Application of SOPNN to water-flooded layer recognition in logging
Zou Tao-feng · 2008
Aiming at the problem for automatic recognition of logging curves in thin water-flooded layer,a dynamic classification model and method based on self-organization process neural networks(SOPNN)is presented.The SOPNN consists of input layer and competitive layer,whose inputs and connection weights can be functions of time.The continuous logging curves in thin layers can be inputs of the network,which extracts the corresponding forms and amplitude values automatically,implements self-organization and then outputs the classification result in the competitive layer.The learning algorithms of SOPNN competitive learning and teacher demonstration are given in this paper,which are used to process actual data of water-flooded layer logging and obtain good results.