Classificação de petróleos - Ferreira, Fernando Guimarães (2018)
The identification of patterns in the crude oil assay data provides useful information for crude oil properties estimation as well as for the refinery operation and logistics. The a priori information about the characteristics of a determined crude improves the logistic concerning which refineries should process it, together with pricing. This work explores data mining techniques over some characterization properties of crude oil assays, in order to group similar crude oils in an unsupervised way. The results show that the derived models are able to find patterns, clustering crudes according these properties. Afterwards, these are compared to a standard classification which is aware only about the oil crude density.