Hongfeng Fang

PhD Researcher (2023 – present)

Institute of Earth Surface Dynamics (IDYST) | University of Lausanne

School of Future Technology | China University of Geosciences (Wuhan)

About Me

I am a PhD candidate in Geological Resources and Geological Engineering at China University of Geosciences (Wuhan), and currently undertaking a one-year visiting research stay at the University of Lausanne. My research interests focus on 3D geological modelling, especially the development of multiple-point geostatistics (MPS) algorithms for reliable geostatistical simulation under non-stationary and heterogeneous conditions. Furthermore, I work on practical applications of MPS for subsurface characterisation, with a particular focus on hydrocarbon reservoirs. I am also interested in AI-based geological modelling.

hongfeng fang
hongfeng fang

Educational Background

  • 2026.11 – Present | Visiting PhD, IDYST, University of Lausanne (UNIL)
  • 2023.09 – 2026.10 | Ph.D. Candidate, School of Future Technology, China University of Geosciences (Wuhan) Major: Geological Resources and Geological Engineering
  • 2020.09 – 2023.06 | Master of Engineering, School of Computer Science, China University of Geosciences (Wuhan) Major: Geoinformatics Engineering
  • 2016.09 – 2020.06 | Bachelor of Engineering, School of Computer Science, China University of Geosciences (Wuhan) Major: Spatial Information and Digital Technology

Publications & Patents

  • Fang, H., Liu, G., Cui, Z., Ma, X., Xiong, J., & Chen, Q. (2026). Three-Dimensional Stratigraphic Modeling via Adaptive Search Strategy-Based Multiple-Point Geostatistical Simulation. Mathematical Geosciences, 1-33.
  • Liu, G., Fang, H., Chen, Q., Cui, Z., & Zeng, M. (2022). A Feature-Enhanced MPS Approach to Reconstruct 3D Deposit Models Using 2D Geological Cross Sections: A Case Study in the Luodang Cu Deposit, Southwestern China. Natural Resources Research, 31(6), 3101-3120.
  • ChenQ.,FangH., Liu G. A 3Dstratigraphic modeling method based on adaptive-search MPS simulation. NO. CN120431279A. Patent, Granted.