Multiscale Characterization, Prediction, and Discrete Fracture Network (DFN) Modeling of Natural Fractures in the Tight Sandstone Reservoir of Sub-member 1, Chang 8 Member, Ning 218 Well Block, Zhengning Oilfield, Southern Ordos Basin

This study focuses on the Chang 8 tight sandstone reservoir in the Ning 218 well block of the Zhengning Oilfield, southern Ordos Basin. By integrating core, thin-section, logging, and seismic data, and based on the fine identification of multi-scale fractures, the fracture development characteristics were systematically characterized. A multi-scale fracture modeling approach was developed, and ultimately a three-dimensional Discrete Fracture Network (DFN) model for multi-scale fractures in the Chang 8 reservoir of the Ning 218 well block was established. Firstly, the distribution of large-scale natural fractures was identified using the VarAntAntPas post-stack seismic attribute volume. Statistical analysis determined the seismic fracture recognition resolution in the study area to be 300 m. For fractures longer than 300 m (large-scale fractures), a deterministic modeling method was applied to construct their DFN model. For fractures with lengths less than 300 m, a three-dimensional fracture intensity model was built by integrating log-derived fracture intensity interpretations with multiple fracture-related seismic attributes, employing an artificial neural network combined with cokriging simulation. Subsequently, using the fracture intensity model as a constraint and selecting appropriate fracture statistical parameters, a stochastic modeling method was adopted to establish the small-scale fracture DFN model. Finally, the two-scale fracture models were merged to form a complete multi-scale DFN model. The established multi-scale fracture model is consistent with existing geological understanding and can provide a reliable geological basis for increasing reserves and production of tight oil and gas in the Ning 218 well block.