As an important target for deep to ultra-deep carbonate oil and gas exploration, Fractured-Vuggy dolomite reservoirs have strong heterogeneity. Accurate characterization of reservoir facies is crucial for their exploration and exploitation. Three methods, including the unsupervised intelligent clustering method of improved Fuzzy C-means clustering Algorithm Based on Density Sensitive Distance and Fuzzy Partrition (FCM-DSDFP), the fusion method of Principal Components Analysis (PCA) dimensionality reduction and noise reduction, and the principle of clustering feature analysis are applied to identify reservoir facies based on logging data. Based on the PCA method, the logging response characteristics of the reservoir facies are excavated, and the fusion characterization data of dimensionality reduction and noise reduction are extracted. The FCM-DSDFP unsupervised intelligent clustering method, a model that approximates the subsurface conditions is established, and the reliability of the model is tested according to the elbow rule and silhouette coefficient. Combining drilling core observation, Fractured-Vuggy type, partially cemented Fractured-Vuggy type, Pore-Vuggy type, Pore Type I, Pore Type II, Tight Type I, and Tight Type II are divided in the Dengying Formation 4th Member. Fractured-Vuggy type, partially cemented Fractured-Vuggy type, Pore-Vuggy Type I, Pore-Vuggy Type II, Pore Type I, Pore Type II, and Tight Type are divided in the Dengying Formation 2nd Member, respectively. Two methods were applied to verify the reservoir facies identification results based on intelligent algorithms. The first method is to compare the identification results with the reservoir facies types identified by core observations (Well PT103 and PS13). The second method is to verify the recognition results of intelligent algorithms by utilizing the relationship between reservoir facies types and bitumen. The test results show that the accuracy of the reservoir level identification is higher than 0.9, and the applicability is better than the commonly used algorithms such as FCM and K-means.

Summary: Buried hills are basement uplifts beneath sediment layers that possess significant exploration potential. Using the Jianbei Slope of the Qaidam Basin in China as a case study, we systematically investigated the types and origins of fractures in deep buried-hill gas reservoirs. In our study, we synthesized various data, including experimental results, production dynamics, and both conventional and special logging with the aim of clarifying the sequence and effectiveness of fracture formation in these gas reservoirs; analyzing the impact of effective fractures on fluid migration, accumulation, and preservation; and proposing a development plan to enhance stable production. Research reveals that since the Late Paleozoic, the region has been influenced by multiple phases of tectonic stress, deep fluid dissolution, and surface weathering leaching. This has resulted in a fracture system dominated by east-west trending deep major faults, with accompanying tectonic fractures, alongside dissolution, diagenetic, and weathering-collapse fractures. Smaller fractures oriented at an angle to the maximum principal stress and fractures with normal stress lower than the compressive strength are conducive to maintaining fracture effectiveness. Fracture widths range from 0.1 μm to 343.36 μm, with effective fractures comprising 63.49% of the total. Based on aperture and permeability, effective fractures are categorized into three levels: Level I fractures (>100 μm) serve as primary migration pathways; Level II fractures (10–100 μm) are well configured with dissolution pores, forming a foundation for favorable reservoir development; and Level III fractures (micron scale) enhance reservoir storage capacity by connecting fractures. The gas-water interface in the reservoir rises rapidly and unevenly. In the I + II + III fracture combination model, fluid exhibits high-conductivity channeling, leading to rapid declines in formation pressure, quick water breakthroughs in single wells, and severe water sealing. Conversely, in the II + III fracture combination model, fluid invasion is characterized by weak-to-strong finger-like intrusion, leading to prolonged stable production. Vertically, the 20-m to 60-m interval above the bedrock weathering crust has a favorable pore-fracture configuration, making it a high-quality reservoir zone in buried hills. In addition, local thick layers of Level II microfractures within the bedrock represent potential exploration targets. Considering the differential distribution of reservoir fractures, the optimal development plan is expected to achieve a recovery rate of 28.35% by 2030.