Prediction of Waxy Crude Oil Properties Using Near- Infrared Spectroscopy for Upstream Applications

Abstract Monitoring the flowability of waxy crude oil in offshore pipelines is crucial due to its tendency to solidify when the ambient temperature drops below the crude oil's pour point. Preventing this condition is essential to avoid undesired clogging in the pipeline. Pour Point temperature (PPT) and density are among the critical flow assurance (FA) properties for waxy crude oil that directly indicate the flowability state and the quality of the waxy crude oil in the pipeline. Therefore, it is imperative to develop a rapid and precise technique for an in-situ determination of the waxy crude oil properties. This research describes the prediction of pour point and density of waxy crude oils by exploiting the absorbance spectrum obtained from near-infrared (NIR) region. In this study, the prediction of the PPT and density properties of waxy crude oils were investigated through a calibration models developed using Fourier transform near-infrared (FT-NIR) spectroscopy which capable of performing multicomponent analysis and can be used with multivariate analytic methods. The FT-NIR spectra for the waxy crude oil were captured and interpreted by using suitable spectra wavenumber regions through multivariate statistical techniques such as partial least square (PLS). A total of 110 samples of waxy crude oils were analyzed for their pour point and density using ASTM 64749-02 and ASTM D5002 methods, respectively. These properties were then utilized as reference data to establish the calibration models and validated using 40 unknown waxy crude oil samples to ensure the robustness of the models. The Calibration models developed for both properties had the coefficient of determination (R2) of 0.9895 with the RMSECV of 0.75% for the pour point and R2 of 0.9789 and RMSECV of 0.024% for the density property. The statistical evaluation of the validation samples also confirmed that the difference between the actual value and the predicted value from the calibration model was not significantly different and acceptable. Model validation exercise using unknown samples, successfully meeting model performance acceptance criteria of less than 20% outlier and less than 5%Relative standard deviation (RSD). Therefore, the both models have given a satisfactory result for the pour point and density properties determination using the FT-NIR technique. The results of this study indicated that FT-NIR spectroscopy with chemometrics and multivariate technique can be used for the pour point and density of the waxy crude oil monitoring to replace the time-consuming and labor-intensive conventional methods.