Internal corrosion model predicts corrosion severity in pipelines: Fid-Bau Portal

Internal corrosion model predicts corrosion severity in pipelines

Cameron, Glenn R. / Helgeland, Doug / Ho, Bill / Caleb, Katherine

A NUMBER OF high profile pipeline failures across Canada and the United States have brought the issue of pipeline safety to the forefront. Every year in Alberta, more than 750 pipelines fail, potentially causing harm to both people and the environment. The Energy and Utilities Board (EUB)that regulates pipelines in Alberta attributes these failures to three primary causes: internal corrosion, external corrosion, and third-party damage. Upstream pipelines account for approximately two thirds of the pipeline failures that occur in Alberta, and over half of those failures are due to internal corrosion. For the operators of these pipelines, integrity maintenance is problematic due to three factors. * Upstream pipelines are typically multiphase and have a corrosive environment caused by the CO₂, H₂S, and chloride-containing water that comes directly from the production reservoir. * Most of these pipelines cannot be easily inspected with smarts tools, and determination of the location and severity of internal corrosion is difficult by other means. * The sheer volume of pipelines (H-200,000km in Alberta) makes it difficult for operators to know where to concentrate their efforts to ensure the best value and highest impact. In the lates release of their pipeline i ntegrity software, PipeCraft, Green Pipe Industries Ltd has developed an internal corrosion (ICM) to help operators manage its internal corrosion issues using information from the operator's records and the public domain (such as the EUB). The ICM combines the power of a geographic-information system (GIS) with corrosion prediction and hydraulic analysis tools to determine the locations for direct assessment for internal corrosion. In a joint proj ect, Green Pipe and Talisman Energy Inc have worked together to validate the algorithms in the internal corrosion model using the results from actual inline inspection data. The results of this project demonstrated an excellent correlation between the predicted and measured severity of the major corrosion defects. PipeCraft also includes a comprehensive GIS-based consequence algorithm which, when used in conjunction with the ICM, provides the risk based methodology to prioritize pipelines for direct assessment as recommended by ASME B31,8S-2000, as well as verify the effectiveness of corrosion inhibition and monitoring programs.