Caracterização de água produzida na indústria de petróleo para fins de descarte e otimização do processo de separação óleo/água
The oil industry has several segments that can impact the environment. Among these, produced water which has been highlight in the environmental problem because of the great volume generated and its toxic composition. Those waters are the major source of waste in the oil industry. The composition of...
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| Formato: | Dissertação |
| Idioma: | por |
| Publicado em: |
Universidade Federal do Rio Grande do Norte
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| Endereço do item: | https://repositorio.ufrn.br/jspui/handle/123456789/15808 |
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| Resumo: | The oil industry has several segments that can impact the environment. Among these,
produced water which has been highlight in the environmental problem because of the great
volume generated and its toxic composition. Those waters are the major source of waste in the
oil industry. The composition of the produced water is strongly dependent on the production
field. A good example is the wastewater produced on a Petrobras operating unit of Rio
Grande do Norte and Ceará (UO-RNCE). A single effluent treatment station (ETS) of this unit
receives effluent from 48 wells (onshore and offshore), which leads a large fluctuations in the
water quality that can become a complicating factor for future treatment processes. The
present work aims to realize a diagnosis of a sample of produced water from the OU - RNCE
in compliance to certain physical and physico-chemical parameters (chloride concentration,
conductivity, dissolved oxygen, pH, TOG (oil & grease), nitrate concentration, turbidity,
salinity and temperature). The analysis of the effluent is accomplished by means of a MP
TROLL 9500 Multiparameter probe, a TOG/TPH Infracal from Wilks Enterprise Corp. -
Model HATR - T (TOG) and a MD-31 condutivimeter of Digimed. Results were analyzed by
univariated and multivariated analysis (principal component analysis) associated statistical
control charts. The multivariate analysis showed a negative correlation between dissolved
oxygen and turbidity (-0.55) and positive correlations between salinity and chloride (1),
conductivity, chloride and salinity (0.70). Multivariated analysis showed there are seven
principal components which can explain the variability of the parameters. The variables,
salinity, conductivity and chloride were the most important variables, with, higher sampling
variance. Statistical control charts have helped to establish a general trend between the
physical and chemical evaluated parameters |
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