MWD data analysis for optimization of tunnel excavation

The drill and blast tunneling method applies to various rock mass conditions and is widely used in underground construction. Optimization of drill and blast requires careful planning and currently depends on the engineers’ ability to execute the art of blasting. Intelligent analysis of measurement while drilling (MWD) data from blast holes can be used for process optimizations, responsible resource utilization, and risk minimization. For example, an Artificial Intelligence (AI) -based decision support system (DSS) can suggest the volume and content of explosive material. However, to develop a reliable and trustworthy DSS, one needs to understand the relation between MWD data logs and the underlying lithology conditions, like composition or type of rock mass. This work provides an overview of the most common methods for MWD data analysis. Selected methods are then utilized to develop predictive machine-learning (ML) models, which are further validated with available MWD data.