SAR-AD Method to Characterize Eight SARA Fractions in Various Vacuum Residues and Follow Their Transformations Occurring during Hydrocracking and Pyrolysis

Adams, Jeramie J.; Rovani, Joseph F.; Planche, Jean‐Pascal; Loveridge, Jenny; Literati, Alex; Shishkova, Ivelina; Palichev, Georgi Nikolov; Kolev, Iliyan; Atanassov, Krassimir; Nenov, Svetoslav; Ribagin, Simeon; Stratiev, Dicho; Yordanov, Dobromir; Huo, Jianqiang

doi:10.3390/pr11041220

Cited by 4 publications

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“…An example of a model compound reporting to this fraction is dodecylbenzene. 36 Molecules of this type are similar to microcrystalline wax molecules. The amount of Aro 1 increases in the order Amenam < Varandey < Norne.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

“…29,30 In the SAR-AD separation the maltene fraction is further refined into three aromatics fractions (Arom 1 = 1 aromatic ring, Arom 2 = 2−3 fused aromatic rings, and Arom 3 = 4+ fused aromatic rings) in addition to the saturates and resins. 36 Table 4 shows the SAR-AD data for the three different crude oils in this study. The amount of saturates, which contain the paraffinic waxy molecules, increases in the order Amenam < Norne < Varandey.…”

Section: ■ Results and Discussionmentioning

confidence: 99%

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Physicochemical Approach to Pour Point Depressant Treatment of Waxy Crudes

et al. 2023

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A physicochemical approach was taken to show wax-based and crude oil-based differences between three waxy crudes (Amenam, Norne, and Varandey), that had similar amounts of wax according to DSC crystallizable areas, that were responsible for very different responses to pour point depressant additive treatments. Varandey crude oil was the most difficult to treat, and the effectiveness of the additives decreased with time when the oil had been aged for 2 years prior to treating with the additives. Detailed compositional analysis of these three crude oils, and their waxes, showed that Varandey contains the highest concentration of longer n-paraffins, significantly more total n-paraffins, a higher wax appearance temperature, the highest amount of wax that can be centrifuged at ambient temperature, a bimodal distribution of crystallizable waxes by DSC, more saturates in the heavy ends by the Saturates, Aromatics, Resins-Asphaltene Determinator, a very high amount of Waxphaltene Determinator Waxy B (−24 °C methyl ethyl ketone precipitated waxes that do not dissolve in heptane at that temperature but melt at 60 °C in heptane) and very little asphaltenes that do not flocculate. These additional characterization methods, including the wax appearance temperature, show that the amount of wax by DSC is not discriminating for some crude oils. Microscopy of Varandey showed large fractal crystalline domains that were different from Amenam, which showed classic large macrocrystalline needle-like crystals, or Norne that had a gelled network with much smaller needle-like crystals. Norne is less responsive to additive treatment than Amenam despite having significantly less n-paraffins, Waxphaltene Determinator Waxy B waxes, and asphaltenes. Simulated distillation shows that Norne is the heaviest oil and has the highest amount of isomeric material in the C24−C34 range and a higher temperature wax appearance temperature. Furthermore, its asphaltenes flocculated with the addition of isooctane at 60 °C, whereas the asphaltenes did not flocculate in Amenam. The higher amount of isomeric material by GCMS and the much smaller needle-like crystallites suggest that Norne wax is more microcrystalline in nature. Centrifuging Varandey waxes and doping them into Amenam and Norne resulted in the doped crude oils having a bimodal DSC profile with a higher wax appearance temperature. The presence of Varandey wax caused the oils to be significantly less responsive to pour point additive treatments. Overall, for these relatively similar crude oils, it is shown that the nature of the highest carbon number waxes, the wax appearance temperature, and the amount of the least soluble waxes are significantly more important than the crude oil composition when treating with additives since they will dictate the temperature at which n-paraffins first self-associate leading to crystal nucleation.

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Section: ■ Results and Discussionmentioning

confidence: 99%

Section: ■ Results and Discussionmentioning

confidence: 99%

Physicochemical Approach to Pour Point Depressant Treatment of Waxy Crudes

et al. 2023

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“…SARA composition of vacuum residue fractions was measured by patented method SAR-AD and LNB in house method. More details about both SARA procedures are presented in [31,32].…”

