Application of multivariate modelling to detect hydrocarbon components for optimal discrimination between two source rock types

The present study presents a multivariate procedure to reveal light hydrocarbon components which significantly distinguish between source rock thermal extracts. The two source rocks included in this study are the marine shales of the Late Jurassic Spekk Formation and the coals and paralic shales of the Early Jurassic Åre Formation offshore Mid-Norway. Because of the large number of components in the C4–C13 hydrocarbon fraction of source rock extracts a multivariate approach was required. The procedure consists of three distinct steps: (1) Principal component analysis of the whole data set for detection of non-significant individual components. This reduced the number of individual components from 46 to 22. (2) Separate principal component analysis of the two source rocks (Åre and Spekk) to detect outliers. (3) Principal component modelling of each of the two source rocks after deletion of outliers and non-discriminating variables to detect those hydrocarbon components which are most significant and robust for the separation of the two source rocks. The resulting model shows that there is a definitive compositional difference between the source rocks investigated.