Abstract: The present disclosure refers to the use of very high resolution mass spectrometry analysis methodology in combination with the use of multivariate calibration models to predict Total Acidity Number (TAN). The models are built from data of total abundance value with the application of machine learning methods for regression.

Abstract: The present invention relates to the field of organic geochemistry wherein a method for accessing high molecular mass aromatic hydrocarbons and diamondoids was developed from comprehensive characterization carried out by high resolution spectrometry coupled with the atmospheric pressure photoionization source (APPI FT-ICR MS). Based on the compositional profile of diamondoids and aromatic hydrocarbons, it is possible to quickly and robustly classify oils in relation to their origin and thermal evolution. It is verified that the compositional detail provided by the APPI(+)-FT-ICR MS analysis allowed the development of new molecular indicators, accessed without the need for any preliminary separation technique, in order to become a powerful tool for prospecting the use of oils exploited for specific purposes.

Abstract: The invention teaches a method proposing two new indices for evaluating thermal evolution in oils from different basins and organofacies. The first index is based on the distribution ratio of high molecular weight sulfur compounds, belonging to the DBE 6 (benzothiophene) and DBE 9 (dibenzothiophene) series. The second index, called TEI, was created from the profile of aromatic hydrocarbons and molecules containing N, O and S. Both parameters were obtained from the direct characterization of the oils, by using the photoionization at atmospheric pressure (APPI) technique combined with Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS).

Abstract: The present invention relates to a method for detecting and mapping the spatial distribution of organic compounds aiming to understand how such organic compounds are distributed on the surfaces of reservoir rocks subjected to injection fluids for oil recovery purposes. The DESI and LAESI techniques may be used in the analysis of rocks from trials of oil recovery in small or large scale. Furthermore, both techniques may be applied in the analysis of compounds present on the surfaces of minerals from aquatic environments.