The objective of this research project is to complement the objectives proposed for the EPIC-Energy Production Innovation Center, which is focused on studies of emulsion properties and the influence of physical and chemical parameters on viscosity and inversion of phases. This work aims to improve models of viscosity and phase inversion by implementing a parameter representative of the chemistry of the system, i.e., chemical composition of both phases. It is known that the definition of the type of emulsion formed (o / w or w / o) is defined by the chemical equilibrium thermodynamics established between the phases that make up the emulsion and, in principle, one type can be converted into another just by changing the composition phase chemistry or system temperature. Likewise, the inversion point (critical fraction of dispersed phase) can be shifted to higher or lower values. The chemical magnitude that adds the chemical thermodynamics of the system is known as HLD (Hydrophilic / Lipophilic Difference). The present approach brings the application of new concepts in the oil area with respect to the inversion of emulsions and a possibility of applying this concept in the field. The HLD parameter is a thermodynamic property directly associated with the partitioning of the surfactant between the phases of an emulsion, affecting the physicochemical properties of the interfacial film and, consequently, the energy barrier that separates the thermodynamic state of isolated drops from the thermodynamic state after coalescence of the micro-drops in the bulk of the emulsion. The prediction of viscosity variation and phase inversion is extremely important for field operations due to impacts on the electrical submersible pumps (ESP) and on the production system as a whole. Models of viscosity and phase inversion take into account only physical parameters such as dispersed phase fraction and phase viscosity ratio. With this guidance, the present post-doc proposal is integrated with the other research works that are under development within the EPIC, such as master's dissertations, doctoral and post-doctoral theses. The post-doc will work by compiling the experimental data obtained from the bench tests and will implement chemical parameters to the existing models in order to improve the predictability of these models.
News published in Agência FAPESP Newsletter about the scholarship: