Grey system theory-based wax deposit rate prediction model for oil pipeline
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Abstract
Gray prediction model of wax deposit rate suitable for oil pipeline is built based on grey system theory. Applying this model can obtain the interaction result from different influencing factors, so as to avoid the non-objectivity of the result caused by unilateral study of individual factor. A case study shows that the average relative error from the prediction model is 2.376%, which is better than the stepwise regression prediction model. Mass fraction of wax molecular at pipe wall has greatest impact on wax deposit rate, and great in turn at pipe wall is shearstress, temperature gradient, wax molecular mass fraction and viscosity of crude oil. The model is simple with large amount of information. However, it is a static model, and a dynamic grey model is desired to get a better model.
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