Abstract:

The lithofacies of shale oil within the Dongying Sag of the Jiyang Depression are distinguished by their complex lithology, strong heterogeneity, and marked regional distribution variances. Current logging methods inadequately identify and evaluate the lithofacial characteristics of shale oil in this region. This study delves into the lithofacies characteristics of the upper submember of Chunhuazhen Formation of the fourth member of the Shahejie Formation in Dongying Sag, employing core calibration logging integrated with core, thin section, experimental analysis, and testing data. Utilizing the “three terminal elements and four elements” shale lithofacies partitioning scheme as a guiding principle, this research selects responsive characteristics of different lithofacies logging and sensitive parameter logging curves to develop an appropriate shale oil logging lithofacies partitioning method. The approach combines stratification, clustering through Agglomerative Hierarchical Clustering（AHC）, Fisher discriminant analysis, wavelet frequency extraction, and genetic optimization neural networks to discern the rock composition, sedimentary structure, rock texture, and organic matter content of different lithofacies. This methodology addresses the challenges posed by complex lithology, limited logging resolution, incomplete special logging data, and inadequate Total Organic Carbon（TOC）model accuracy. By identifying the “four characteristics” of lithofacies, the study establishes a quantitative logging identification method and technology for shale oil lithofacies in Dongying Sag, pinpointing concentrated lithofacies segments. The findings provide a critical geological basis for the large-scale exploration and development of shale oil in the region.

Key words: the upper submember of Chunhuazhen Formation of the fourth member in Dongying Sag, shale oil lithofacies, rock structure, bedding structure, organic carbon content, logging evaluation method