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A database of 140 diesel fuels having cetane numbers in the range of 10–70 points; densities at 15 °C; and distillation characteristics according to ASTM D-86 T 10%, T 50%, and T 90% was used to develop new procedures for predicting diesel cetane numbers by application of the least-squares method (LSM) using MAPLE software and an artificial neural network (ANN) using MATLAB. The existing standard methods of determining cetane-index values, ASTM D-976 and ASTM D-4737, which are correlations of the cetane number, confirmed the earlier conclusions that these methods predict the cetane number with a large variation. The four-variable ASTM D-4737 method was found to better approximate the diesel cetane number than the two-variable ASTM D-976 method. The developed four cetane-index models (one LSM and three ANN models) were found to better approximate the middle-distillate cetane numbers. Between 4% and 5% of the selected database of 140 middle distillates were samples with differences between their measured cetane numbers and the cetane-index values predicted by the four new procedures was higher than the specified reproducibility limit in the standard for measuring cetane number, ASTM D-613. In contrast, the cetane-index values calculated in accordance with standards ASTM D-976 and ASTM D-4737 demonstrated that 18% and 16% of the selected database of 140 middle distillates, respectively, were samples with differences between their measured cetane numbers and predicted cetane-index values higher than the specified reproducibility limit in standard ASTM D-613. The ASTM D-4737 method, LSM, and three ANN models were tested against 22 middle distillates not included in the database of 140 diesel fuels. The LSM cetane index showed the best cetane-number prediction capability among all of the models tested.

Twenty-two crude oils around the world, from which 19 are processed in the LUKOIL Neftohim Burgas (LNB) refinery, were characterized in the LNB research laboratory by measuring 67 properties. These 22 crude oils included light low sulfur, light sulfur, intermediate low sulfur, intermediate sulfur, intermediate high sulfur, heavy high sulfur, and extra heavy extra high sulfur crudes. A new mathematical approachthe intercriteria analysiswas employed to study the relations between the petroleum properties. It was found that the petroleum properties, density, and sulfur content, along with the crude oil simulated distillation, seem to be capable of providing the same information as that from the full assay of a crude oil. Crude oils containing insoluble asphaltenes (self-incompatible oils) were found to have a high content of low aromaticity naphtha and kerosene. It was found that the asphaltene solubility correlated with the asphaltene hydrogen content. The oil solubility power was found to correlate with the oil saturate content. The oil colloidal stability seems to be controlled by the following rule: "like dissolves like". The higher the aromaticity of the asphaltenes, the higher the aromaticity of the oil is required to keep the asphaltenes in solution. The processing of blends of oils which are incompatible or nearly incompatible may deteriorate the performance of the dewatering and desalting in the refinery, which consequently may damage the equipment due to accelerated corrosion, entailed by salt deposition. The processing of blends of oils, which are incompatible, not always can be related to an increased fouling.