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Lin Ying Hu
Lin Ying Hu
Phone:
(979) 458-8503
Email:
lin.hu@tamu.edu
Office:
Halbouty 316
Address:

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


Degrees:

Ph.D. Geostatistics – Mines Paris Tech, 1988

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

Awards:

2001 Best Paper Award, Mathematical Geosciences

2004 Grand Prix Schlumberger, French Academy of Science


Lin Ying Hu

Professor of the 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.
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