Genetic Programming in Geostatistical Reservoir Geophysics

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Azevedo:2016:CSCI,
  author =       "Leonardo Azevedo and Ruben Nunes and Amilcar Soares",
  booktitle =    "2016 International Conference on Computational Science
                 and Computational Intelligence (CSCI)",
  title =        "Genetic Programming in Geostatistical Reservoir
                 Geophysics",
  year =         "2016",
  pages =        "1208--1213",
  abstract =     "Hydrocarbon reservoir modelling and characterisation
                 is a critical step for the success of oil and/or gas
                 exploration and production projects. Reservoir
                 modelling is frequently based on the results provided
                 by geostatistical seismic inversion techniques. These
                 procedures are computationally heavy and expensive even
                 for small-to-medium size fields due to the use of
                 stochastic sequential simulation as the model
                 perturbation technique. This work proposes the use of
                 machine learning techniques, specifically symbolic
                 regression, a category from the group of genetic
                 programming methodologies, as a proxy to surpass the
                 need of stochastic sequential simulation without
                 compromising the advantage of using these simulation
                 methodologies, for example uncertainty assessment of
                 the property of interest. The proposed methodology is
                 illustrated with an application example to a real case
                 study and the results compared with the traditional
                 geostatistical seismic inversion approach.",
  keywords =     "genetic algorithms, genetic programming, Computational
                 modelling, Correlation coefficient, Data models,
                 Iterative methods, Mathematical model, Reflection,
                 Stochastic processes, genetic programming
                 geostatistical seismic inversion seismic reservoir
                 characterisation",
  DOI =          "doi:10.1109/CSCI.2016.0228",
  month =        dec,
  notes =        "Also known as \cite{7881521}",
}

Genetic Programming entries for Leonardo Azevedo Ruben Nunes Amilcar Soares

Citations