Wood and NERA announced on May 27 a new funding partnership arrangement led by Wood in collaboration with The University of Western Australia (UWA) to support the development of an online hydrate blockage prediction model for operating gas condensate systems.

Methane hydrates present a major challenge in multiphase subsea production pipelines. These ice-like substances form inside the pipe and can eventually build up to create a blockage. Removing a hydrate blockage from a subsea pipeline is an expensive and time-consuming exercise. For LNG facilities, such interruptions to production can have severe financial consequences, and therefore hydrate blockages are avoided at all costs.

Commencing in June as part of the “Long Subsea Tie-back” project, Wood will integrate UWA’s mechanistic hydrate model into its operational online Virtuoso software package. This will allow operators for the first time ever to calculate in real time the operational risk of a hydrate blockage in their assets both now and into the future, considerably reducing operational uncertainties.

Virtuoso is Wood’s world leading asset performance monitoring software, providing real-time operational and optimization advice to over 10% of the world’s upstream gas production.

This project builds on the Wood-led Transforming Australia Subsea Equipment Reliability (TASER) project, which leveraged NERA funding and industry connections to focus on sharing knowledge to improve subsea equipment design and reduce costly and time-consuming associated with equipment that is failing prematurely.

“Following the successful implementation of the TASER project last year, we are delighted to again receive funding from NERA for another project which will assist operators and others in the oil and gas industry to avoid costly offshore repair campaigns,” Dr. James Holbeach, Wood’s strategy and development director of automation and control business, said.

Wood intends to deliver a fully integrated commercially available version of Virtuoso with the UWA Hydrate Mechanistic model by October 2019.