Use of Artificial Neural Networks for Predicting Crude Oil Effect on CO2 Corrosion of Carbon Steels

摘要: The role of crude oil on CO2 corrosion has gained special attention in the last few years due to its significance when predicting rates. However, complexity and variability oils makes it hard model effects, which can influence not only wettability properties but also corrosivity associated brine. This study evaluates usefulness Artificial Neural Networks (ANN) predict inhibition offered by as a function several their have been related previous studies protectiveness oils, i.e. nitrogen sulfur contents, resins asphaltenes, TAN, nickel vanadium content, etc. Results showed that neural networks are powerful tool validity results is closely linked amount data available experience knowledge accompany analysis.