Abstract:  Aiming at the reservoir lithology discrimination based analysis data of coring well and the logging
process data, we proposed and established a learning vector quantization process neural network model (LVQ-
PNN). The model by increasing the output layer, expanded the depth of the self-organization process neural
network, using the combination algorithm strategies with unsupervised competition and supervised learning,
to improve the adaptive extraction of multidimensional signal feature and self-organization comprehensive ability,
The experimental result shows that it has better recognition ability and comprehensive lithology. The recognition
rate of lithology discrimination is 84. 7%.

Key words: process neural network, lithology discrimination, learning vector quantization