Estimation of in-situ maximum horizontal principal stress magnitudes from borehole breakout data using machine learning

This paper presents a technique for in-situ horizontal stress prediction in vertical boreholes based on borehole breakout data using a machine learning-based meta-modelling technique, i.e. Kriging. This model is generated based on the deterministic mean function and a stationary Gaussian process function derived from the 106 data points from published experimental studies. To examine the reliability of the model, a leave-one-out cross-validation...