The exactitude of petroleum fluid molecular weight correlations affects significantly the precision of petroleum engineering calculations and can make process design and trouble-shooting inaccurate. Some of the methods in the literature to predict petroleum fluid molecular weight are used in commercial software process simulators. According to statements made in the literature, the correlations of Lee–Kesler and Twu are the most used in petroleum engineering, and the other methods do not exhibit any significant advantages over the Lee–Kesler and Twu correlations. In order to verify which of the proposed in the literature correlations are the most appropriate for petroleum fluids with molecular weight variation between 70 and 1685 g/mol, 430 data points for boiling point, specific gravity, and molecular weight of petroleum fluids and individual hydrocarbons were extracted from 17 literature sources. Besides the existing correlations in the literature, two different techniques, nonlinear regression and artificial neural network (ANN), were employed to model the molecular weight of the 430 petroleum fluid samples. It was found that the ANN model demonstrated the best accuracy of prediction with a relative standard error (RSE) of 7.2%, followed by the newly developed nonlinear regression correlation with an RSE of 10.9%. The best available molecular weight correlations in the literature were those of API (RSE = 12.4%), Goosens (RSE = 13.9%); and Riazi and Daubert (RSE = 15.2%). The well known molecular weight correlations of Lee–Kesler, and Twu, for the data set of 430 data points, exhibited RSEs of 26.5, and 30.3% respectively.

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The intercriteria analysis developed on the base of intuitionistic fuzziness and index matrices was applied to evaluate processing data of the LUKOIL Neftohim Burgas H-Oil ebullated bed vacuum residue hydrocracker with the aim of revealing the reasons for increased fouling registered during the 3rd cycle of the H-Oil hydrocracker. It was found that when the ratio of the Δ T of the 1st reactor to the Δ T of the 2nd reactor gets lower than 2.0, an excessive H-Oil equipment fouling occurs. The fouling was also found to be favored by processing of lower Conradson carbon content vacuum residual oils and increased throughput and depressed by increasing the dosage of the HCAT nanodispersed catalyst. The fouling in the atmospheric tower bottom section is facilitated by a lower aromatic content in the atmospheric tower bottom product. The addition of FCC slurry oil not only increases aromatic content but also dissolves some of the asphaltenes in the atmospheric residual hydrocracked oil and decreases its colloidal instability index. The fouling in the vacuum tower bottom section is facilitated by a higher saturate content in the VTB. Surprisingly, it was found that the asphaltene content in the VTB depresses the fouling rate. No relation was found of the sediment content in the hydrocracked residual oils measured by hot filtration tests and by the centrifuge method to the equipment fouling of the H-Oil hydrocracker.