Drilling-based rock strength estimation: A validated model for Mohr-Coulomb and a new theoretical-empirical approach for Hoek-Brown parameters

• An innovative approach using operational drilling data for continuously monitoring drilling parameters, enabling real-time estimation of rock strength. • A theoretical-empirical model was developed to estimate the constants of the Hoek & Brown (H-B) failure criterion using drilling data. • The strength properties of the Mohr-Coulomb (M-C) failure criterion were evaluated using the theoretical model developed by previous researchers. • The ratio of the bit diameter (D) to the rock grain size (d) is a significant parameter in the accuracy of the estimation. • The uniaxial compressive strength of the rock is directly proportional to the intrinsic specific energy. Conventional methods for determining the strength properties of rock are often costly and time-consuming. This research presents an innovative approach using operational drilling data for the continuous, real-time estimation of rock strength parameters for both the Mohr-Coulomb and Hoek-Brown failure criteria. The study evaluates a theoretical model for Mohr-Coulomb parameters and introduces a new theoretical-empirical model to estimate Hoek-Brown constants. These models were validated against conventional laboratory tests on ten different rock types, including sedimentary, metamorphic, and igneous varieties. The results demonstrate that the models can effectively estimate the strength properties for both failure criteria. A key finding is the introduction of a dimensionless ratio of bit diameter to rock grain size (D/d), which was shown to be a critical factor governing the accuracy of the Mohr-Coulomb parameter estimation; estimation error decreases significantly as the D/d ratio increases. Furthermore, the newly developed model accurately estimated the Hoek-Brown criterion constants, showing excellent agreement between the drilling-derived intrinsic specific energy and the Uniaxial Compressive Strength (UCS) values from conventional tests. This work provides a robust framework for more efficient rock strength characterization in various engineering applications.