The exploration of new reservoirs of oil offshore in Brazil shows that the oil has different physical properties, which significantly influence the yield and quality of production. In this sense, principal component analysis (PCA), linear discriminant analysis (LDA), and hierarchical cluster analysis (HCA) chemometric tools were successfully used to correlate the characterization properties of oils with nuclear magnetic resonance (NMR) data. A total of 48 crude oil samples from Brazil were grouped in relation to the origin, that is, fields and reservoirs of pre- and post-salt. Results of the first principal component (PC1) versus the second principal component (PC2) make up for 97.2%, a value considered satisfactory to explain the variability of samples in fields and reservoirs with HCA and LDA. The present study also showed that the transverse relaxation time obtained from low-field nuclear magnetic resonance (LF-NMR) can predict kinematic viscosity in the range of 21-1892 mm(2) s(-1) American Petroleum Institute (API) gravity between 17 degrees and 29.4 degrees, thus allowing for the classification of the 48 samples of Brazilian crude oil into medium and heavy. Besides, the oils were identified in relation to their origin. The present study describes a novel methodology to obtain the "chemical signature" of crude oil of different fields and reservoirs.