Enhancing the efficiency and accuracy of the system reliability analysis of soil slopes is of great importance in engineering design. An advanced kriging metamodel integrated with the quasi–Monte Carlo simulation (AKQMCS) is proposed for such a purpose in this paper. The proposed advanced kriging model is used as a surrogate for the limit state function (LSF) of a slope, and it is established by a sequential design of experiments, which updates the kriging model step by step, with the help of a learning function based on the entropy theory. QMCS simulation is then performed on the advanced kriging metamodel to evaluate the system failure probability of the slope. Finally, three soil slope examples, including a two-layered cohesive slope, a three-layered c-φ slope, and a single-layered sand slope, are examined to verify the capability and validity of the proposed approach. The results indicate that the proposed approach can provide a reasonable and accurate estimation of the system failure probability of slope stability with a significantly reduced number of deterministic stability analyses compared with the ordinary kriging method and the direct Monte Carlo simulation (MCS). The QMCS well outperforms the MCS in efficiency due to the low-discrepancy sequences used in the QMCS. Hence, the proposed AKQMCS provides a new and efficient tool for the system reliability analysis of soil slopes.

Shale reservoirs are characterized by extremely low permeability and high clay content. To further study the stress sensitivity of a shale reservoir, the Lower Cambrian shale in north Guizhou was utilized. Through laboratory testing, the relationships between the shale porosity and permeability and the effective stress were established, and the stress sensitivity of shale was analysed. The mechanical properties and mineral composition of this shale were studied by rock mechanics testing and X‐ray diffraction. The main factors affecting the stress sensitivity were analysed. The results show that the porosity and permeability of this shale decrease with increasing effective stress; the shale reservoir permeability damage rate is 61.44 ~ 73.93%, with an average of 69.92%; the permeability stress sensitivity coefficient is 0.04867 ~ 0.05485 MPa⁻¹, with an average of 0.05312 MPa⁻¹; and the shale reservoir stress sensitivity is strong. Shale stress sensitivity is related to the rock mineral composition and rock mechanical properties. The higher the clay content in the mineral composition, the lower the elastic modulus of shale, the higher the compressibility, and the greater the stress sensitivity coefficient.