A Hybrid GP-Fuzzy Approach for Reservoir Characterization

Created by W.Langdon from gp-bibliography.bib Revision:1.4420

  author =       "Tina Yu and Dave Wilkinson and Deyi Xie",
  title =        "A Hybrid GP-Fuzzy Approach for Reservoir
  booktitle =    "Genetic Programming Theory and Practice",
  publisher =    "Kluwer",
  year =         "2003",
  editor =       "Rick L. Riolo and Bill Worzel",
  chapter =      "17",
  pages =        "271--289",
  keywords =     "genetic algorithms, genetic programming, Oil
                 Exploration and Production, Reservoir Characterisation,
                 Soft Computing, Permeability Estimation, Fuzzy Logic,
                 Fuzzy Modelling.",
  ISBN =         "1-4020-7581-2",
  URL =          "http://www.cs.mun.ca/~tinayu/Publications_files/gptp2003.pdf",
  URL =          "http://www.springer.com/computer/ai/book/978-1-4020-7581-0",
  DOI =          "doi:10.1007/978-1-4419-8983-3_17",
  abstract =     "A hybrid GP-fuzzy approach to model reservoir
                 permeability is presented. This approach uses a
                 two-step divide-and-conquer process for modelling.
                 First, GP is applied to construct classifiers that
                 identify permeability ranges. Within each range, ANFIS
                 is employed to build a Takagi-Sugeno-Kang fuzzy
                 inference system that gives permeability estimation. We
                 applied this method to five well log data sets. The
                 results show that this hybrid system gives more
                 accurate permeability estimation than other previous
  notes =        "ChevronTexaco Information Technology Company and
                 ChevronTexaco Exploration and Production Technology
                 Company. Part of \cite{RioloWorzel:2003}",
  size =         "19 pages",

Genetic Programming entries for Tina Yu Dave Wilkinson Deyi Xie