Numerical Study of Wax Deposition from Multiphase Flow in Oil Pipelines with Heat and Mass Transfer

Wax deposition in field-scale crude oil pipelines poses a significant challenge to the oil and gas industry, leading to reduced flow rates, increased pressure drops, and potential blockages. Understanding the mechanisms governing wax deposition is crucial for developing effective mitigation strategies. This study investigates the impact of multiphase flow conditions, including water-in-oil emulsion, wax precipitation kinetics, shear dispersion, and molecular diffusion, on wax deposition in field-scale crude oil pipelines. A numerical model is developed that employs second-order semi-implicit temporal discretization schemes, such as Crank–Nicolson and Adams–Bashforth methods, in conjunction with a bivariate spectral collocation scheme using Chebyshev–Gauss–Lobatto grid points. The impact of various flow parameters, including Reynolds number (Re), mass Grashof number (Gr), Schmidt number (Sc), and Weber number (We), on the flow variables, wall shear stress, and heat and mass fluxes are investigated. The numerical simulations demonstrate that flow parameters significantly influence the flow behavior, wall shear stress, wall heat flux, and wall mass flux in waxy crude oil pipelines. Specifically, the aggregation of wax crystals in the pipeline decreases by at most 2.5% with increasing Reynolds number from 2.2361 to 3.1361. Conversely, it increases by at most 3.4% with increasing mass Grashof number from 5 to 11 and by at most 4.8% with increasing Weber number from 1.0 to 2.5. Furthermore, the Nusselt number increases from 1.9907 to 4.9834 with increasing Reynolds number from 2.2361 to 5.2361 and from 1.9907 to 2.0225 with increasing mass Grashof number from 5 to 20. It also increases from 1.9907 to 2.0434 with increasing Weber number from 1.0 to 2.5. The insights gained from this study can be applied to optimize pipeline design, operational parameters, and wax deposition mitigation strategies, leading to enhanced pipeline performance and reduced operational costs. The numerical model developed in this work serves as a valuable tool for simulating and predicting wax deposition behavior under various operating conditions.