COURSE OVERVIEW
PE1016 : AI in Natural Gas Treatment

OVERVIEW
COURSE TITLE | : | PE1016 : AI in Natural Gas Treatment |
COURSE DATE | : | May 25 - May 29 2025 |
DURATION | : | 5 Days |
INSTRUCTOR | : | Mr. Hany Ghazal |
VENUE | : | Dubai, UAE |
COURSE FEE | : | $ 5500 |
Register For Course Outline |
Course Description
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.
link to course overview PDF
TRAINING METHODOLOGY
This interactive training course includes the following training methodologies:
LecturesPractical Workshops & Work Presentations
Hands-on Practical Exercises & Case Studies
Simulators (Hardware & Software) & Videos
In an unlikely event, the course instructor may modify the above training methodology for technical reasons.
VIRTUAL TRAINING (IF APPLICABLE)
If this course is delivered online as a Virtual Training, the following limitations will be applicable:
Certificates | : | Only soft copy certificates will be issued |
Training Materials | : | Only soft copy materials will be issued |
Training Methodology | : | 80% theory, 20% practical |
Training Program | : | 4 hours per day, from 09:30 to 13:30 |
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