Soft Sensor applied to Natural Gas Process Units
NGPU, LPG, Soft Sensor, Artificial Neural Network
In NGPU (Natural Gas Processing Units), one of the most profitable products is LPG (Liquefied Petroleum Gas) which is composed mostly of propane (C3) and butane (C4). In addition, pentane (C5) and ethane (C2) may also be present in the gas as contaminants. Measurement of the molar fraction of the components of the GLP has been done by gas chromatographs. However, chromatography is a slow process, making it impossible to monitor the quality of the product in real time. In this work, it is proposed a soft sensor, using artificial neural networks, with the objective of inferring the molar fractions of C3, C4, C5 and C2. In this way, it would be possible to estimate the molar fractions of these LPG components once per minute, considerably faster than chromatographers. The results obtained are promising, showing that the virtual sensor can infer the molar fractions of C3, C4, C5 and C2 and thus enable improvement in the monitoring of LPG quality and, consequently, profitability.