In this work, an ultrasound experimental setup was designed to investigate the feasibility of using low-frequency ultrasonic waves as a substitute to reduce the consumption of chemical demulsifiers in the pretreatment of crude oil. The experiments were planned to study the effects of irradiation time, ultrasonic field intensity and initial water content on the efficiency of separation. The results of experiments showed that by selecting a proper irradiation time and field intensity, it is possible to decrease the usage of demulsifiers by 50%. Moreover, a population balance model was proposed to explicate the experimental data. A hybrid coalescence model was developed to determine the frequency of aggregation. The parameters of the model were estimated by linear regression. The parameter estimation was performed using a parallel execution of the particle swarm optimization algorithm. The results of the model showed a decent agreement with the experimental data.

A hybrid model based on the population balance approach was developed to represent the electrocoalescence phenomena in water-in-oil emulsions. A semi-empirical aggregation model was used in a population balance equation to simulate the dehydration of two different crude oils. The unknown parameters of the population balance equation were estimated using experimental data. The experiments were performed in a continuous pilot plant used to evaluate the dehydration of crude oil emulsions with an initial 4−10 wt % of water. Different functional forms for the specific rate of coalescence and sink term of the population balance equation were evaluated. The results of the proposed hybrid model were compared to the experimental data and previous empirical models reported in the literature. The results showed good agreement with the experimental data and values obtained by empirical models.

An experimental and theoretical study was performed to analyze the evolution of droplet size distribution and phase separation in water-in-oil emulsions under the effect of the electric field in a batch vessel. The effects of electrostatic time, initial water content, and electric potential on the efficiency of separation were studied in the experiments. Moreover, a mathematical model based on population, mass, and momentum balance equations for dispersed, oil, and free phases was developed to interpret the experimental data. A coalescence kernel was proposed to predict the aggregation of droplets. Furthermore, a capture term was added to the balance equations to address the creation of free water. The parameters of the coalescence and capture models were estimated using the experimental data. The estimation of the parameters was done using parallel execution of the particle swarm optimization algorithm. The results of the simulation showed a decent performance of the model in predicting the profiles of water content inside the vessel.

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