An Alternative Model for Gross Characterization Method of AGA8 to Predict Natural Gas Properties

Density correction factor is an important property of natural gas (NG) which is a function of operating conditions and composition of NG. This property is very important as a viewpoint of economic in the gas industry. In this study, an alternative model for AGA8-GCM (Gross Characterization Method) EOS has been presented by Artificial Neural Network modeling called ANN-GCM to predict the density correction factor of NG measured by the instrument of gas volume corrector. Due to low accuracy and limitations of input variables metering used in GCM-EOS, it is tried to provide a simple model with less input variables (temprature, pressure and specific gravity in the base condition) in ANN-GCM model. The results indicated that the ANN-GCM model have the satisfactory agreement with experimental data which not applied to construct the ANN model.

کلیدواژه ها:

Natural Gas ، Density Correction Factor ، Artificial Neural Network ، Gross Characterization Method