Application of Fuzzy Cluster Analysis on Identifying Sedimentary Microfacies

There are multiple solutions and fuzziness of the corresponding relationship between sedimentary environment and depositional features due to diversity and complexity of the sedimentary rock. Against this characteristic, the neural network fuzzy clustering analysis method was applied, which combined self-adaptiveness and fault tolerance of neural network technology with fuzzy synthetic discriminant features of fuzzy logic, for achieving sedimentary microfacies identification with multi-factor fuzzy comprehensive judgement. This method was used to process the data from 128 layers of three boreholes drilled in Huayingshan region of Sichuan Basin, and achieved good results with the coincidence rate of 89.85%. The result showed that the method had good adaptability for automatic identification of sedimentary microfacies and increased automatic identification accuracy of sedimentary microfacies.