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 Ro = 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 ΔlogR method with multiple linear regression, achieves a TOC prediction coefficient of determination of R2=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.