A Hybrid GP-Fuzzy Approach for Reservoir Characterization

Created by W.Langdon from gp-bibliography.bib Revision:1.8051

@InCollection{TinaYu:2003:GPTP,

• author = "Tina Yu and Dave Wilkinson and Deyi Xie",
• title = "A Hybrid GP-Fuzzy Approach for Reservoir Characterization",
• 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 works.",
• 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

Citations