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Comparison of Near-Infrared, Infrared, and Raman Spectroscopy for the Analysis of Heavy Petroleum Products
Near-infrared (NIR) spectroscopy has been successfully applied to the determination of API (American Petroleum Institute) gravity of atmospheric residue (AR), which is the heaviest fraction in crude oil. This fraction is completely dark and very viscous. Preliminary studies involving Raman and infra...
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Published in: | Applied spectroscopy 2000-02, Vol.54 (2), p.239-245 |
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description | Near-infrared (NIR) spectroscopy has been successfully applied to the determination of API (American Petroleum Institute) gravity of atmospheric residue (AR), which is the heaviest fraction in crude oil. This fraction is completely dark and very viscous. Preliminary studies involving Raman and infrared (IR) spectroscopies were also evaluated along with NIR spectroscopy. The Raman spectrum of AR was completely dominated by strong fluorescence from polycyclic aromatic hydrocarbons, called asphaltenes. IR spectroscopy provided reasonable spectral features; however, its spectral reproducibility was poorer and noisier than that of NIR. Although absorption bands in the NIR region were broad and less characterized, NIR provided better spectral reproducibility with higher signal-to-noise ratio (which is one of the most important parameters in quantitative calibration in comparison to Raman and IR spectroscopies). Partial least-squares (PLS) regression was utilized to develop calibration models. NIR spectra of AR samples were broad, and baselines were varying due to the strong absorption in the visible range. However, the necessary information was successfully extracted and correlated to the reference API gravity with the use of PLS regression. API gravities in the prediction set were accurately predicted with an SEP (standard error of prediction) of 0.22. Additionally NIR showed approximately three times better repeatability compared to the ASTM reference method, which directly influences the process control performance. |
doi_str_mv | 10.1366/0003702001949168 |
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This fraction is completely dark and very viscous. Preliminary studies involving Raman and infrared (IR) spectroscopies were also evaluated along with NIR spectroscopy. The Raman spectrum of AR was completely dominated by strong fluorescence from polycyclic aromatic hydrocarbons, called asphaltenes. IR spectroscopy provided reasonable spectral features; however, its spectral reproducibility was poorer and noisier than that of NIR. Although absorption bands in the NIR region were broad and less characterized, NIR provided better spectral reproducibility with higher signal-to-noise ratio (which is one of the most important parameters in quantitative calibration in comparison to Raman and IR spectroscopies). Partial least-squares (PLS) regression was utilized to develop calibration models. NIR spectra of AR samples were broad, and baselines were varying due to the strong absorption in the visible range. However, the necessary information was successfully extracted and correlated to the reference API gravity with the use of PLS regression. API gravities in the prediction set were accurately predicted with an SEP (standard error of prediction) of 0.22. 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This fraction is completely dark and very viscous. Preliminary studies involving Raman and infrared (IR) spectroscopies were also evaluated along with NIR spectroscopy. The Raman spectrum of AR was completely dominated by strong fluorescence from polycyclic aromatic hydrocarbons, called asphaltenes. IR spectroscopy provided reasonable spectral features; however, its spectral reproducibility was poorer and noisier than that of NIR. Although absorption bands in the NIR region were broad and less characterized, NIR provided better spectral reproducibility with higher signal-to-noise ratio (which is one of the most important parameters in quantitative calibration in comparison to Raman and IR spectroscopies). Partial least-squares (PLS) regression was utilized to develop calibration models. NIR spectra of AR samples were broad, and baselines were varying due to the strong absorption in the visible range. However, the necessary information was successfully extracted and correlated to the reference API gravity with the use of PLS regression. API gravities in the prediction set were accurately predicted with an SEP (standard error of prediction) of 0.22. 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This fraction is completely dark and very viscous. Preliminary studies involving Raman and infrared (IR) spectroscopies were also evaluated along with NIR spectroscopy. The Raman spectrum of AR was completely dominated by strong fluorescence from polycyclic aromatic hydrocarbons, called asphaltenes. IR spectroscopy provided reasonable spectral features; however, its spectral reproducibility was poorer and noisier than that of NIR. Although absorption bands in the NIR region were broad and less characterized, NIR provided better spectral reproducibility with higher signal-to-noise ratio (which is one of the most important parameters in quantitative calibration in comparison to Raman and IR spectroscopies). Partial least-squares (PLS) regression was utilized to develop calibration models. NIR spectra of AR samples were broad, and baselines were varying due to the strong absorption in the visible range. 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title | Comparison of Near-Infrared, Infrared, and Raman Spectroscopy for the Analysis of Heavy Petroleum Products |
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