Permeability estimation in heterogeneous oil reservoirs by multi-gene genetic programming algorithm

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@Article{Kaydani:2014:JPSE,
  author =       "Hossein Kaydani and Ali Mohebbi and Mehdi Eftekhari",
  title =        "Permeability estimation in heterogeneous oil
                 reservoirs by multi-gene genetic programming
                 algorithm",
  journal =      "Journal of Petroleum Science and Engineering",
  volume =       "123",
  pages =        "201--206",
  year =         "2014",
  note =         "Neural network applications to reservoirs:
                 Physics-based models and data models",
  ISSN =         "0920-4105",
  DOI =          "doi:10.1016/j.petrol.2014.07.035",
  URL =          "http://www.sciencedirect.com/science/article/pii/S0920410514002344",
  abstract =     "Permeability estimation has a significant impact on
                 petroleum fields operation and reservoir management.
                 Different methods were proposed to measure this
                 parameter, which some of them are inaccurate, and some
                 others such as core analysis are cost and time
                 consuming. Intelligent techniques are powerful tools to
                 recognise the possible patterns between input and
                 output spaces, which can be applied to predict
                 reservoir parameters. This study proposed a new
                 approach based on multi-gene genetic programming (MGGP)
                 to predict permeability in one of the heterogeneous oil
                 reservoirs in Iran. The MGGP model with artificial
                 neural networks (ANNs), adaptive neuro-fuzzy inference
                 system (ANFIS) and genetic programming (GP) model were
                 used to predict the permeability and obtained results
                 were compared statistically. The comparison of results
                 showed that the MGGP model can be applied effectively
                 in permeability prediction, which gives low
                 computational time. Furthermore, one equation based on
                 the MGGP model using well log and core experimental
                 data was generated to predict permeability in porous
                 media.",
  keywords =     "genetic algorithms, genetic programming, rock
                 permeability, porous media, core analysis",
}

Genetic Programming entries for Hossein Kaydani Ali Mohebbi Mehdi Eftekhari

Citations