Markovian geology prediction approach and its application in mountain tunnels

A geology prediction approach based on Markov random process and Bayesian updating procedure is presented in this article. It can dynamically predict the ground conditions ahead of tunnel face in a probabilistic way with very low cost, when the tunnel face advances and new geological information is revealed. The application case study on Chuangshi Tunnel project shows that the prediction results fit the real grounds condition well, especially for the short range ahead of face. This approach can be regarded as a good complement to the geophysical prospecting approach during the construction of mountain tunnels.

► The Markov process and Bayesian updating are used in the proposed approach.
► The ground condition ahead of tunnel face is dynamically predicted in a probabilistic way.
► The case study shows that the prediction results fit the real ground conditions well.
► Merits and drawbacks are discussed through the application case study.