A simulation approach to predict electrostatic coalescence performance of water-in-oil emulsion using population balance model

Abstract

ABSTRACT Electrostatic coalescence of the water droplets in water-in-oil (W/O) emulsion plays a significant role in demulsification process. As the droplets collide and aggregate with each other, the dispersed droplets may coalesce and separate from continuous phase. Several mechanisms simultaneously contribute to the complexity associated with droplets coalescence. Thus, an appropriate simulation approach is needed to predict electrostatic coalescence performance in W/O emulsion. In this work, the population balance model (PBM) was used to predict coalescence performance of W/O emulsion under electric field. The proposed approach is novel as it integrates various mathematical models to study dispersed droplets collision frequency considering Boltzmann motion, differential settlement, and electric field. Moreover, a new collision efficiency model, which is best proper for the droplet size between 1 μm and 100 μm, is also proposed to make the prediction model more accurate. The simulation results were verified by comparing with existing experimental datasets. After that, a sensitivity analysis was carried out to study parameters that affect electrostatic coalescence performance, such as electric field strength, dispersion permittivity, continuous viscosity, and collision efficiency coefficient. The results show that the higher voltage and droplet permittivity both lead to the greater electrostatic coalescence performance, but the increments are gradually smaller under the condition of neglecting the droplet fragmentation. With the increasing of continuous viscosity, the droplet size median significantly decreases at first and then flattens. Meanwhile, the performance of electrostatic coalescence is greater at bigger collision efficiency coefficient. But the variation of volume size median with collision efficiency coefficient is modest. The simulation approach proposed in this paper provides an in-depth understanding of the dispersed droplets collision in electric field, which provides useful insights for prediction of electrostatic coalescence performance of W/O emulsion in petroleum industries.