Abstract

This paper proposes a methodology to characterize the following petroleum properties: UOP characterization factor (K), nitrogen content, solubility parameter, sulfur content, maximum and minimum pour point, and kinematic viscosity (at 20 °C, 30 °C, 40 °C and 50 °C), in petroleum within a single 1H NMR (proton nuclear magnetic resonance) spectra. Multivariate calibration tools, such as partial least squares (PLS), orthogonal projections to latent structures (OPLS) (with variable selection), interval PLS (iPLS), synergy interval PLS (siPLS) and model population analysis (MPA), were applied to 138 samples. The models were evaluated by coefficient of determination (R2), root mean square error of prediction (RMSEP), and residuals. In general, model population analysis had better results in the determination of petroleum's physicochemical properties than PLS and OPS. Thus, MPA provided models with better accuracy in the determination of the following properties: UOP characterization factor (0.06), nitrogen content (0.048 wt%), kinematic viscosity at 40 °C (relative error of 21.9%) and pour point (14.58 °C and 19.2 °C, respectively). The sulfur content was estimated with a 0.09 wt% mean error of prediction, using the PLS model, and the solubility parameter with a 1.06 (MPa)1/2 mean error of prediction, using the OPLS model.

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