COURSE OVERVIEW

This practical and highly-interactive course includes real-life case studies and exercises where participants will be engaged in a series of interactive small groups and class workshops. 

 

This course is designed to provide participants with a detailed and up-to-date overview of Artificial Intelligence in Natural Gas Treatment. It covers the fundamentals of AI in natural gas processing and AI for gas feedstock characterization and quality prediction; the AI in gas separation and fractionation optimization; the AI for process control, real-time monitoring and acid gas removal; the AI for predictive maintenance of gas processing equipment, heat exchanger and gas cooler efficiency optimization; the AI in gas dehydration and water removal optimization, pump and compressor health monitoring; and the AI for pipeline and storage tank monitoring. 

 

Further, the course will also discuss the AI for gas sweetening and acid gas processing, natural gas liquefaction (LNG) optimization, mercury removal and trace contaminant detection; the AI for sulfur recovery and flue gas optimization including NGL (natural gas liquids) processing; the AI for gas processing safety and risk management; and the AI for environmental compliance and emission monitoring. 

During this interactive course, participants will learn the AI-driven real-time gas plant simulation models, machine learning for process optimization in digital twins and AI-powered predictive analytics for plant performance monitoring; the AI in advanced control systems and process automation, smart gas plant management and AI-driven decision making; the future AI trends in gas processing and LNG production; and the AI for AI-driven predictive analytics in gas treatment, reducing operational costs and increasing efficiency.