2013
DOI: 10.1590/s0100-40422013000900002
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PCA: uma ferramenta para identificação de traçadores químicos para água de formação e água de injeção associadas à produção de petróleo

Abstract: PCA: A TOOL FOR IDENTIFICATION OF CHEMICAL TRACERS FOR FORMATION AND INJECTION WATERS ASSOCIATED WITH OIL PRODUCTION. This study describes the use of Principal Component Analysis to evaluate the chemical composition of water produced from eight oil wells in three different production areas. A total of 609 samples of produced water, and a reference sample of seawater, were characterized according to their levels of salinity, calcium, magnesium, strontium, barium and sulphate (mg L-1) contents, and analyzed by u… Show more

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Cited by 9 publications
(5 citation statements)
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“…Thus, the results show that the produced water is a dynamic medium of complex chemical composition, subject to variation as a function of time, due to ambient temperature conditions, contact with air, photo-oxidation, biodegradation, as well as other factors inherent in the studied system 2 . The literature states that variations in the physical-chemical parameters of produced water in oilfields may be related to seasonal aspects 44 .…”
Section: Physico-chemical Analysis Of Produced Watermentioning
confidence: 99%
“…Thus, the results show that the produced water is a dynamic medium of complex chemical composition, subject to variation as a function of time, due to ambient temperature conditions, contact with air, photo-oxidation, biodegradation, as well as other factors inherent in the studied system 2 . The literature states that variations in the physical-chemical parameters of produced water in oilfields may be related to seasonal aspects 44 .…”
Section: Physico-chemical Analysis Of Produced Watermentioning
confidence: 99%
“…Bi-plot partially grouped walnut genotypes according to their parents (Table 6; Figure 2). Multivariate analysis is performed to summarize the variability of a complex data set and present the data in an interpretable form as in the prin cipal components (Ribeiro et al 2013). The purpose of PCA is to identify the main factors and influential parameters that distinguish pa rticipation .…”
Section: Phenological Data Analysismentioning
confidence: 99%
“…2). Multivariate analysis summarized the variability of a complex dataset and presented it in an interpretable form, such as in principal components (Ribeiro et al 2013). The aim of PCA is to determine the main factors and effective parameters that discriminate among accessions (Khadivi-Khub et al 2015).…”
Section: Phenological Data Analysismentioning
confidence: 99%