The requirement of ensuring the integrity of pipelines in high sour and high-pressure services drives the use of real time corrosion monitoring to achieve an effective corrosion management. In this regards, Petroleum Development Oman (PDO) has used online corrosion monitoring technology to ensure the integrity of carbon steel pipelines transporting high sour fluids with the premise of internal mitigation. The online corrosion monitoring in pipelines has supported PDO's approach as part of overall corrosion management strategy. In this case, Field Signature Method (FSM) technology is used as online corrosion monitoring tool to monitor the metal loss and determine the corrosion rate of the pipelines. In addition, the data from the FSM units can be used to support other studies such as pigging and corrosion inhibitor optimization. This paper will cover the real time corrosion monitoring results with FSM technology and learnings for several pipelines in high sour and high-pressure services.
Corrosion monitoring is the practice of measuring the corrosivity of process fluid conditions and the effectiveness of corrosion barriers by the use of intrusive and/or non-intrusive techniques at most susceptible locations. PDO developed a new project located in south which have five main pipelines, carbon steel operating at high pressure and high sour conditions.
The Corrosion Management Framework (CMF) includes non-intrusive technique (NIT) with real time data collection to measure the corrosivity of the fluid and effectiveness of corrosion barriers (continuous and batch corrosion inhibitor with routine pigging),1 whilst reducing the risk of people exposure to high pressure and high sour services. Corrosion monitoring and management for high H2S applications and underground is also discussed by Wold & Al. 2
The selected NIT, to monitor expected corrosion mechanism: localized corrosion due to H2S corrosion, was Field Signature Method (FSM) located in three points across each pipeline (beginning of the line, middle and at the end) with consideration of low points (see Table 1).
