Genetic Algorithm Development for Prediction of Modified Langmuir Isotherm Parameters of Asphaltene Adsorption onto Metal Surfaces: Using Novel Quartz Crystal Nanobalance

Abstract

Asphaltene deposition is a common problem in production operation; these problems cause obstruction through pore throats, production tubing, and also surface facilities. In this article, adsorption of asphaltene, obtained from a crude oil sample from Iranian southern oil fields, onto metal surfaces has been extensively investigated. The metal surfaces are aluminum, iron, and copper. The amount of adsorbed asphaltene was successfully measured with a novel method named as quartz crystal nanobalance. To model the prediction of asphaltene adsorption onto metal surfaces, a concentration dependent factor, X, was introduced. To account for the exact asphaltene concentration effect on both adsorption and desorption steps, the modified Langmuir isotherm was developed. Genetic algorithm was used to optimize the set of unknown parameters. The results indicated that good agreement was between model results for different metal surfaces and experimental data.