Borehole optimization method utilizing local coupled Markov chain model

The rational use of exploration data for accurate geological modeling and the step-by-step optimization of drilling plans are of great importance for reducing the exploration costs and improving the efficiency of stratigraphic data collection. Due to the typically sparse borehole data at the early stage of geotechnical surveying and the potential for significant variations in the geological structure across different locations within the project area, the difficulty of borehole design is greatly increased. The CMC model can handle sparse geological exploration data and is widely used in geological modeling and geological uncertainty analysis due to its simple parameters and straightforward theory. However, the existing CMC models cannot be used for the borehole design in complexly varying strata because they rely on the global sequence direction and the Walther's constant, which may lead to incorrect estimates of geological structures. A method for optimizing the additional boreholes is proposed based on the local coupled Markov chain model (LCMC model). This method establishes a geological model that adapts to complex and varying strata by fragmenting borehole data from geological profiles, employing local stochastic modeling, and overlaying multiple fragments; it uses an entropy map generated by the LCMC model to quantitatively evaluate the uncertainty of geological units; and it progressively predicts the optimal locations for the additional boreholes based on the column-averaged entropy curve. The research results show that, compared to the traditional methods, the proposed approach can achieve more reasonable and efficient borehole optimization, increase the modeling accuracy of complex strata with changing dips and directions, and reduce the uncertainty in geological profile simulations. The proposed method offers a the beneficial reference for borehole design in geologically complex and variable regions.