Research on Dynamic Prediction Model of Wax Deposition in Wellbore

Wax deposition in oil wells has become an important issue, which affects the production of oil fields. According to the wax deposition in the wellbore of an oilfield in Northwest China, a dynamic prediction model of the wellbore wax deposition was established based on the molecular diffusion mechanism. The compiled software can predict the temperature and pressure of the fluid, wax deposition point, wax deposition weight, wax deposition volume, wax deposition speed, and wax removal cycle of self-blowing wells and pumping well bores and sucker rods at different well depths. The software is used to predict the influence of flow temperature and pressure, wax deposition point, wax deposition volume, wax deposition rate, wax removal cycle and water content, gas-liquid ratio and oil production on the wax deposition rate of the wellbore of M1 well in a certain northwest oilfield. The results show that the prediction results of the model are reliable. The prediction accuracy of the flow temperature and pressure of the M1 well is higher than 92%, and the prediction accuracy of the wax removal cycle is up to 89%. The law of influence is consistent with the literature results. Therefore, the research results of this article provide a quantitative basis for the formulation of wax removal cycle in an oilfield in Northwest China, and provide theoretical and technical support for optimizing wax removal and control technology.