Research on the prediction model of wax deposition thickness of waxy crude oil in pipeline transportation

In order to formulate an economical and safe pigging plan, an improved GM(1,1) model based on the transformation of function ln(x + c)(c >= 0) is proposed to find a more accurate prediction model of wax deposition thickness. Firstly, the feasibility of the improved GM(1,1) model based on function ln(x + c) transformation is proved by theoretical analysis. Secondly, the traditional GM(1,1) model and the improved GM(1,1) model are established by taking the indoor loop experiment and the field experiment data of wax deposition thickness in oil pipeline as examples, respectively, and the influence of c value on the fitting accuracy and prediction accuracy of wax deposition thickness is analyzed. The results show that the fitting accuracy and prediction accuracy of the improved GM(1,1) model are higher than those of the traditional GM(1,1) model; and the fitting accuracy increases with the increase of c value. The prediction accuracy increases greatly at first and then decreases slightly, and there is an optimal value of c, which makes the prediction accuracy reach the highest. Finally, in the practical application of the improved GM(1,1) model based on the function ln(x + c) transformation, the value of c should be reasonably selected in order to achieve the highest prediction accuracy.

Automated summary

In order to predict the wax deposition thickness accurately, an improved GM(1,1) model based on the transformation of function ln(x + c) is proposed. The results show that the improved model has higher accuracy compared to the traditional GM(1,1) model, and the accuracy can be further improved by selecting an optimal value for the parameter c in the function transformation.