Significance  As the new round of national exploration & development planning continues, resource exploration is advancing toward the deep Earth. However, deep strata exhibit diverse rock types, which complicate the measurement of rock mechanical parameters. Furthermore, the harsh environments of these strata, characterized by high temperatures, high pressures, and high in-situ stress, are prone to induce downhole accidents like drilling tool failure, wellbore collapse, loss of circulation, and well kicks, posing challenges to geological drilling.

Advances Aiming at the perception and modeling of complex geological environments, this study reviews the existing studies on the modeling of stratigraphic characteristic parameters from the perspective of formation drillability and formation pressure, aiming to provide guidance for the technique adjustment and efficiency optimization of geological drilling processes based on these two key characteristic parameters. To satisfy the demands for safe and efficient geological drilling, this study explores the advances in research on the safety early warning of the geological drilling process from two perspectives: wellbore stability assessment and downhole failure monitoring. The safety early warning technology allows drillers to promptly find and identify downhole accidents and, accordingly, eliminate potential safety hazards in advance.

Prospects Under the more complex and harsh geologic conditions of deep strata compared to those of shallow ones, the models of stratigraphic characteristic parameters will play a more significant role in the geological drilling process, and the safety early warning technology will act as the core technology in the next generation of intelligent geological drilling equipment. In the future, it is necessary to build an intelligent geological exploration system with the geological exploration data platform as the core, make data play a key role in the whole process of geological exploration and mineral exploitation, and promote the application of artificial intelligence in the optimization of the geological drilling process, the perception of stratigraphic environments, and prospecting predictions. The purpose is to ensure safe and efficient geological drilling.