Bio

David Zhen Yin is the program director and co-founder of Stanford Mineral-X Initiative to lead the research of sustainable critical minerals explorations for renewable energy transitions. He is also a research scientist at Stanford Center for Earth Resources Forecasting and Co-PI of the Stanford-KoBold collaboration. He develops data-scientific approaches for prediction, uncertainty quantification, and decision-making in earth resources exploration and developments (including critical minerals, groundwater, and oil and gas).

David developed broad experience working with complex projects involving academia and industry and broad knowledge of the fields. His research delivered several key technologies transferred as in-house technologies in Chevron, Equinor, and KoBold. In addition, his research developments have been implemented on various subjects, from Antarctica bed topography modeling, critical mineral explorations in Canada/China/US, and the North Sea and Gulf of Mexico projects.

Before joining Stanford, David was a Research Associate at Edinburgh Time-Lapse Project in Scotland, leading a geophysical monitoring research project in collaboration with Equinor from 2016 to 2018. He was also a technology consultant at Equinor's Research Center in Bergen, Norway. Then, he was a Chevron CoRE Postdoctoral Fellow at Stanford from 2018 to 2021.

David received his Ph.D. in Geosciences from Heriot-Watt University, Edinburgh, UK, in 2016. His research interests include data science for geosciences, geological uncertainty quantification, and decision-making under uncertainty. He has authored one book and tens of articles in peer-reviewed journals and international conferences.

Academic Appointments

Administrative Appointments

  • Research Scientist, Stanford University (2022 - Present)
  • Chevron CoRE Postdoctoral Fellow, Stanford University (2018 - 2021)
  • Research Associate, Heriot-Watt University (2016 - 2018)

Honors & Awards

  • Chevron CoRE (Center of Research Excellence) Fellowship, Chevron (2018)
  • Frans and Alice Hammons Award, SEG (2014)

Boards, Advisory Committees, Professional Organizations

  • Co-chair, Stanford Earth Postdoc Advisory Council (2019 - 2022)

Contact

  • Academic
    yinzhen@stanford.edu
    University - Academic staff Department: Department of Geological Sciences Position: Research Scientist
    • 367 PANAMA MALL
    • STANFORD,  California  94305 

Additional Info

Links

All Publications

  • Mapping high-resolution basal topography of West Antarctica from radar data using non-stationary multiple-point geostatistics (MPS-BedMappingV1) GEOSCIENTIFIC MODEL DEVELOPMENT Yin, Z., Zuo, C., MacKie, E. J., Caers, J. 2022; 15 (4): 1477-1497

    View details for DOI 10.5194/gmd-15-1477-2022

    View details for Web of Science ID 000760301100001

  • Quantifying Uncertainty in Downscaling of Seismic Data to High-Resolution 3-D Lithological Models IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING Yin, Z., Amaru, M., Wang, Y., Li, L., Caers, J. 2022; 60

    View details for DOI 10.1109/TGRS.2022.3153934

    View details for Web of Science ID 000779841600020

  • Stochastic modeling of subglacial topography exposes uncertainty in water routing at Jakobshavn Glacier JOURNAL OF GLACIOLOGY MacKie, E. J., Schroeder, D. M., Zuo, C., Yin, Z., Caers, J. 2021; 67 (261): 75–83

    View details for DOI 10.1017/jog.2020.84

    View details for Web of Science ID 000608835500007

  • A Monte Carlo-based framework for risk-return analysis in mineral prospectivity mapping GEOSCIENCE FRONTIERS Wang, Z., Yin, Z., Caers, J., Zuo, R. 2020; 11 (6): 2297–2308

    View details for DOI 10.1016/j.gsf.2020.02.010

    View details for Web of Science ID 000583042200026

  • Automated Monte Carlo-based quantification and updating of geological uncertainty with borehole data (AutoBEL v1.0) GEOSCIENTIFIC MODEL DEVELOPMENT Yin, Z., Strebelle, S., Caers, J. 2020; 13 (2): 651–72

    View details for DOI 10.5194/gmd-13-651-2020

    View details for Web of Science ID 000516580600001

  • A Tree-Based Direct Sampling Method for Stochastic Surface and Subsurface Hydrological Modeling WATER RESOURCES RESEARCH Zuo, C., Yin, Z., Pan, Z., MacKie, E. J., Caers, J. 2020; 56 (2)

    View details for DOI 10.1029/2019WR026130

    View details for Web of Science ID 000535672800045

  • 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

  • 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

  • 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

  • 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

  • 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

https://orcid.org/0000-0001-9215-4426