Logging Identification Methods for Oil-Bearing Formations in the Chang 6 Tight Sandstone Reservoir in the Qingcheng Area, Ordos Basin

The Chang 6 sandstone reservoir of the Upper Triassic Yanchang Formation in the Ordos Basin is one of the tight-oil-rich intervals in the basin. Owing to the strong heterogeneity and complex lithology of the Chang 6 reservoir, lithology and fluid identification have become more challenging, hindering exploration and development. This study focused on the Chang 6 member in the Qingcheng area of the Ordos Basin to systematically analyze the lithology, physical properties, and oil-bearing properties of the Chang 6 reservoir. We adopted the method of normalized superposition of neutron and acoustic time-difference curves, the method of induced conductivity–porosity–density intersection analysis, the method of superposition of difference curves (Δφ), and the induced conductivity curve. Our results indicated that the method of normalized superposition of neutron and acoustic wave time-difference curves could quickly and effectively identify the lithologies of tight fine sandstone, silty mudstone, mudstone, and carbonaceous mudstone. The induced conductivity–porosity–density cross-plot could be used to effectively identify oil and water layers, wherein the conductivity of tight oil layers ranged from 18 to 28.1 mS/m, the density ranged from 2.42 to 2.56 g/cm 3 , the porosity was more than 9.5%, and the oil saturation was more than 65%. Based on the identification of tight fine sandstone using the dual-curve normalized superposition method, the oil layer thickness within the tight fine sandstone could be effectively identified using the superposition of difference curves (Δφ) and induced conductivity curves. Verified by oil-bearing reservoir data from the field test, the overall recognition accuracy of the plots exceeded 90%, effectively enabling the identification of reservoir lithology and fluid types and the determination of the actual thickness of oil layers. Our results provide a reference for predicting favorable areas in the study area and other tight reservoirs.