Differentiation of oil samples by isomeric composition of paraffins using cluster analysis methods

Abstract

A new method is proposed for controlling the sources of oil samples by chemical composition for their differentiation, identification and establishment of their origin (specific wells of the operating field) using the agglomerative hierarchical data clustering and applying the J. Ward algorithm. The initial information is the data on the composition and relative contents of n-paraffins С17Н36 ÷ С34Н70, isoprenoids of pristane С19Н40 and phytane С20Н42 in oil samples obtained by selected-ion monitoring gas chromatography/mass spectrometry. The solution to the problem was carried out in the absence of the information about the magnitude of the total uncertainty in the data, without using the standard samples for their assessment and without the preliminary assumption of the number of expected clusters. The proposed technique’s possibilities were illustrated by the results of 20 × 27 data matrix processing based on the relative paraffin content in 27 encrypted anonymous samples. As an outcome, three clusters were identified, each of which included objects sampled from the specific well. Differentiating the sources of the samples using the traditional methods by comparing the amounts of n-paraffins and isoprenoids proved to be impossible. Due to the inevitable errors in the analysis results and the possible changes in the composition of the recovered oil, the values of the relative contents of paraffins in the oil samples from all three wells overlap and the sources remain indistinguishable. The newly proposed method made it possible to solve the differentiation problem of oil samples in organic geochemistry and environment control which are complicated by the wide variability of the composition of oil samples, the lability of petroleum system under the influence of natural and technogenic factors and the absence of the estimate of the actual errors in the data.