Modelagem da transferência de massa na remoção do óleo da água produzida por flotação em coluna com uso de tensoativos de origem vegetal

• Ano de defesa: 2012
• Autor(a) principal: Valença, Raniere Dantas
• Tipo de documento: Dissertação
• Tipo de acesso: Acesso aberto
• Idioma: por
• Instituição de defesa: Universidade Federal do Rio Grande do Norte; BR; UFRN; Programa de Pós-Graduação em Engenharia Química; Pesquisa e Desenvolvimento de Tecnologias Regionais
• Palavras-chave em Português: Água de produção; Flotação; Tensoativo; Modelagem.; Oil produced water; Flotation; Surfactant; Modeling.; CNPQ::ENGENHARIAS::ENGENHARIA QUIMICA
• Link de acesso: https://repositorio.ufrn.br/jspui/handle/123456789/15822

The treatment of oil produced water and its implications are continually under investigation and several questions are related to this subject. In the Northeast Region Brazil, the onshore reservoirs are, in its majority, mature oil fields with high production of water. As this oil produced water has high levels of oil, it cannot be directly discarded into the environment because it represents a risk for contamination of soil, water, and groundwater, or even may cause harm to living bodies. Currently, polyelectrolytes that promote the coalescence of the oil droplets are used to remove the dispersed oil phase, enhancing the effectiveness of the flotation process. The non-biodegradability and high cost of polyelectrolytes are limiting factors for its application. On this context, it is necessary to develop studies for the search of more environmentally friendly products to apply in the flotation process. In this work it is proposed the modeling of the flotation process, in a glass column, using surfactants derived from vegetal oils to replace the polyelectrolytes, as well as to obtain a model that represents the experimental data. In addition, it was made a comparative study between the models described in the literature and the one developed in this research. The obtained results showed that the developed model presented high correlation coefficients when fitting the experimental data (R2 > 0.98), thus proving its efficiency in modeling the experimental data.