A reliable model for estimating the wax deposition rate during crude oil production and processing

Deposition of wax in surface and subsurface pipes and even perforations can lead to serious problems including pore spaces blockage, plugging of pipelines, and minimum profitability. Therefore, understanding wax deposition and wax related-properties improves the oil recovery and processing operations in petroleum industry. In this research work, the rate of wax deposition is correlated to a number of main parameters such as the dynamic viscosity of crude oil, shear stress, gradient of wax molecular concentration and temperature difference in pipeline system through implementation of a newly developed model, known as least squares support vector machine (LSSVM) along with the coupled simulated annealing (CSA) optimization strategy. The possible outliers are detected through employing the Leverage technique which involves residual errors plots, Williams' plot, and Hat matrix. The results imply that whole collected real data are in applicability domain of the proposed model. Using a comprehensive statistical investigation, a very good agreement between the predicted LSSVM-CSA outputs and real wax deposition rate is found such that the average relative error percentage and determination coefficient (R2) are 0.048% and 0.999, respectively. Such a study can assist to provide better designs (technically and economically) for underground and surface facilities while dealing with wax deposition cases.