Classification tools based on artificial neural networks for the purpose of identification of origin of organic matter and oil pollution in recent sediments

Abstract

The distinction between autochthonous, and oil-like origin of organic matter in geological sediments can be performed on the basis of n-alkane abundance and distribution patterns, determined by gas chromatography, or on the basis of the carbon-isotope ratio (delta (CPDB)-P-13) patterns of dominant n-alkanes, determined by gas chromatography-mass spectroscopy. Here we present solutions for automatic classification of organic matter origin in geological sediments, based on artificial neural networks.