An experimental and theoretical investigation of asphaltene precipitation and aggregation kinetics in model oil systems

Abstract

Asphaltenes are the heaviest and most complex fraction of crude oil with the highest aromaticity and polarity. They can precipitate at any point of oil production or transportation as a result of changes in temperature, pressure or/and composition. The precipitation and deposition of asphaltenes during oil production and processing can lead to serious problems including plugging of pipelines and production facilities, reduction of storage capacity, equipment fouling, etc. Thus, it can have a serious economic impact on petroleum production and processing. Because of the chemical complexity of asphaltenes, their molecular structure, natural state, association, aggregation etc. are a subject of continuous debate and research efforts. To unravel the key parameters that govern asphaltenes precipitation, numerous studies have been carried out over the past fifty years. It has been shown that the onset of asphaltenes precipitation is a thermodynamic driven process due to asphaltene solubility variation as a result of pressure, temperature and compositional changes [1]. The present Thesis deals with the kinetic investigation of asphaltene precipitation/aggregation from model oils using photon correlation spectroscopy as the detection technique. The asphaltenes used in this study was the pentane insoluble asphaltenes fraction extracted from field deposits. npentane was used as precipitant for inducing asphaltene destabilization and precipitation from model asphaltenes-toluene systems. A series of experiments were carried out with different initial asphaltene concentrations in model oil systems (i.e. 10, 20, 40, 60, and 120 mg of asphaltenes/Liter of toluene) and different toluene/pentane volume ratios. The onset of asphaltene precipitation and dynamic evolution of the effective hydrodynamic diameter of asphaltene aggregates as well as the asphaltene nanoaggregates size distribution were monitored at discrete time intervals with the aid of NanoBrook 90Plus Zeta Particle Size Analyzer instrument for different asphaltene concentrations and n-pentane volume fractions from 50 to 95.24%. The experimental results revealed that as the n-pentane concentration increased the measured effective diameter of asphaltene aggregates exhibited a concave type of functional dependence with respect to the n-pentane volume fraction. In particular, the effective diameter of asphaltene aggregates initially increased with the n-pentane concentration up to a maximum size followed by a decrease in size beyond a critical value of n-pentane concentration (~85-83 % C5). This is a clear indication that depending on the precipitant concentration (i.e. asphaltene and solvent solubility parameters) the contribution of the various asphaltene association/aggregation forces (i.e. Acid–base and hydrogen bonding interactions, formation of metal coordination complexes, steric interactions, π–π stacking interactions, etc.) to the overall asphaltene interaction potential vary leading to the formation of more or less dense assemblies of asphaltene nanoaggregates. One can model the aggregation kinetics of unstable asphaltenes nanoaggregates by employing the general Smoluchowski Equation. The rate of particle aggregation will depend on the size of the colloidal particles and the aggregation rate constant manifested by the stability ratio which is a complex function of all molecular interactions (i.e., steric, electrostatic, etc.) acting on the colloidal asphaltenes nano-aggregates. An advanced numerical approach (i.e. collocation on finite elements) was employed to solve the general population balance equation describing the aggregation kinetics of asphaltenes primary particles. Model predictions were found to be in excellent agreement with the experimental measurements on the time evolution of the average particle diameter under different conditions, which clearly shows the predictive capabilities of the proposed population balance model.

Date of Award	2015
Original language	American English
Supervisor	Fawzi Banat (Supervisor)