Quantitative Lithofacies Characterization and Log-Based Identification of Organic-Rich Shales from the First Member of the Upper Cretaceous Qingshankou Formation in the Southern Songliao Basin of Northeast China

Lithofacies characterization of organic-rich shales constitutes the essential foundation for sweet spot evaluation in lacustrine shale oil systems. This study targets the first member of the Upper Cretaceous Qingshankou Formation (K₂qn¹) in the southern Songliao Basin. Based on systematic core description of 908 m of core from eight cored wells, combined with 123 total organic carbon (TOC) measurements, 47 whole-rock X-ray diffraction (XRD) analyses, 29 major- and trace-element analyses, and six maceral identification datasets (≥500 organic particles counted per sample), together with conventional well log data from 75 wells (measured vitrinite reflectance $R_o$ = 0.34%–1.38%, mean = 0.94%), we establish an integrated lithofacies classification scheme incorporating the TOC as a classification parameter and develop a log-based lithofacies identification workflow. Eight lithofacies are recognized within K₂qn¹ across the study area, of which three are organic-rich. The high-TOC clay-rich mudstone-grade laminated shale deposited in a deep lake setting (LF-A; mean TOC = 3.18%, clay minerals ≥50%, formed under saline and strongly anoxic-euxinic conditions; mean paleosalinity = 8.06‰, V/(V + Ni) = 0.75–0.97) and the high-to-moderate-TOC felsic mudstone-grade laminated shale deposited in a semi-deep lake setting (LF-B; mean TOC = 2.18%, felsic minerals ≥50%, formed under brackish-to-saline anoxic conditions; mean paleosalinity = 5.10‰, V/(V + Ni) = 0.70–0.84) constitute the dominant organic-rich lithofacies. From Y1 to Y3, the cumulative thickness of organic-rich lithofacies expands from approximately 10 m to approximately 25 m. Areally, the mean TOC increases systematically from 1.65% in the southern delta-front zone to 2.74% in the northern deep lake center, reflecting an enrichment pattern governed primarily by paleoproductivity and modulated jointly by preservation conditions and terrigenous dilution. The log-based identification workflow, established by integrating a modified $\Delta$logR method with multiple linear regression, achieves a TOC prediction coefficient of determination of $R^2=0.86$ in the calibration well and lithofacies identification accuracies ranging from 64.6% to 94.0% in validation wells, with the highest performance observed in the delta-front facies zone. These results provide quantitative constraints for the genetic interpretation and log-based identification of organic-rich lacustrine shales.