Wax deposition in flowlines is a major flow assurance issue that lowers the oil production rate and causes significant economic losses. This justifies the need for reliable tools to accurately predict the deposition process and analyze the risk factors in production design and management. This study developed a mechanistic model based on the particulate deposition phenomenon. A mass balance was applied based on particle size, and the growth was tracked by the population balance model. The concept of critical size was applied to determine the fraction of aggregates that can deposit on the wall. An integrated simulator is developed by coupling thermodynamics, hydrodynamics, heat transfer, and deposition modules. In addition, data analytics was applied on available flow loop deposition data to develop a closure relation for the precipitation rate constant as a function of time, temperature, flow rate, and diameter. Then, another set of deposition data was used to verify the accuracy of the proposed model and closure. After the robustness of the developed model was tested, a sensitivity analysis was performed based on pipe size, particle size, and flow rate on the paraffin deposition rate. Based on the model results, the rate of deposition increased with increasing the diameter size, decreasing the initial particle size, and reducing the flow rate. This is attributed to several factors, such as the flow velocity that affects the sticking probability and the advection force applied on bigger particle sizes. Furthermore, the model results can aid in estimating optimum conditions to reduce or manage wax deposition in transport flowlines.
