Skip to main content

ENGIE’s Cape Ann to provide FSRU services to Chinese group CNOOC for the winter season

Published by
LNG Industry,


ENGIE has announced that it has renewed the regasification and storage services contract with Chinese energy group CNOOC for the coming winter season.

The contract will be fulfilled by the FSRU GDF SUEZ Cape Ann which arrived in the port of Tianjin fully loaded with LNG and started operations on 28 October. She will remain in the Chinese port until Spring 2018.

Cape Ann has previously provided similar services to CNOOC, from November 2013 to January 2017, as a contribution to both LNG and natural gas supply needs, mainly during winter period associated with peak demand.

In addition to the usual FSRU activities, Cape Ann will also transfer LNG into smaller on-shore tanks which are used by CNOOC for LNG trucking activity.

Philip Olivier, Head of ENGIE Global LNG, commented: “We are especially pleased to continue this relationship with CNOOC, a long standing partner of ENGIE in the field of LNG. This new contract illustrates ENGIE’s fast track capabilities to provide safe, reliable and flexible LNG importing solutions to meet the needs of our customers.”

Read the article online at: https://www.lngindustry.com/liquid-natural-gas/02112017/engies-cape-ann-to-provide-fsru-services-to-chinese-group-cnooc-for-the-winter-season/

You might also like

 Webinar

[WEBINAR] Insulation advances: Mitigating noise and CUI in your LNG plant

Heightened noise levels are harmful to the well-being and productivity of a plant’s personnel as well as the surrounding environment. With excessive noise presenting so many financial and health and safety risks, LNG plants need reliable, cost-effective noise-reduction solutions. This webinar will outline the most popular acoustic standards in the industry today and distill down to the audience what they need to know in order to best protect their work personnel and profits.

Register for your free space today »

 
 
 

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