A high-pressure gas condensate development located offshore consists of a subsea production system comprising a series of subsea manifolds located on the north, west, and east flanks of the development area. The well clusters and manifolds are tied back via looped 14" carbon steel flowlines to a new platform. In order to manage corrosion, the project corrosion monitoring objective was to flag any short fall in corrosion inhibitor injection rates to minimise internal corrosion in the ten subsea infield flowlines and to confirm the corrosion
inhibitor is working. The timeline to deliver the initial device chosen for corrosion monitoring spools (based on electrical resistance) had already been factored into the project plan in 2012. The first batch of corrosion monitoring devices (4) had to all be delivered to the new development by the first quarter of 2016 to ensure installation of the flowline termination assemblies (FTAs) so that the flowlines were not affected.
The device chosen initially was unable to meet the scheduled dates; thus, there was a real possibility that the FTAs and flowlines would be installed without adequate corrosion monitoring. Thus, a new subsea corrosion monitoring device based on ultrasonic technology was designed, fabricated, installed and commissioned. The data to date demonstrates that the corrosion inhibitor has been injected at the required rate by and large and the wall thickness data/corrosion rate data from the corrosion monitoring clamps also confirm negligible corrosion below design requirement (0.1 mm/yr). Should the corrosion inhibitor injection concentration be maintained at or above the target (75 ppm) and the corrosion monitoring data continues to be indicative of negligible corrosion rates, this will be a useful input into determining when in line inspection should be carried out in future. Credible corrosion rates relayed by monitoring device were determined using real time linear
regression. A long-term service agreement is in place to enable periodical processing of the raw data, assessment of sensor performance and also continually improving algorithms to realise the full potential of the device.