Multi-level ultra-deep fault-controlled karst reservoirs characterization methods for the Shunbei field

Abstract

Ultra-deep carbonate fault-controlled reservoirs are characterized by large burial depths, low dissolution degrees, strong heterogeneity, and limited effective well data. Accurate 3D characterization based on seismic data is essential for efficient development of this type of reservoir. However, traditional seismic prediction methods are insufficient to accurately characterize different reservoir levels in the exploration and development of fault-controlled ultra-deep reservoirs. We propose a set of improved multi-level characterization methods for fault-controlled reservoirs. The improved methods could recover seismic information obscured by strong reflections and reduce the uncertainty of seismic interpretation. This study combined seismic strong reflection suppression and sedimentary strata seismic reflection interference elimination, proposed improved inversion methods, and advanced attribute calculation methods to improve the identification accuracy of reservoirs. In particular, we proposed the karst cave carving method based on improved inversion method and karst cave enhancement algorithm, the dissolved pore zone identification method based on optimization energy envelope algorithm, and the fault-fracture zone characterization method based on optimized atomic decomposition texture contrast. These methods were thoroughly validated by theoretical 3D models and field data. The proposed multi-level characterization methods can effectively improve the identification accuracy of fault-controlled karst reservoirs, provide a benchmark for predicting similar strong heterogeneous carbonate reservoirs, and provide reliable support for further facies modeling.