Selection of Candidates and Formation Damage Advisor with an Expert System

In the lifecycle of an oil well, numerous factors such as pressure drop, partial perforation, turbulent flow, and formation damage can adversely affect its productivity. Identifying and addressing these issues, especially formation damage, is crucial. Acid treatment is commonly used to mitigate such formation damage, thereby enhancing well productivity. Traditionally, the selection of wells for acid treatment and the identification of formation damages have relied on extensive geological and engineering analyses. These conventional methods, while thorough, are time-consuming and involve the examination of complex geochemical, geophysical, and geological data. Accordingly, the current study introduces an expert system designed to streamline these processes. Expert systems, capable of automated and rapid data analysis, offer significant advantages by accelerating decision-making and improving efficiency. The expert system developed in this research demonstrates notable proficiency in processing intricate datasets, thus enhancing productivity and reducing the probability of errors. Its predictive capabilities also enable proactive management of wells. This research employs an expert system to analyze ten wells, identifying six as suitable candidates for acidizing. The system effectively detects potential formation damages in these wells, demonstrating its accuracy in diagnosis and decision-making. The adoption of expert systems in high-uncertainty scenarios requiring precise analysis is promising. Utilizing more routine or standard algorithms and mathematical models, these systems can significantly improve decision-making processes, predictive accuracy, and operational efficiency in oil and gas reservoirs. Improved decision-making is a key benefit as these systems, with comprehensive and analyzed data, enable more informed and effective decisions. In this study, an expert system is developed for selecting wells suitable for acid treatment and diagnosing formation damage types. Of the ten wells analyzed, six were deemed suitable for acid treatment. The system's ability to detect potential formation damages in each well highlights its effectiveness. These systems, employing algorithms and mathematical models for event modeling and prediction, aid in enhanced, faster decision-making processes. The use of expert systems in areas with high uncertainty and the need for precise modeling is valuable, contributing to improved operational efficiency and productivity in the oil and gas sector.