Technology

Process Summary

The proprietary process technology, Lurgi MegaMethanol™, converts natural gas into methanol. 

Suited to large-scale production, Lurgi MegaMethanol™ converts syngas into raw methanol using a two-step reactor process with high levels of energy integration and low recycling ratios during synthesis. The two stage reaction process allows low recycle ratios leading to reduced equipment size and therefore large single train capacities.

The Lurgi MegaMethanol™process is particularly well-suited to customers with methanol production needs of more than one million tons per year. The most recent designs are capable of producing as much as 10,000 tons of methanol per day in a single train.

Process Flow Diagram

The Process Flow Diagram featuring the methanol synthesis section only is show inthe attached image. The feedstock (natural gas or syngas) is passed over a copper catalyst in a two-step synthesis process involving water-cooled and then gas-cooled reactors (GCR). The GCR works as a gas preheater and methanol synthesis refinement reactor (catalyst on shell-side) allowing for a smaller Boiling Water Reactor (BWR, catalyst on tube-side) and a low recycle ratio. Any unconverted syngas is recycled back into the synthesis loop to increase yield and improve carbon efficiency. The resulting raw methanol product is then distilled further to meet customers' required specifications (e.g.: International Methanol Producers and Consumers Association, United States Federal Grade Acrylic Acid). 

Process Conditions

The process conditions are as it follows:

Details about mass flow rates are provided in Reference^[3].

Key figures (including combined reforming and Air Separation Unit)

• Capacity: 2 500 to 7 000 tons per day or 10 000 tonnes per day.
• Natural gas consumption: 29 million british thermal unit (MMBTU) per tonne.
• Oxygen from integrated Air Separation Unit: 0.4-0.5 tonnes per tonne.

References

1. Air Liquide, Methanol. (Accessed 1^st Dec 2024) 
2. Engineering Air Liquide, Lurgi Megamethanol™. (Retrieved via the Internet Archive, 9th Mar 2022)
3. Filippo Bisotti et al., 2022, Impact of Kinetic Models on Methanol Synthesis Reactor Predictions: In Silico Assessment and Comparison with Industrial Data. Industrial & Engineering Chemistry Research, 61.10.1021/acs.iecr.1c04476.