The ultra-deep tight sandstone reservoirs of the Lower Cretaceous Bashijiqike Formation in the Kelasu Structural Belt, Kuqa Depression, have been significantly influenced by intense lateral tectonic compression since the late Himalayan period (ca. 5 Ma), resulting in the formation of fractured tight sandstone reservoirs. Deciphering the control of the stress-strain state on reservoir quality is crucial for establishing a predictive model. This study systematically investigates the impact of stress state and strain degree on reservoir quality through thin-section identification, analysis of rock mechanical parameters, triaxial stress tests, and rock stress-strain experiments on samples from typical structural positions. The results show that: (1) Sandstones in the hanging wall of the Kelasu Fault experienced weak tectonic compression, characterized by low paleo-stress and present-day stress, minimal strain, and relatively high porosity (10%-14%). (2) Footwall sandstones exhibit higher stress and strain than those in the hanging wall, with notable spatial variations: proximal footwall areas display low vertical stress due to thrusting from the hanging wall, forming collapse structures with weak compression, good physical properties (porosity ~ 10%), and underdeveloped fractures; distal footwall areas show concentrated stress accumulation and the strongest relative/effective compressive stress. These areas develop intensely compressed imbricated and pop-up structures with high strain, low porosity (< 5%), and well-developed fractures. (3) The eastern Keshen area in the footwall has long been subjected to deep burial and intense compression, exhibiting higher strain, relatively lower porosity, and more developed fractures than the western Dabei and Bozi areas at similar structural positions. These findings reveal how stress-strain variations, controlled by structural positioning, govern reservoir quality. This supports a new genetic model for reservoir formation in the Kelasu Structural Belt and provides key geological insights for reservoir prediction in future natural gas exploration and development.
Wang et al. (Sat,) studied this question.