Comparing the predictions by NIR spectroscopy based multivariate models for distillation fractions of crude oils by...

The whole range of distillation fractions in industrially relevant crude oil samples is predicted by using two multivariate models based on near-infrared (NIR) spectra. The first versions of the models as well as the respective model updates are considered, with the updates largely aimed at expanding the models. The prediction results are compared across all the fractions and F-test is used to critically compare the performance of the models and the effectiveness of the limited updates. The results suggest that both multivariate methods perform very comparably, and the updates do not lead to statistically significant changes, which differs from what one could conclude from the nominal prediction errors. The near-equivalency of the prediction accuracy of the updated models is additionally illustrated by perusing predictions of a number of batches from one sour and one sweet crude arriving at the refinery during a four month period.