Oil-Source Correlation in the Ordovician and Carboniferous Strata from the Southwestern Ordos Basin (China):...

Recently, oil and gas shows have been identified in both the Carboniferous Yanghugou Formation and the Ordovician Wulalike Formation in the southwestern Ordos Basin. However, oil-source correlation in this area is challenging because conventional biomarker parameters are inherently limited, and the two source rock systems exhibit pronounced maturity differences. As a result, traditional biomarker-based approaches often suffer from ambiguity and low reliability. To address these limitations, this study introduces multivariate statistical methods, including hierarchical cluster analysis (HCA) and Q- and R-mode factor analysis (FA). A total of 31 biomarker parameters from 47 source rocks and crude oil samples collected from Wells YT1, YT2, and YT3 were systematically integrated. On this basis, four composite indices were established: the Maturity Index (MI), Organic Matter Origin Index (OMOI), Water Salinity Index (WSI), and Organic Matter Source Index (OMSI). These indices were applied to construct oil-source correlation diagrams, thereby reducing the influence of single-parameter limitations and maturity differences on oil-source identification. The results indicate that the Yanghugou Formation source rocks are characterized by high organic matter abundance (average total organic carbon (TOC) of 4.29%), low maturity, and Type II₂ kerogen deposited in a paralic facies, whereas the Wulalike Formation exhibits lower TOC values (average 0.31%) and represents highly mature Type I marine source rocks. Multivariate statistical analysis shows that the biomarker characteristics of the Yanghugou oil sands are intermediate between those of the two source rock systems. The MI-OMOI diagram further demonstrates that the Yanghugou oil sands have a mixed origin, with contributions from both the Yanghugou and Wulalike Formations, while the Wulalike oils are predominantly self-sourced and self-reservoired. Overall, the composite indices method established in this study effectively improves oil-source identification accuracy under conditions of strong maturity contrast and provides new insights for hydrocarbon exploration in structurally complex areas.