Optimization of Borehole Location for Site Investigation Based on Coupled Markov Chain

Based on coupled Markov chain and information entropy theory, an optimization method for geological borehole is proposed to obtain the location, depth and quantity of boreholes by considering the tradeoff between the accuracy of ground information and cost of boreholes. The probabilistic distribution of soil information is predicted and identified based on coupled Markov chain theory. To evaluate both the information entropy and exploration cost, genetic algorithm is used to calculate the optimal solution of borehole location and depth under the condition of dual objectives. Based on orthogonal boundary crossing method, the optimal number of boreholes is calculated. Finally, the feasibility of the proposed method is verified by taking the data of Shenzhen Mawan tunnel cross section 4 borehole as an example. The proposed method can provide the basis for the optimization of the location, depth and number of boreholes in tunnel geological prospecting. According to considering the uncertainty of borehole cost and site information comprehensively, it provides a feasible means for predicting engineering geological information based on limited exposed soil data.

Keywords: Coupled Markov chain, Information entropy, Genetic algorithm, Orthogonal boundary crossing method