Skip Nav
Lin Ying Hu
Lin Ying Hu
(979) 458-8503
Halbouty 316

Department of Geology and Geophysics
Texas A&M University
3115 TAMU
College Station, Texas 77843-3115


Ph.D. Geostatistics – Mines Paris Tech, 1988

Habilitation Geosciences – Universite Pierre et Marie Curie - Paris VI, 2002


2001 Best Paper Award, Mathematical Geosciences

2004 Grand Prix Schlumberger, French Academy of Science

Lin Ying Hu

Professor of Practice

Research Interests

  • Data Analytics
  • Geostatistics
  • Integrated Reservoir Modeling
  • Geoconsistent History Matching
  • Fractured Reservoirs
  • Unconventional Resources

Selected Publications

  • Hu, L.Y. (2016): On the conceptual variety of training images in multiple-point geostatistics. Presented at the 10th Geostatistics Congress, 5-9 September 2016, Valencia, Spain.
  • Hu, L.Y., Liu, Y., Scheepens, C., Shultz, A.W. and Thompson, R.D. (2014): Multiple-point simulation with an existing reservoir model as training image. Mathematical Geosciences, 46:227–240.
  • Tolstukhin, E., Hu, L.Y. and Sudan, H. (2014): Geologically consistent seismic history matching workflow for Ekofisk chalk reservoir. Paper presented at ECMOR XIV - 14th European Conference on the Mathematics of Oil Recovery, 8 - 11 September 2014, Catania, Sicily, Italy.
  • Hu, L.Y., Allwardt, T. and McLennan, J. (2014): Proxy of fracture flow property for integrated fractured reservoir modelling. Presented at the Gussow Geoscience Conference 2014: Advances in Applied Geomodeling for Petroleum Reservoirs, 22-24 September 2014, Banff, Canada.
  • Hu, L.Y., Zhao, Y., Liu, Y., Scheepens, C. and Bouchard, A. (2013): Updating multipoint simulations using ensemble Kalman filter. Computers & Geosciences, 51:7-15.
  • Hu, L.Y. and Chugunova, T. (2008): Multiple-point geostatistics for modeling subsurface heterogeneity – a Comprehensive review. Water Resources Research, Vol.44, W11413.
  • Chugunova, T. and Hu, L.Y. (2008): Multiple-point simulations constrained to continuous auxiliary data. Mathematical Geosciences, 40, No.2
  • Jenni, S., Hu, L.Y., Basquet, R., de Marsily, G. and Bourbiaux, B. (2007): History matching of stochastic models of field-scale fractures: methodology and case study. Oil & Gaz Science and Technology, Vol.62, No.2.
  • Hu, L.Y. and Jenni, S. (2005): History matching of object-based stochastic reservoir models. SPE Journal, Vol.10, No.3.
  • Bourbiaux, B., Basquet, R., Daniel, J.M., Hu, L.Y., Jenni, S., Lange, A. and Rasolofosaon, P. (2005): Fractured reservoirs modelling: a review of the challenges and some recent solutions. First Break, 23, September 2005.
  • Hu, L.Y. and Le Ravalec-Dupin, M. (2004): Elements for an integrated geostatistical modeling of heterogeneous reservoir. Oil & Gaz Science and Technology, Vol.59, No.2.
  • Hu, L.Y. and Le Ravalec-Dupin, M. (2004): An improved gradual deformation method for reconciling random and gradient searches in stochastic optimizations. Mathematical Geology,36, No.6.
  • Hu, L.Y., Blanc, G. and Noetinger, B. (2001): Gradual deformation and iterative calibration of sequential stochastic simulations. Mathematical Geology,33, No.4.
  • Hu, L.Y. (2000): Gradual deformation and iterative calibration of Gaussian-related stochastic models. Mathematical Geology, Vol.32, No.1.
  • Hu, L.Y., Blanc, G. and Noetinger, B. (1998): Estimation of lithofacies proportions by use of well and well-test data. SPE Reservoir Evaluation & Engineering, Vol.1, No.1.
  • Moulière, D., Beucher, H., Hu, L.Y., Fournier, F., Terdich, P., Melchiori, F. and Griffi, G. (1997): Integration of seismic derived information in reservoir stochastic modelling using truncated Gaussian approach. in E.Y. Baafi and N.A. Schofield (eds.), “Geostaistics Wollongong ’96”, Vol.1, Kluwer Academic Pub., Dordrecht.
  • Hu, L.Y., Joseph, P., and Dubrule, O. (1994): Random genetic simulation of the internal geometry of deltaic sand bodies. SPE Formation Evaluation, December 1994.
  • Hu, L.Y. et Lantuéjoul, C. (1988): Recherche d’une fonction d’anamorphose pour la mise en œuvre du krigeage disjonctif isofactoriel gamma. Science de la Terre, Série Informatique Géologique, N.28.
Geosciences TAMU Logo

Aggies can change the world. Geoscientists lead the way.