Application of Data Mining techniques for the development of new geomechanical characterization models for rock masses

Abstract

Due to the inherent geological complexity and characterization difficulties in rock formations, the evaluation of geomechanical parameters is very complex and still subject to high uncertainties. However, in large geotechnical projects, a great amount of data are produced and used to establish near-homogeneous geotechnical zones. If properly analyzed, these data can provide valuable information that can be used in situations where knowledge about the rock mass is limited. Yet, this implies the organisation of geotechnical data in formats for proper analysis using advanced tools which is not normally done. Data Mining (DM) techniques have been successfully used in many fields and more recently also in geotechnics with good results in different applications. They are adequate as an advanced technique for analyzing large and complex databases that can be built with geotechnical information within the framework of an overall process of Knowledge Discovery in Databases (KDD). In this Chapter, a KDD process is carried out in the context of rock mechanics using the geotechnical information of two hydroelectric schemes built in Portugal interesting mainly granite rock formations. The main goal was to find new models to evaluate strength and deformability parameters (namely friction angle, cohesion and deformability modulus) and also the RMR index. Databases of geotechnical data were assembled and DM techniques used to analyze and extract new and useful knowledge. The procedure allowed developing new, simple, and reliable models for geomechanical characterization using different sets of input data which can be applied in different situations of information availability.