Bayesian networks (BN) are useful tools for corrosion modeling. This paper is a case study demonstrating how to perform Internal Corrosion Direct Assessment (ICDA) using BN modeling with limited data. A BN model was developed for ICDA of a 50 km refined oil pipeline. Internal corrosion probability of failure along the pipeline was assessed.
There is uncertainty about the best way to determine the corrosion risk for gas-condensate pipelines, and use of chemical inhibitors as mitigation strategy. We present considerations when devising corrosion mitigation and inhibition strategies, as well as a recommended test for inhibitor qualification.