Abstract: In order to solve the problem that the model fitting effect is not good due to the complex coupling relationship between drilling controllable factors, a prediction model of mechanical drilling speed based on fuzzy neural network is proposed. The fuzzy control idea is used to solve the parameter coupling problem and to predict. Clustering algorithm is used to divide the data with high similarity into a fuzzy set as the initialization parameter of the second layer of fuzzy neural network. Taking an oilfield as the background, the simulation results show that the empirical knowledge extracted by fuzzy neural network conforms to the coupling relationship between controllable parameters of drilling in the oilfield, and it is suitable for most drilling operations in the region. It proves that the model has good prediction ability, and verifies the feasibility and applicability of the model, which is of great significance to improve drilling efficiency and save cost.

Key words: drilling rate prediction; , fuzzy control; , neural network; , coupling; , membership degree