Skip to main content

New Fortress Energy will apply Honeywell LNG pre-treatment technologies on fast LNG

Published by , Editorial Assistant
LNG Industry,


Honeywell has announced that New Fortress Energy Inc. will use a series of technologies from Honeywell UOP to remove various contaminants from natural gas prior to liquefaction at its Fast LNG projects.

Each project is a nominal 1.4 million tpy LNG gas treating and liquefaction plant. Honeywell UOP will provide engineering services and process technology which will pre-treat feed gas at the facilities.

“Honeywell’s ready-now technology allows for the critical removal of impurities from natural gas streams through the use of the most reliable, efficient, and cost-effective technology which translates directly to greater throughput and reduced utility consumption,” said Bryan Glover, President, Honeywell UOP.

Honeywell UOP is a global leader in gas processing technologies. Its solutions for contaminant removal and hydrocarbon management are used in the production of approximately 40% of the world’s LNG. These technologies are optimised for onshore and offshore natural gas conditioning, treating, natural gas liquids recovery, LNG pre-treatment, and synthesis gas purification from single unit to highly integrated, multiple technology operations.

Honeywell recently committed to achieve carbon neutrality in its operations and facilities by 2035. This commitment builds on the company’s track record of sharply reducing the greenhouse gas intensity of its operations and facilities as well as its decades-long history of innovation to help its customers meet their environmental and social goals. Approximately 60% of Honeywell’s new product introduction research and development investment is directed toward products that improve environmental and social outcomes for customers.

Read the article online at: https://www.lngindustry.com/liquefaction/10022023/new-fortress-energy-will-apply-honeywell-lng-pre-treatment-technologies-on-fast-lng/

You might also like

 
 

Embed article link: (copy the HTML code below):