Abstract
In this study several major source rocks: Kazhdumi, Pabdeh, and Gurpi formations, along with crude oils from the Asmari and Bangestan reservoirs in the Gachsaran oilfield, southwestern Iran, were investigated from the organic geochemistry point of view. Results indicate that the Kazhdumi and Pabdeh formations have excellent generation potential and are mature and immature source rocks, respectively. In contrast, the Gurpi Formation has lower petroleum generation potential. The organic matter in the Kazhdumi and Pabdeh formations in the neighboring synclines within the Gachsaran oilfield is in the late and peak oil generation stages, respectively. SARA composition by Liquid Chromatography performed on four crude oils produced from these source rocks suggest a paraffinic-naphthenic composition. The source rocks had carbonate and shale lithology. Distinct biomarkers point to an open marine environment characterized by marine kerogen Type II and mixed Types II/III deposited under anoxic-suboxic depositional conditions, although. The presence of relatively high amounts of oleanane in the oils points to contribution from a terrigenous source. Based on biomarkers, the four oils exhibit similar thermal maturity, which is equivalent to the primary stage of oil generation. The star diagrams of various normal alkanes and biomarker ratios show that the four crude oil have high similarities, which suggests a single source origin. Nonetheless, utilizing different ML methods of K-means Clustering, Fuzzy C-means clustering (FCM), Comptlayar Neural Network, Construction of agglomerative clusters, and the obtained dendrogram all suggest that there are two oil families in the Gachsaran oil field. Furthermore, geochemical parameters including specific biomarkers denote the contribution of the Kazhdumi and Pabdeh formations in the Gachsaran oil field whereby charges of mixed origins at different reservoir horizons of Asmari and Bangestan can be identified. Ultimately, two scenarios for the presence of oleanane in Bangestan reservoir are envisaged: 1) connectivity of the Asmari and Bangestan reservoirs as a result of natural fracturing, and 2) emplacement of the Pabdeh Formation near the vicinity of the Bangestan reservoir as a result of thrust faulting. Overall, this study demonstrated that integration of data analytics (ML) methods with conventional geochemical techniques can precisely delineate the correlation between the generated oil and the source rocks. • Geochemical analysis performed on two rarely studied major source rocks in Middle East: kazhdumi and Pabdeh Formations. • Several machine learning (ML) algorithms were implemented to identify existing oil families from these two source rocks. • These two oil families were also confirmed by detection of the Oleanane biomarker in separated oil groups.
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