Bio

David Zhen Yin is the Postdoctoral Researcher working on Stanford-Chevron CoRE Project at SCERF (Stanford Center for Earth Resources Forecasting). He develops Bayesian Evidential Learning for predictions and uncertainty quantification of oil/gas reservoirs.

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)

Professional Education

  • Bachelor of Engineering, Univ of Petroleum East China (2011)
  • Doctor of Philosophy, Heriot-Watt University (2016)

Contact

  • Academic
    yinzhen@stanford.edu
    University - Scholar Department: Department of Geological Sciences Position: Postdoctoral Scholar

Additional Info

  • Mail Code: 2115

All Publications

  • A workflow for building surface-based reservoir models using NURBS curves, coons patches, unstructured tetrahedral meshes and open-source libraries Computers & Geosciences Zhang, Z., Yin, Z., Yan, X. 2018; 121: 11

    View details for DOI 10.1016/j.cageo.2018.09.001

  • Improving 4D Seismic Interpretation and Seismic History Matching Using the Well2seis Technique First EAGE Workshop on Practical Reservoir Monitoring Yin, Z., Ayzenberg, M., MacBeth, C. 2017

    View details for DOI 10.3997/2214-4609.201700035

  • Evaluation of inter-well connectivity using well fluctuations and 4D seismic data JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING Yin, Z., MacBeth, C., Chassagne, R., Vazquez, O. 2016; 145: 533–47

    View details for DOI 10.1016/j.petrol.2016.06.021

    View details for Web of Science ID 000381835600049

  • Enhancement of dynamic reservoir interpretation by correlating multiple 4D seismic monitors to well behavior Interpretation-A Journal of Subsurface Characterization Yin, Z., Ayzenberg, M., MacBeth, C., Feng, T., Chassagne, R. 2015; 3 (2): SP35–SP52

    View details for DOI 10.1190/INT-2014-0194.1

    View details for Web of Science ID 000364282200035

  • Joint interpretation of interwell connectivity by integrating 4D seismic with injection and production fluctuations SPE EUROPEC Yin, Z., MacBeth, C., Chassagne, R. 2015

    View details for DOI 10.2118/174365-MS

  • A method to update fault transmissibility multipliers in the flow simulation model directly from 4D seismic JOURNAL OF GEOPHYSICS AND ENGINEERING Benguigui, A., Yin, Z., MacBeth, C. 2014; 11 (2)

    View details for DOI 10.1088/1742-2132/11/2/025006

    View details for Web of Science ID 000343006600006