Research on Oil Well Daily Production Forecasting Model based on FWA-CNN-LSTM Hybrid Optimization

With the increasing importance of oil field production, ensuring the sustainable development of the oil industry has become increasingly urgent. In this study, an advanced oil well daily production forecasting method based on FWA-CNN-LSTM hybrid optimization model is explored. This hybrid model combines the Fireworks Algorithm (FWA), Convolutional Neural Network (CNN), and Long Short-Term Memory Network (LSTM). By utilizing CNN for feature extraction and LSTM for modeling in artificial intelligence technology, this method significantly improves the accuracy and robustness of oil well daily production forecasting. The global optimization capability of the FWA algorithm plays a key role in accelerating the search for optimal hyperparameters in the CNN-LSTM model. Finally, through simulation experiments on the data of the Yao-xxx well in the second oil production operation area of the Changqing Oilfield, the research results show that compared to various other models, the proposed FWA-CNN-LSTM hybrid optimization model demonstrates superior accuracy in oil well daily production forecasting.