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Whitney Trainor-Guitton is a quantitative geoscientist with a demonstrated history of working in the subsurface and remote-sensing research and development and higher education. Whitney is experienced in blending data science, spatial statistics and geophysical inversion, and specializes in geostatistics, geophysics, geothermal exploration, carbon dioxide sequestration monitoring, inverse problems, and deep learning. She earned her doctorate focused on earth, energy and environmental sciences from Stanford University. She has also served as a staff scientist at Lawrence Livermore National Laboratory and assistant professor at the Colorado School of Mines doing research and development in statistical learning applied to distributed acoustic sensing, angle versus offset seismic data and screen out pressure data. Currently, Whitney is advancing play fairways analysis for discovery of hidden geothermal systems, using value of information and spatial statistics. 

Research Interests

Value of information methodologies

Stochastic techniques and geostatistical modeling of geophysical data

Distributed acoustic sensing

Integration of data of diverse scales

Uncertainty quantification

Subsurface flow modeling

Carbon sequestration monitoring

Geothermal exploration

Professional Experience

Affiliate Faculty, Colorado School of Mines (2023–present)

Geoscience Researcher, NREL (2022–present)

Team Member, INGENIOUS Project (2021–present)

Senior Decision Scientist, Zanskar Geothermal & Minerals (2021–2022)

Geophysicist, SeaOwl Energy (2020–2021)

Assistant Professor, Colorado School of Mines (2015–2019)

Postdoctoral Research Fellow, Lawrence Livermore National Laboratory (2010–2014)

Staff Scientist, Lawrence Livermore National Laboratory (2010–2011)

Risk Analyst, Risk Management Solutions (2010- 2011)

Education/Academic Qualification

Bachelor, Geophysical Engineering, Colorado School of Mines

PhD, Earth, Energy & Environmental Science, Stanford University

Master, Geophysics, Stanford University


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