Classification and identification of hydrocarbon reservoir lithofacies and their heterogeneity using seismic attributes, logs data and artificial neural networks

► Multi-attribute analysis according to the competitive learning algorithm as unsupervised and back-error propagation (BP) algorithm as supervised artificial neural networks methods ► Recognizing seismic facies and their spatial distribution with 3D seismic data, well log data, and geological information ► Statistical analyses on seismic attributes together with their geological significance as the main criteria to choose proper seismic attributes ► Identifying lithofacies and their lateral heterogeneity in the hydrocarbon reservoir as the main objective of this study