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The aim of this paper is to predict the equilibrium water dew point of natural gas in TEG dehydration process using feedforward artificial neural network (FANN). The ANN model shows a good result as the coefficient of determination of 0.9989 and 0.9976 was obtained for training and testing data respectively with relatively small value of mean square errors of 0.0203 and 0.0221. 0.5% of average absolute deviation percentage was observed which is comparable with the literatures. It clearly shows that FANN gives a good prediction on water dew point of natural gas in TEG dehydration process. [ABSTRACT FROM AUTHOR]

The hydrocarbon dew point (HCDP) of natural gas is a key parameter in the gas transportation industry. Predicting and calculating HCDP precisely can ensure the security and reliability of the system. This article begins with an introduction of the methods to predict and measure HCDP and determines a suitable equation of state model to calculate HCDP of natural gas from the West to East-I pipeline. The natural gas composition is analyzed by an on-line gas chromatograph and an extended analysis in the laboratory. Based on the results computed by TPCOMP,1 the influence of natural components to calculate HCDP is discussed, and a modified method to add 0.0002-0.0004% up to the heaviest hydrocarbon is proposed to make the agreement within ±3°C between calculation and measurement. [ABSTRACT FROM AUTHOR]