Prediction of Wax Appearance Temperature Using Artificial Intelligent Techniques

摘要

The paraffin particles can promote and be involved in the formation of deposits which can lead to plugging of oil productionfacilities. In this work, an experimental prediction of wax appearance temperature (WAT) has been performed on 59Algerian crude oil samples using a pour point tester. In addition, a modeling investigation was done to create reliable WATparadigms. To do so, gene expression programming and multilayers perceptron optimized with Levenberg–Marquardt algorithm(MLP-LMA) and Bayesian regularization algorithm were implemented. To generate these models, some parameters,namely density, viscosity, pour point, freezing point and wax content in crude oils, have been used as input parameters. Theresults reveal that the developed models provide satisfactory results. Furthermore, the comparison between these modelsin terms of accuracy indicates that MLP-LMA has the best performances with an overall average absolute relative error of0.23% and a correlation coefficient of 0.9475.