Four nonlinear regression techniques were explored to model gas oil viscosity on the base of Walther’s empirical equation. With the initial database of 41 primary and secondary vacuum gas oils, four models were developed with a comparable accuracy of viscosity calculation. The Akaike information criterion and Bayesian information criterion selected the least square relative errors (LSRE) model as the best one. The sensitivity analysis with respect to the given data also revealed that the LSRE model is the most stable one with the lowest values of standard deviations of derivatives. Verification of the gas oil viscosity prediction ability was carried out with another set of 43 gas oils showing remarkably better accuracy with the LSRE model. The LSRE was also found to predict better viscosity for the 43 test gas oils relative to the Aboul Seoud and Moharam model and the Kotzakoulakis and George.
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.
Inter-criteria analysis was employed in VGO samples having a saturate content between 0.8 and 93.1 wt.% to define the statistically significant relations between physicochemical properties, empirical structural models and vacuum gas oil compositional information. The use of a logistic function and employment of a non-linear least squares method along with the aromatic ring index allowed for our newly developed correlation to accurately predict the saturate content of VGOs. The empirical models developed in this study can be used not only for obtaining the valuable structural information necessary to predict the behavior of VGOs in the conversion processes but can also be utilized to detect incorrectly performed SARA analyses. This work confirms the possibility of predicting the contents of VGO compounds from physicochemical properties and empirical models.
252 literature sources and about 5000 crude oil assays were reviewed in this work. The review has shown that the petroleum characterization can be classified in three categories: crude oil assay; SARA characterization; and molecular characterization. It was found that the range of petroleum property variation is so wide that the same crude oil property cannot be measured by the use of a single standard method. To the best of our knowledge for the first time the application of the additive rule to predict crude oil asphaltene content from that of the vacuum residue multiplied by the vacuum residue TBP yield was examined. It was also discovered that a strong linear relation between the contents of C5-, and C7-asphaltenes in crude oil and derived thereof vacuum residue fraction exists. The six parameter Weibull extreme function showed to best fit the TBP data of all crude oil types, allowing construction of a correct TBP curve and detection of measurement errors. A new SARA reconstitution approach is proposed to overcome the poor SARA analysis mass balance when crude oils with lower density are analyzed. The use of a chemometric approach with combination of spectroscopic data was found very helpful in extracting information about the composition of complex petroleum matrices consisting of a large number of components.
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