Research on Application and Optimization of Intelligent Algorithms in Digital Reservoir Management

This study focuses on the application and optimization of intelligent algorithms in digital reservoir management, aiming at meeting the efficiency and cost challenges faced by reservoir management under the global energy demand growth. Traditional reservoir management methods are limited by data processing ability and prediction model accuracy, and it is difficult to meet the needs of modern oilfield refined management. In this paper, a Hybrid Ensemble Transfer Learning (HETL) is proposed, which combines the advantages of integrated learning and transfer learning, and improves the prediction accuracy, stability and model interpretability by optimizing the algorithm structure and introducing a new learning mechanism. The model trains a high-performance machine learning model on the source oil field data set, and migrates to the new oil field data set for fine adjustment to adapt to the geological characteristics and production conditions of different oil fields. Case analysis takes Shengli Oilfield as an example. The results show that HETL model is significantly superior to traditional methods in predicting oilfield production, optimizing water injection strategy and determining production scheme. The prediction accuracy is improved to 95%, oil recovery is improved by 5%, and operating cost is reduced by 10%. The application of HETL model not only improves the production and oil recovery of Shengli Oilfield, but also shows the superiority and practicability of intelligent algorithm in reservoir management. The research emphasizes that in the future, reservoir management should pay more attention to regional differences, formulate personalized management strategies, and continuously monitor and optimize intelligent algorithm models to ensure long-term and efficient oilfield development. This study provides a new idea and solution for the application of intelligent algorithm in digital reservoir management, and promotes the sustainable development of petroleum industry.