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        Constructing a unique two-phase compressibility factor model for lean gas condensates

        Mahmood Moayyedi,Arash Azamifard,Aliashghar Gharesheikhlou,Emadoddin Mosaferi 한국화학공학회 2015 Korean Journal of Chemical Engineering Vol.32 No.2

        Generating a reliable experimental model for two-phase compressibility factor in lean gas condensate reservoirshas always been demanding, but it was neglected due to lack of required experimental data. This study presentsthe main results of constructing the first two-phase compressibility factor model that is completely valid for Iranianlean gas condensate reservoirs. Based on a wide range of experimental data bank for Iranian lean gas condensate reservoirs,a unique two-phase compressibility factor model was generated using design of experiments (DOE) method andneural network technique (ANN). Using DOE, a swift cubic response surface model was generated for two-phase compressibilityfactor as a function of some selected fluid parameters for lean gas condensate fluids. The proposed DOEand ANN models were finally validated using four new independent data series. The results showed that there is agood agreement between experimental data and the proposed models. In the end, a detailed comparison was madebetween the results of proposed models.

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