Application of transient electromagnetic data inversion in tunnel detection using Hamiltonian Monte Carlo method

ABSTRACT The transient electromagnetic (TEM) method can detect underground resistivity anomalies, and it is often used in the advanced detection of tunnels. This method can detect the low-resistance anomaly in front of the tunnel face. The resistivity of rock and groundwater is different, and groundwater usually presents a low-resistance anomaly, which can be used to determine the size and location of the water body and prevent water inrush accidents. A probabilistic statistical method is developed, which is different from the conventional optimal method. It can explore the full sampling space and obtain a set of inversion parameters to quantify the uncertainty of the result. A Hamiltonian Monte Carlo (HMC) method is devised for the inversion of TEM data in tunnels for the first time and applied to the Dadushan tunnel project in the Guizhou Province, China. In the tunnel construction site, the space of a parallel pilot tunnel is used for TEM detection of the main tunnel. The synthetic case proves that it is a faster convergence method than the conventional Markov chain Monte Carlo method and can cope with the tight tunnel construction period. On the premise that we know the location of the main tunnel cavity in advance, it is easy to judge whether the inversion results are consistent with the actual situation. The HMC provides the inversion results of the observed data and the distribution of a posteriori probability density function, and the location of the banded low-resistance anomaly is consistent with the location of the main tunnel cavity. Finally, based on the inversion results, some suggestions are made for the subsequent construction of the tunnel. These suggestions can provide an important reference for the waterproofing work of Dadushan tunnel and provide help for the safe construction of tunnel projects.