Sedimentary structure characteristics and logging identification method for the first member of Qingshankou Formation shale strata in Gulong sag

[Objective] The fine classification and quantitative characterization of sedimentary structure types is a crucial issue in the exploration and development of shale oil. [Methods] To this end, taking the continental shale strata of the first member of Qingshankou Formation (K2qn1) in Gulong sag of Songliao Basin as an example, based on core and thin section observations, whole-rock mineral X-ray diffraction and electrical imaging logging data, the sedimentary structure characteristics under lithological differences were clarified, and a quantitative logging identification method for sedimentary structures applicable to continental shale strata was established. [Results] The result shows that the differences in sedimentary structure characteristics under different lithologies of K2qn1 shale strata are mainly reflected in the mineral composition of the laminae and the thickness variation of the bedding (texture). The sedimentary structure types can be divided into laminar (single layer ≤1 cm), lamellar (1 cm < single layer < 10 cm), and massive (single layer ≥ 10 cm) based on the size of the single-layer thickness. Relying on the high resolution advantage of electrical imaging logging slice image, the layer interface in electrical imaging slice is identified by edge detection and Hough transform, and the sedimentary structure type is quantitatively divided based on the thickness of the layer interface. This method not only overcomes the problem of insufficient characterization accuracy of millimeter-scale laminae in traditional dynamic and static imaging logging images, but also compensates for the drawback that the previous use of laminae density cannot effectively divide the lamellar and laminar sedimentary structures within the logging unit window length. [Conclusion] Overall, the sedimentary structure logging identification method based on electrical imaging slices proposed in this paper has high accuracy and good generalization, which can provide strong support for the subsequent continental shale reservoir effectiveness evaluation.