Lithology classification using self-organising map

Abstract

This paper reports the application of Kohonen's self-organising map (SOM) network to the classification of lithology from well log data. The well log data are classified into nodes according to a pre-defined grid arrangement. The learning vector quantization (LVQ) algorithm is then applied to train the network under supervised learning. After the network is trained, it is used as the classification model for subsequent data. Results obtained from example studies using this proposed method have shown to be fast and accurate.