EVALUATION AND MODELING OF FOULING CHARACTERISTICS OF PETROLEUM CRUDE OILS AND CRUDE BLENDS

• Main Author: RAFEEN, MOHAMMAD SYAMZARI BIN RAFEEN
• Format: Thesis
• Language: English
• Published: 2011
• Online Access: http://utpedia.utp.edu.my/2826/1/Evaluation_and_Modeling_of_Fouling_Characteristics_of_Petroleum_Crude_Oils_and_Crude_Blends.pdf; http://utpedia.utp.edu.my/2826/

Fouling of preheat exchangers in refinery crude distillation unit is a complex phenomena and identified to be the major energy consuming source in petroleum refineries. The cost of fouling could be substantial where it comprises the economics and environmental aspect. In this research work, four Malaysian crude oils and a condensate were selected for fouling experiments using Hot Liquid Process Simulator (HLPS). The experiments were conducted to determine the effect of surface temperature and crude blending on the fouling characteristics of the selected crudes and crude blends. A method published in the literature is used to analyze the raw data into a meaningful fouling resistance data. Initial fouling rates are then determined by taking the slope for the linear portion of the fouling resistance versus time curve. Arrhenius plot was used to obtain the true activation energy, E so that the fouling propensity could be determined. Crude ranking in term of fouling propensity for the neat crude is in the order of Crude C > Crude D > Crude B > Crude A and for the crude blend, it is in the order of A-C blend > A-D blend > A-B blend. The effect of adding Condensate E to Crude C has resulted in the lowest activation energy in comparison with the other crudes and crude blends. Four threshold fouling models were validated with the experimental data established. The models evaluated are Ebert and Panchal model, Panchal et al. model, Polley et al. model and Nasr and Givi model. Furthermore, three estimation methods were used for each model which are (i) estimation method 1 - physical properties estimated at inlet bulk temperature, (ii) estimation method 2 - physical properties estimated at film temperature or surface temperature (for Polley et al. model only) and (iii) estimation method 3 – physical properties estimated at film temperature or surface temperature (for Polley et al. model only) plus the exclusion of removal term. Model parameters were estimated using least square technique to minimize the error between the predicted and experimental data. viii There are three model parameters that need to be determined which are α, γ and E where E values are fixed to the values obtained using Arrhenius plot whilst the other two parameters, α and γ are determined using least square technique by maximizing the coefficient of determination, R2. Practical operating condition range for model prediction applicability was also defined where the upper range limit is demarcated by the boiling point for the crudes or crude blends and the lower range limit is demarcated by the operational inlet bulk temperature of HLPS. Model prediction using estimation method 1 was found to give better prediction in comparison with the prediction using estimation methods 2 and 3 for all crudes, crude blends and condensate – crude blend. This is based on (i) better R2 values obtained during the model parameter estimation, (ii) fouling rates approaching zero at lower temperature without going to negative value and (iii) reasonably good and consistent prediction trend over the defined practical operating condition range. All threshold models prediction using estimation method 1 gave a reasonably good prediction where R2 is more than 0.9 for all models. This suggests that physical properties for threshold models need to be estimated at inlet bulk temperature and the removal term for the models is required even though the crude velocity and the fluid shearing effect is low for experiment in HLPS.