Optimization of the Claus Process Using Machine Learning and Real Operational Data: A Case Study in an SRU

Key Points

• The optimization enhances the Claus process, promoting higher efficiency and reduced emissions in sulfur recovery.
• Machine learning analysis integrated real operational data for predictive modeling and performance optimization.
• Analysis of real operational data improves Claus process efficiency by 15% under specific conditions and constraints.
• Improved operational strategies may enable better outcomes, yet validation across different SRUs is necessary.