Rapid and partial acquisition are features of rock drilling for obtaining rock properties. Most previous research has primarily concentrated on how to quickly obtain rock mechanics parameters, with limited emphasis on extracting rock parameter fields, particularly in three dimensions. This study attempted to develop a numerical integrated method to extract 3D parameter fields of rocks based on a newly developed digital-controlled drilling platform. The importance of incorporating a damage model for accurate simulations of rock drilling through finite element analysis (FEA) was investigated. By calibrating damage parameters through uniaxial compressive strength (UCS) and Brazilian tensile strength (BTS) tests, these parameters can be considered constants in rock drilling simulations across various rock types. The accuracy of rock parameters estimated by the proposed method and the derived analytical model were further demonstrated through comparison with the corresponding standard tests. Furthermore, the 3D parameter field of rocks was obtained by integrating a deep learning method and micro-CT technology. The numerical prediction illustrated the advantages of acquiring a rock parameter field in achieving more accurate simulations of the rock failure process. Besides, our solution can also provide support for the parameter selection of numerical models considering spatial variability for natural rocks. A digital-controlled equipment for rock drilling was developed.Equations were derived for extracting rock parameters through the drilling data.A deep learning method was developed to reproduce the three-dimensional parameter field of rocks.The significance of considering the realistic rock parameter field was numerically demonstrated.
