservoir monitoring. David has authored more than 10 publications in peer-reviewed journals and international conferences. He was awarded the SEG Frans and Alice Hammons Award in 2014.
Honors & Awards
Frans and Alice Hammons Award, SEG (2014)
Bachelor of Engineering, Univ of Petroleum East China (2011)
Doctor of Philosophy, Heriot-Watt University (2016)