A Comparative Survey of Modeling Absorption Tower Using Mixed Amines

In natural gas treatment, the removal of CO2 and H2S in acid gases is a critical concern. There are various purification technologies that can be used for the removal of acid gas impurities. Absorption of acid gas into amines is one preferred method in gas industries. In the past, single amines was used, but recently in order to improve absorption performance, mixed amines with different solubility and reaction rates have been used. In this study, artificial neural network ANN is used as a method to model the absorption tower when uses mixed amines. A specified model which is simple in calculation and good in accuracy was developed. In this model back propagation learning is used and the corresponding parameters have been optimized. Finally, the new method has been compared with conventional mass transfer and equilibrium methods. The obtained results confirmed the simplicity and accuracy of the developed method