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Evolving an accurate model based on machine learning approach for prediction of dew-point pressure in gas condensate reservoirs
, Article Chemical Engineering Research and Design ; Vol. 92, issue. 5 , May , 2014 , p. 891-902 ; ISSN: 02638762 ; Shokrollahi, A ; Arabloo, M ; Mahdikhani-Soleymanloo, R ; Masihi, M ; Sharif University of Technology
Abstract
Over the years, accurate prediction of dew-point pressure of gas condensate has been a vital importance in reservoir evaluation. Although various scientists and researchers have proposed correlations for this purpose since 1942, but most of these models fail to provide the desired accuracy in prediction of dew-point pressure. Therefore, further improvement is still needed. The objective of this study is to present an improved artificial neural network (ANN) method to predict dew-point pressures in gas condensate reservoirs. The model was developed and tested using a total set of 562 experimental data point from different gas condensate fluids covering a wide range of variables. After a...