Comprehensive logging identification method of shell limestone fractures in the Lower Jurassic Da'anzhai Member in the Dongpo area of the Western Sichuan Depression

Shell limestone tight reservoirs are developed in the Lower Jurassic Da'anzhai Member of the Sichuan Basin. Fractures are important storage spaces and seepage channels in shell limestone tight oil reservoirs and are key factors for high oil and gas production in wells. In this study, considering the shell limestone reservoir of the Da'anzhai Member on the eastern slope of the Western Sichuan Depression as an example, we used multiple fracture interpretation models based on conventional logging to identify fractures. Our results show that: (1) the reservoirs in the Da'anzhai Member primarily showed low-angle structural fractures, mostly filled with calcite. The effective linear density of fractures in each well varied greatly, which primarily explains the strong heterogeneity of tight reservoirs. (2) The logging response characteristics of the fractured and non-fractured segments differ considerably, and the fractured segment shows the characteristics of high acoustic time difference and low resistivity. (3) The well log recombination method, principal component analysis method, multivariate discriminant method, backpropagation (BP) neural network method, and K-nearest neighbor (KNN) algorithm are used for fracture identification. According to the consistency of the fracture identification results with the core observation results, we established a comprehensive fracture identification standard using the multi-logging method. In this study, we established a fracture identification method based on the coupling of multiple linear and nonlinear multi-logging models through core calibration, which avoids the errors and uncertainties caused by using a single method. Additionally, this study provides a foundation for the control factors and the prediction of fracture distribution.