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Name  
 TU Xiaolei
Title  
   Professor
Highest Education  
   Ph.D
Subject Categories  
   Geophysics
Phone  
   -
Zip Code  
   100029
Fax  
   86-10-62010846
Email  
   XiaoleiTu[at]mail.iggcas.ac.cn
Office  
   No.19 Beitucheng West Road, Chaoyang District, Beijing, 100029, China

Education and Appointments：

Xiaolei Tu is a Professor at the Institute of Geology and Geophysics, Chinese Academy of Sciences, and a Courtesy Faculty at Oregon State University. His research focuses on multi-physics joint inversion and integrated interpretation in geophysics. He has developed a systematic framework for integrated imaging of seismic, electromagnetic, gravity, and magnetic data, including joint inversion methods based on structural Gramian, minimum joint support, and minimum joint entropy constraints. These techniques have been widely adopted by academic institutions and industry, with successful applications in geohazard assessment, geothermal energy, offshore hydrocarbon exploration, and critical mineral resources. He has contributed to several major international and national research programs and currently serves on the Oregon State University Faculty Senate Research Council and the SEG Research Committee, where he also chaired the Early-Career Subcommittee. He maintains long-term collaborations with universities, government agencies, and industry partners, and actively encourages interdisciplinary and international graduate training.

• 2020-2024 Faculty Research Associate, College of Oceanic and Atmospheric Sciences, Oregon State University
• 2016-2020 Ph.D., Geophysics, University of Utah, USA
• 2012-2015 M.Sc., Geophysics, Institute of Geology and Geophysics, Chinese Academy of Sciences, China
• 2008-2012 B.Eng., Geophysics, Ocean University of China, China

Research Interests：
  1. Integration of multi-physics (i.e., electromagnetics, potential field, and seismic) geophysical data
  2. Development of geophysical electromagnetic modeling, inversion, and data acquisition methods
  3. Geothermal, mining, and environmental applications of geophysical multi-physics solutions
  4. High performance computing in geophysics
Public Services：

Honors：

Supported Projects：
  1. 2025-2027 CNSF grant: Integrated Multi-physical Approach for Deep Earth Resources Prospecting
  2. 2025-2029 National Science and Technology Major Project for Deep Earth Probe and Mineral Resources Exploration
  3. 2024-2025 NSF CRESCENT seed grant: Magnetotelluric Monitoring of Fluid Movements in the Cascadia Margin Mantle Wedge and Crust During Episodic Tremor and Slip Events: A Feasibility Study

Publications：
  1. N. Bennington, A. Schultz, P. Bedrosian, E. Bowles-Martinez, K. Lynn, M. Stelten, X. Tu, C. Thurber, 2025, The Progression of Basaltic-Rhyolitic Melt Storage at Yellowstone Caldera: Nature.
  2. Tu, X., Bowles-Martinez, E.J. and Schultz, A., 2024, Massively parallel modeling of electromagnetic field in conductive media: An MPI-CUDA implementation on Multi-GPU computers: Computers & Geosciences, 192, doi: https://doi.org/10.1016/j.cageo.2024.105710
  3. Taverna, N., Pauling, H., Trainor-Guitton, W., Kolker, A., Mibei, G., Dobson, P., Sonnenthal, E., Tu, X. and Schultz, A., 2024, De-risking superhot EGS development through 3D play fairway analysis: Methodology development and application at Newberry Volcano, Oregon, USA: Geothermics, 118, doi: https://doi.org/10.1016/j.geothermics.2023.102909.
  4. Tu, X., and M. S. Zhdanov, 2022, Joint focusing inversion of marine controlled-source electromagnetic and full tensor gravity gradiometry data: Geophysics, doi: 10.1190/geo2021-0691.1.
  5. Zhdanov, M.S., Tu, X. and Čuma, M., 2022, Cooperative inversion of multiphysics data using joint minimum entropy constraints: Near Surface Geophysics, https://doi.org/10.1002/nsg.12203
  6. Tu, X., and M. S. Zhdanov, 2021, Joint Gramian inversion of geophysical data with different resolution capabilities: case study in Yellowstone: Geophysical Journal International, 226(2), doi: https://doi.org/10.1093/gji/ggab131
  7. Tu, X., and M. S. Zhdanov, 2021, Least square migration of synthetic aperture data for towed streamer electromagnetic survey: IEEE Geoscience and Remote Sensing Letters, 18(1), doi: https://doi.org/10.1109/LGRS.2020.2968862
  8. Tu, X., and M. S. Zhdanov, 2020, Robust optimal synthetic aperture imaging of marine controlled-source electromagnetic data: IEEE Transactions on Geoscience and Remote Sensing, 58(8), doi: https://doi.org/10.1109/TGRS.2020.2966727
  9. Tu, X., and M. S. Zhdanov, 2019, Enhancement and sharpening of migration images for gravity field and its gradients, Pure and Applied Geophysics, 12, doi: https://doi.org/10.1007/s00024-019-02397-9
  10. Zhdanov, M. S., and X. Tu, 2019, Processing and imaging of towed-streamer electromagnetic data with synthetic aperture method, First Break, 37(12), doi: https://doi.org/10.3997/1365-2397.2019041
 
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No. 19, Beitucheng Xilu, Chaoyang District, 100029, Beijing, P.R.China
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