关键词: 概率神经网络技术, 储层预测, 岩性反演, 相关性, 地震参数, 地层特征

Abstract: In order to predict the reservoir with strong heterogeneity,a probabilistic neural network technique was developed on the theory of probabilistic density function and trained using known information of sandstone-mudstone reservoir.The probabilistic neural network was used to predict the reservoirs of a lithologic oilfield in the southwest China.The targets in the study area are the beach sandstone and channel sandstone of Sha-1 Member where the reservoir thickness is small and the lateral change of lithology is big.The correlations among the features of logging,seismic attributes and geological lithology were developed to train the probabilistic neural network,and the seismic attributes were transformed by the trained network to identify the lithologic information of reservoirs.The results show that the probabilistic neural network technique has good application effectiveness in the actual data processing.

Key words: probabilistic neural network technique, reservoir prediction, lithology inversion, correlation, seismic data, stratum feature