Shale oil development is facing challenges in accurately quantifying oil-bearing properties and determining key parameters. In this study, focusing on frozen core samples from the Paleogene Hetaoyuan Formation in the Nanyang Sag, Nanxiang Basin, we improve the experimental method for two-dimensional nuclear magnetic resonance (2D NMR). Based on systematic oil-water calibration experiments, we conduct 2D NMR experiments, Rock-Eval pyrolysis, multi-step temperature-programmed pyrolysis, and azeotropic distillation on the samples. The experimental results reveal that the crude oil and pore water with different occurrence states in shales can be quantitatively characterized by determining the 2D NMR T₁-T₂ spectrum-based evaluation chart for shale oil, combined with calibration experiments. The results indicate that the contents of free and adsorbed oil calculated using 2D NMR slightly exceed those of free and adsorbed hydrocarbons determined by temperature-programmed pyrolysis, with strong positive correlations observed between the counterparts. These findings demonstrate that 2D NMR enables more effective hydrocarbon retention. In contrast, the effective porosity and oil saturation calculated using 2D NMR exhibit relatively weak correlations with gas logging-derived porosity and azeotropic distillation-derived oil saturation, respectively, reflecting the influence of sample properties and experimental methods. 2D NMR technology offers the effective retention of light hydrocarbons in shale oil. Meanwhile, this technology can yield oil-water saturation and multiple key parameters for quantitative shale oil evaluation, including the contents of free oil, adsorbed oil, and pore water. These advantages highlight the significant technical advantages and great application potential of 2D NMR in the geological assessment of shale oil.

The genetic identification of hydrocarbons in complex hybrid petroleum systems remains challenging due to overlapping geochemical signatures caused by multi-source inputs and superimposed geological processes. Traditional biomarker-based methodologies often struggle to decouple these nonlinear interactions, leading to interpretive uncertainties in source correlation, thermal maturity assessment, and secondary alteration characterization. This study introduces an unsupervised machine learning framework leveraging manifold learning to resolve these challenges within the hybrid petroleum system of the eastern Junggar Basin. We employed Uniform Manifold Approximation and Projection (UMAP) to analyze high-dimensional molecular fingerprints of hydrocarbons. This approach allowed us to systematically disentangle the genetic signals influenced by multiple factors, including source material, thermal evolution, mixing, biodegradation, and migration-induced phase fractionation. Results identify two primary oil families: Permian-derived and Jurassic-sourced oils, each exhibiting unique evolutionary pathways shaped by differential thermal maturation and post-generation alterations. Spatial mapping of these genetic types reveals systematic trends in hydrocarbon accumulation, highlighting preferential migration pathways and high-potential exploration targets. This workflow not only advances the interpretation of hybrid petroleum systems but also establishes a transferable framework for optimizing exploration strategies in geochemically complex basins. The integration of machine learning with petroleum geochemistry provides a promising pathway to reconcile multi-proxy datasets, reduce interpretive subjectivity, and enhance predictive accuracy in hydrocarbon genetic studies.

Due to the complexity of the lithofacies associated with shale oil in saline lacustrine basins, the differences of shale oil occurrence state and its controlling factors in different lithofacies are not completely clear. This hinders efficient shale oil exploration and development. We investigated the shale oil in the Permian Lucaogou Formation in the Jimusar Sag, Junggar Basin, China, based mainly on sequential solvent extraction, petrological, organic geochemical, and nuclear magnetic resonance techniques. The fluidity of extractable organic matter decreased from the first extract to the fourth extract, which was caused by the gradual decrease in the contents of saturated and aromatic hydrocarbons, and gradual increase in the contents of NSO compounds and asphaltenes. The contents of free hydrocarbons (the first and second extracts) and adsorbed hydrocarbons (the third and fourth extracts) are very different among the lithofacies. The free hydrocarbon ratios in the siltstones and carbonate rocks are >70% and the main pore throats are >1 μm in size, corresponding to the best sweet spots. The contents of free hydrocarbons in the laminated silty mudstones and shales with bedding fractures are >50%, which are also available. The free hydrocarbons in the siltstones and carbonates are saturated with migrated hydrocarbons, with the contents being more affected by the physical properties of rocks. In contrast, the free hydrocarbons in the mudstones are mainly self-generated and -stored, and their contents are controlled by total organic carbon contents and maturity. For the adsorbed hydrocarbons, the contents in all lithofacies are controlled mainly by the total organic carbon contents. The biomarker parameters record a slight increase in maturity from the fourth to the first extract. The ∑C_22–/∑C₂₃₊ values of n-alkanes in the third extract are the lowest, because carbonate minerals tend to capture long-chain n-alkanes. The sequential solvent extraction method provides new insights into the occurrence state and molecular geochemical characteristics of lacustrine shale oil in different lithofacies. Future exploration should focus on siltstones and carbonate rocks with a relatively high proportion of the first extract (free hydrocarbons occurring in large pores and fractures), and mudstones with a relatively high proportion of the second extract (free to adsorbed hydrocarbons occurring in matrix pores) that are suitable for hydraulic fracturing to aid production.