Model Fusion Based Oilfield Production Prediction

Oil production prediction is the main focus of scientific management. During the process of oil exploitation, the production data can be considered to have time series characteristics, which are affected by production plans and geologic conditions, making this time series data complex. To resolve this, this paper tries to make full use of the advantages of different prediction models and proposes model fusion based approach (called TN-Fusion) for production prediction. This approach can effectively extract the temporal and non-temporal features affecting the production, to improve the prediction accuracy through the effective fusion of time series model and non-time series model. Compared with those single model based approach, and non-time series model fusion methods, TN-Fusion has better accuracy and reliability.