Abstract
Abstract Asphaltene deposition in oil wells is a challenging flow-assurance phenomenon that affects the well production, project economics, and operational safety. While asphaltene precipitation is governed by the hydrocarbon mixture thermodynamics, Asphaltene deposition is governed by the complexity of flow hydrodynamic behavior and characteristics. This study aims to evaluate and compare the performance of the existing asphaltene deposition models and improve the current theoretical understanding of the deposition phenomenon by developing better predictive asphaltene deposition model. A large experimental database is collected, including aerosol and asphaltene particles deposition in air and crude oil systems, respectively, to carry on the evaluation. The results of this study revealed that Kor and Kharrat (2017) model of transport coefficient, which accounts for both diffusional and inertial deposition mechanisms outperformed other models in matching the transport coefficient from aerosol/air data. In addition, an improved sticking probability model is proposed in this study, and curve fitted using corrected deposition flux data to obtain the model constant. The improved model is not only physically sound, i.e. SP≥1, but also it requires less input data than other models. A validation study of the improved model shows a slight over prediction of experimental data with an absolute average error of 6.8% and standard deviation of 11.4%. The significance of this work is to provide theoretical predictive tool for asphaltene deposition in pipes to enable prevention, mitigation, and management of oil field asphaltene deposition strategies.
Published Version
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