Facies Recognition Using the Neural Networks

Key words: 
• facies /
• pattern recognition /
• neural network /
• BP algorithm /
• similarity

Abstract: Pattern recognition methods are a powerful means in studying facies quantitatively. The neural network is a new method and has many improvements such as parallel processing and plasticity imitating the human brain compared with other pattern recognition methods. Permian carbonate rocks in the central Hubei basin have been identified as carbonate platform facies after traditional facies analysis. It includes five subfacies, i.e. sub-facies of districted depression, slope B, depression, slope A and shallow out. They are different from each other in rock color, mineral components, paleobiology components, rock structures and so on. The application of pattern recognition on the basis of the BP neural network for Permian carbonate rock facies studies, particularly comparison with fuzzy pattern recognition is very successful and inspiring. The correct identification ratios of fuzzy sets and the neural network are both about 75%. And the corret identification ratio of the combination of fuzzy sets and neural networks is 100%.