Sedimentary structural characteristics and well logging identification method for shale strata in the First Member of the Qingshankou Formation, Gulong Sag

ObjectiveIn order to establish a detailed classification scheme and quantitative characterization method for the logging of shale sedimentary structure, and to support the efficient exploration and development of shale oil, Methodsthe continental shale strata of the First Member of the Qingshankou Formation (K2qn1) in the Gulong Sag, Songliao Basin were taken as an example. Based on core and thin-section observations, whole-rock mineral X-ray diffraction, and electrical imaging logging data, the sedimentary structural characteristics under lithological variations were clarified, and a quantitative well logging identification method for sedimentary structures applicable to continental shale strata was established. ResultsThe results showed that the differences in sedimentary structural characteristics under different lithologies in K2qn1 shale strata were primarily reflected in the mineral composition of the laminae and the thickness variation of the bedding (texture). Based on the single-layer thickness, sedimentary structure types could be divided into laminated (single-layer thickness ≤ 1 cm), bedded (single-layer thickness is 1-10 cm), and massive (single-layer thickness ≥ 10 cm). Leveraging the high-resolution advantage of electrical imaging logging slice images, the layer interfaces in the slices were identified through edge detection and Hough transform. The sedimentary structure types were quantitatively classified based on layer interface thickness. This method not only overcame the challenge of insufficient characterization accuracy for millimeter-scale laminae in traditional dynamic and static imaging logging but also addressed the limitation of previous methods where laminae density could not effectively distinguish between bedded and laminated sedimentary structures within a well logging unit window length. ConclusionOverall, the logging identification method for sedimentary structures based on electrical imaging slices proposed in this study demonstrates high accuracy and broad applicability, providing robust support for the subsequent evaluation of continental shale reservoir effectiveness.