(584b) Database for Petroleum Fractions Components Identification

Identifying the composition of petroleum is still interesting due to its importance in the world energy matrix and the global market change toward heavier crude oil as the supplies of light crude are depleted.

According to the International Energy Outlook 2016 projections, energy consumption should increase in the next years until 2040. Although there is an increase in the consumption of energy from renewable energy sources until 2040, oil consumption remains the main source of consumption. Some of the reasons for the continued high oil demand are: increased energy consumption in transportation services worldwide and lack of substitutes for petrochemical products (EIA, 2016).

Besides that, great efforts are made to achieve economically attractive oil products, due to declining supplies of conventional oil for refineries and, consequently, an elevation in heavy oil dependence. The main characteristics of heavy oil are directly related to the presence of highest molecular weight compounds such as resins and asphaltenes, which constitute the most polar fractions of these products containing sulfur, nitrogen and oxygen heteroatoms. They can deactivate catalysts in catalytic processes and increase the oil viscosity, making transport and processing more difficult (Merdrignac & Espinat, 2007).

In this context, it is necessary to know the petroleum properties and its composition to develop process models capable of achieving better optimization and management of refining processes. Some petroleum physical properties are calculated from parameters obtained from their fractions characterization, such as molecular weight. For this reason, the purpose of this study is to evaluate the fraction characteristics, classify the organic compounds in saturates, aromatics, resins and asphaltenes (SARA) and identify possible compositions, building and using a database in Excel based on molecular weight.

In the database, the organic compounds are organized in an atomic matrix of homologous series, which are a family of hydrocarbons with similar chemical properties who share the same general formula and differ by a constant molecular weight (CH₂). Then, these compounds are classified through heuristics of H/C (hydrogen/ carbon) and DBE (Double Bond Equivalent) relations. The database in Excel was developed using VBA (Visual Basic for Aplicattions) programming and the data are obtained by analytical technique of MALDI-TOF mass spectrometry. The compounds are identified by their molecular weights based on experimental error and classified according to SARA compounds.

The results show that the VBA algorithm is able to identify the possible compounds from a given sample, within the mass error range of 1 Da. This error is acceptable according to the calibration of the mass spectrometer.

EIA (U.S. Energy Information Administration), International Energy Outlook 2016, 2016. Available in: www.eia.gov/forecasts/ieo/pdf/0484(2016).pdf. Access: October 2016.

Merdrignac & Espinat, D. (2007). Physicochemical characterization of petroleum fractions: the state of the art. Oil & Gas Science and Technology, Rev. IFP, vol. 62, Nº 1, 7-32, doi:10.2516/ogst:2007002.