Section: Physical and Chemical Characterization Of Studied Oilsmentioning

confidence: 99%

Effect of Crude Oil Quality on Properties of Hydrocracked Vacuum Residue and Its Blends with Cutter Stocks to Produce Fuel Oil

et al. 2023

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The production of heavy fuel oil from hydrocracked vacuum residue requires dilution of the residue with cutter stocks to reduce viscosity. The hydrocracked residue obtained from different vacuum residue blends originating from diverse crude oils may have divergent properties and interact with the variant cutter stocks in a dissimilar way leading to changeable values of density, sediment content, and viscosity of the obtained fuel oil. H-Oil hydrocracked vacuum residues (VTBs) obtained from different crude blends (Urals, Siberian Light (LSCO), and Basrah Heavy) were diluted with the high aromatic fluid catalytic cracking (FCC) light cycle, heavy cycle, and slurry oil, and the low aromatic fluid catalytic cracking feed hydrotreater diesel cutter stocks and their densities, sediment content, and viscosity of the mixtures were investigated. Intercriteria analysis evaluation of the data generated in this study was performed. It was found that the densities of the blends H-Oil VTB/cutter stocks deviate from the regular solution behavior because of the presence of attractive and repulsive forces between the molecules of the H-Oil VTB and the cutter stocks. Urals and Basrah Heavy crude oils were found to enhance the attractive forces, while the LSCO increases the repulsive forces between the molecules of H-Oil VTBs and those of the FCC gas oils. The viscosity of the H-Oil VTB obtained during hydrocracking of straight run vacuum residue blend was established to linearly depend on the viscosity of the H-Oil vacuum residue feed blend. The applied equations to predict viscosity of blends containing straight run and hydrocracked vacuum residues and cutter stocks proved their good prediction ability with an average relative absolute deviation (%AAD) of 8.8%. While the viscosity was found possible to predict, the sediment content of the blends H-Oil VTBs/cutter stocks was recalcitrant to forecast.

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“…In order to evaluate the relation of specific gravity, molecular weight, and SARA composition data to the crude oil refractive index, an intercriteria analysis (ICrA) evaluation of the data in Table S4 was performed. Details about the application of ICrA in petroleum chemistry and processing and its meaning can be found in our recent studies [61,62]. µ = 0.75 ÷ 1.00 and υ = 0 ÷ 0.25 denote a statistically meaningful significant positive relation, where the strong positive consonance exhibits values of µ = 0.95 ÷ 1.00 and υ = 0 ÷ 0.05, and the weak positive consonance exhibits values of µ = 0.75 ÷ 0.85 and υ = 0.2515 ÷ 0.1525.…”

Section: Prediction Accuracy Of the Refractive Index Of Crude Oils By...mentioning

confidence: 99%

Prediction of Refractive Index of Petroleum Fluids by Empirical Correlations and ANN

et al. 2023

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The refractive index is an important physical property that is used to estimate the structural characteristics, thermodynamic, and transport properties of petroleum fluids, and to determine the onset of asphaltene flocculation. Unfortunately, the refractive index of opaque petroleum fluids cannot be measured unless special experimental techniques or dilution is used. For that reason, empirical correlations, and metaheuristic models were developed to predict the refractive index of petroleum fluids based on density, boiling point, and SARA fraction composition. The capability of these methods to accurately predict refractive index is discussed in this research with the aim of contrasting the empirical correlations with the artificial neural network modelling approach. Three data sets consisting of specific gravity and boiling point of 254 petroleum fractions, individual hydrocarbons, and hetero-compounds (Set 1); specific gravity and molecular weight of 136 crude oils (Set 2); and specific gravity, molecular weight, and SARA composition data of 102 crude oils (Set 3) were used to test eight empirical correlations available in the literature to predict the refractive index. Additionally, three new empirical correlations and three artificial neural network (ANN) models were developed for the three data sets using computer algebra system Maple, NLPSolve with Modified Newton Iterative Method, and Matlab. For Set 1, the most accurate refractive index prediction was achieved by the ANN model, with %AAD of 0.26% followed by the new developed correlation for Set 1 with %AAD of 0.37%. The best literature empirical correlation found for Set 1 was that of Riazi and Daubert (1987), which had %AAD of 0.40%. For Set 2, the best performers were the models of ANN, and the new developed correlation of Set 2 with %AAD of refractive index prediction was 0.21%, and 0.22%, respectively. For Set 3, the ANN model exhibited %AAD of refractive index prediction of 0.156% followed by the newly developed correlation for Set 3 with %AAD of 0.163%, while the empirical correlations of Fan et al. (2002) and Chamkalani (2012) displayed %AAD of 0.584 and 0.552%, respectively.

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SAR-AD Method to Characterize Eight SARA Fractions in Various Vacuum Residues and Follow Their Transformations Occurring during Hydrocracking and Pyrolysis

Cited by 4 publications

References 94 publications

Physicochemical Approach to Pour Point Depressant Treatment of Waxy Crudes

Physicochemical Approach to Pour Point Depressant Treatment of Waxy Crudes

Effect of Crude Oil Quality on Properties of Hydrocracked Vacuum Residue and Its Blends with Cutter Stocks to Produce Fuel Oil

Prediction of Refractive Index of Petroleum Fluids by Empirical Correlations and ANN

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