فهرست نشریات علمی دسترسی آزاد ایران

Matrix acidizing plays an important role in improving oil recovery by decreasing reservoir damage. However, the complexity of selecting the most suitable acidizing fluid, given diverse reservoir conditions, poses a significant challenge. This article explores the utilization of expert systems in improving the acidizing fluid selection process. By examining the role, components, and merits of expert systems, along with real-world case studies, the article highlights how these systems contribute to more efficient and informed decision-making. In this investigation, eight instances of damage have been selected for analysis using the proposed expert system. Following a thorough assessment, selecting a fluid for damage elimination, demonstrates the effectiveness of the expert system. The incorporation of expert systems in modeling and inference under conditions of high uncertainty and precision plays a key role in increasing productivity, declining errors, predicting events, and refining decision-making processes. These systems utilize advanced algorithms and mathematical models for simulation and predicting implications across various applications, thereby aiding in expedited decision-making.