In this thesis we will discuss about about the result of a research project conducted for Politecnico di Torino about the classification of geological pores in rock samples. We analyzed the data collected by the experts about geological pores by using the most well-known clustering techniques of data mining. The aim is to understand which clustering algorithms give the best result in pores data categorization. In general, clustering studies sets of objects properties by finding relationships between these objects based on the similarities of their properties. In our case pores, have a great variety of attributes mainly based on their shape and size.