David Zhen Yin
Senior Research Scientist - Physical
Earth & Planetary Sciences
Bio
David Zhen Yin is the co-founder and program director of Stanford Mineral-X to lead the research of sustainable critical minerals explorations for renewable energy transitions. He is also the principal 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 critical earth resources exploration and development.
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.
Administrative Appointments
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Senior Research Scientist, Stanford University (2024 - Present)
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Co-founder & Program Director, Stanford Mineral-X (2022 - Present)
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Research Scientist, Stanford University (2021 - 2024)
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Chevron CoRE Postdoctoral Fellow, Stanford University (2018 - 2021)
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Research Associate, Heriot-Watt University (2016 - 2018)
Honors & Awards
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Chevron CoRE (Center of Research Excellence) Fellowship, Chevron (2018)
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Frans and Alice Hammons Award, SEG (2014)
Boards, Advisory Committees, Professional Organizations
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Co-chair, Stanford Earth Postdoc Advisory Council (2019 - 2022)
All Publications
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Mapping high-resolution basal topography of West Antarctica from radar data using non-stationary multiple-point geostatistics (MPS-BedMappingV1)
GEOSCIENTIFIC MODEL DEVELOPMENT
2022; 15 (4): 1477-1497
View details for DOI 10.5194/gmd-15-1477-2022
View details for Web of Science ID 000760301100001
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Quantifying Uncertainty in Downscaling of Seismic Data to High-Resolution 3-D Lithological Models
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
2022; 60
View details for DOI 10.1109/TGRS.2022.3153934
View details for Web of Science ID 000779841600020
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Stochastic modeling of subglacial topography exposes uncertainty in water routing at Jakobshavn Glacier
JOURNAL OF GLACIOLOGY
2021; 67 (261): 75–83
View details for DOI 10.1017/jog.2020.84
View details for Web of Science ID 000608835500007
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A Monte Carlo-based framework for risk-return analysis in mineral prospectivity mapping
GEOSCIENCE FRONTIERS
2020; 11 (6): 2297–2308
View details for DOI 10.1016/j.gsf.2020.02.010
View details for Web of Science ID 000583042200026
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Automated Monte Carlo-based quantification and updating of geological uncertainty with borehole data (AutoBEL v1.0)
GEOSCIENTIFIC MODEL DEVELOPMENT
2020; 13 (2): 651–72
View details for DOI 10.5194/gmd-13-651-2020
View details for Web of Science ID 000516580600001
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A Tree-Based Direct Sampling Method for Stochastic Surface and Subsurface Hydrological Modeling
WATER RESOURCES RESEARCH
2020; 56 (2)
View details for DOI 10.1029/2019WR026130
View details for Web of Science ID 000535672800045
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Simulation of hydrogen generation via in-situ combustion gasification of heavy oil
INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
2024; 49: 925-936
View details for DOI 10.1016/j.ijhydene.2023.09.248
View details for Web of Science ID 001134969400001
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Unraveling the uncertainty of geological interfaces through data-knowledge-driven trend surface analysis
COMPUTERS & GEOSCIENCES
2023; 178
View details for DOI 10.1016/j.cageo.2023.105419
View details for Web of Science ID 001047313900001
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GStatSim V1.0: a Python package for geostatistical interpolation and conditional simulation
GEOSCIENTIFIC MODEL DEVELOPMENT
2023; 16 (13): 3765-3783
View details for DOI 10.5194/gmd-16-3765-2023
View details for Web of Science ID 001019979600001
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A nearest neighbor multiple-point statistics method for fast geological modeling
COMPUTERS & GEOSCIENCES
2022; 167
View details for DOI 10.1016/j.cageo.2022.105208
View details for Web of Science ID 000863316600001
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A workflow for building surface-based reservoir models using NURBS curves, coons patches, unstructured tetrahedral meshes and open-source libraries
Computers & Geosciences
2018; 121: 11
View details for DOI 10.1016/j.cageo.2018.09.001
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Evaluation of inter-well connectivity using well fluctuations and 4D seismic data
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
2016; 145: 533–47
View details for DOI 10.1016/j.petrol.2016.06.021
View details for Web of Science ID 000381835600049
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Enhancement of dynamic reservoir interpretation by correlating multiple 4D seismic monitors to well behavior
Interpretation-A Journal of Subsurface Characterization
2015; 3 (2): SP35–SP52
View details for DOI 10.1190/INT-2014-0194.1
View details for Web of Science ID 000364282200035
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A method to update fault transmissibility multipliers in the flow simulation model directly from 4D seismic
JOURNAL OF GEOPHYSICS AND ENGINEERING
2014; 11 (2)
View details for DOI 10.1088/1742-2132/11/2/025006
View details for Web of Science ID 000343006600006
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Joint interpretation of interwell connectivity by integrating 4D seismic with injection and production fluctuations
SPE EUROPEC
2015
View details for DOI 10.2118/174365-MS
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Improving 4D Seismic Interpretation and Seismic History Matching Using the Well2seis Technique
First EAGE Workshop on Practical Reservoir Monitoring
2017
View details for DOI 10.3997/2214-4609.201700035