Abstract: A fusion model based on material balance equation and Informer is proposed to solve the prediction problem of oilfield development indicators. Firstly, the mechanism model before and after the decline of oil field development production is established through the knowledge of the material balance equation field. Secondly, the established mechanism model is fused with the loss function of the Informer model as a constraint to establish an indicator prediction model that conforms to the physical laws of oil field development. Finally, the actual production data of the oil field is used for experimental analysis. The results indicate that compared to several purely data -driven cyclic structure prediction models, this fusion model has better prediction performance under the same data conditions. The mechanism constraints of this model can guide the training process of the model, so that its rate of convergence is faster, and the prediction at the peak and trough is more accurate. This fusion model has better predictive and generalization abilities, and has a certain degree of physical interpretability. 

Key words: Informer model, mechanism model, deep fusion model, prediction