Algorithm Design and Intelligent Analysis for Optimizing Reservoir Development Strategies

With the continuous progress of oilfield exploration and development technology, traditional development planning techniques have gradually shown limitations in the face of increasingly diverse displacement methods and complex reservoir types. It is difficult to efficiently integrate and optimize the workload deployment of various technical fields and multiple measures, thereby restricting the improvement of oilfield development efficiency and economic benefits. In this context, the rapid development of artificial intelligence (AI), especially machine learning (ML) technology, has brought revolutionary changes to the field of oil and gas exploration and development. This article innovatively proposes an ML based optimization algorithm for reservoir development strategy, which deeply integrates advanced technologies such as big data analysis and deep learning (DL). It can accurately analyze reservoir geological characteristics, fluid dynamic changes, and historical production data. By constructing complex models to simulate reservoir responses under different development schemes, intelligent optimization of development strategies can be achieved. The experimental results show that the algorithm can not only significantly improve the accuracy and efficiency of development planning, but also effectively reduce development costs, providing strong technical support for the sustainable development of oil fields.