Application of artificial neural networks to predicate shale content

Abstract

This paper describes an Artificial Neural Network approach to the predication problem of shale content in the reservoir. An interval of seismic data representing the zone of interest is extracted from a three-dimensional data volume. Seismic data and well log data are used as input and target to Regularity Back-propagation (RBP) neural network. A series of ANNs is trained and results are presented. © Springer-Verlag Berlin Heidelberg 2005.