The forecast of failure time of unstable slope and the definition of early warning threshold are very important for preventing landslide disaster and reducing its losses. Based on the monitoring curve of unstable slope deformation varying with time, the mathematical models are used to accurately describe the nonlinear creep behavior in the initial creep stage and the unstable creep stage of unstable slope and a forecasting method for creep landslide is proposed. In addition, this study examines an improved tangential angle criterion obtained by a new forecasting method. The results show that the initial creep stage of unstable slope can not be neglected for forecasting the failure time. The initial creep velocity v0 and the viscoelastic hysteresis coefficientξof the slope are determined at initial creep stage, which together control the creep process of the unstable slope. Moreover, in the secondary creep stage, there is an inverse relationship between the velocity and the critical tangential angle. According to the average velocity of the secondary creep stage, the early warning criterion of the landslide tangential angle is proposed. Combined with the forecast parameters of the unstable slope, comparative analysis of the critical tangential angle warning criterion and an improved tangential angle criterion, the early warning and forecasting system of landslide with creep characteristic is established. This system is applied to the early warning and forecasting analysis of reported soil and rock landslides cases with creep characteristics. The forecasting effect and applicability of the new method are studied in order to make it a better supplement to the early warning strategy of landslide.

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In time-lapse seismic analysis, the Zoeppritz equations are usually used in the time-lapse amplitude variation with offset (AVO) inversion and then combined with a rock-physical model to estimate the reservoir-parameter changes. The real-life reservoir is a two-phase medium that consists of solid and fluid components. The Zoeppritz equations are a simplification, assuming a single-phase solid medium, in which the properties of this medium are estimated by effective parameters from the combined components. This means that the Zoeppritz equations cannot describe the characteristics of the seismic reflection amplitudes in the reservoir in an accurate way. Therefore, we develop a method for time-lapse AVO inversion in two-phase media using the Bayesian theory to estimate the reservoir parameters and their changes quantitatively. We use a reflection-coefficient equation in two-phase media, a rock-physical model, and the convolutional model to build a relationship between the seismic records and reservoir parameters, which include porosity, clay content, saturation, and pressure. Assuming that the seismic-data errors follow a zero-mean Gaussian distribution and that the reservoir parameters follow a four-variable Cauchy prior distribution, we use the Bayesian theory to construct the objective function for the AVO inversion, and we also add a model-constraint term to compensate the low-frequency information and improve the stability of the inversion. Using the objective function of the AVO inversion and the Gauss-Newton method, we derived the equation for time-lapse AVO inversion. This result can be used to estimate the reservoir parameters and their changes accurately and in a stable way. The test results from the feasibility study on synthetic and field data proved that the method is effective and reliable.