On an increasingly frequent basis, pipeline operators are using risk-based decision making to prioritize cross-company expenditures. Due to the long-term mitigation benefits of Cathodic Protection (CP), when planning external corrosion mitigation activities, pipeline operators typically prioritize mitigation of deeper anomalies for integrity expenditures due to their higher Probability of Failure (PoF). However, anomalies that are not receiving adequate CP or those experiencing electrical interference may remain unaddressed using this rationale. This paper presents both a qualitative and semi-quantitative approach to support the quantification of the risk reduction benefits gained from external corrosion prevention on pipelines. This can help in the efficient prioritization of both pro-active and re-active integrity repair activities. Supporting examples are also discussed to help explain the intended use of the methodology and the interpretation of the results.
To stay competitive in the corrosion industry, companies must continually be looking for more efficient, safe, and cost-effective ways to inspect and maintain assets. There are many opportunities for the increased use of robotic solutions in all aspects of the corrosion industry, but the primary reasons focus on limiting human intervention for both safety and accuracy.
This book presents the reader with multiple examples of the use of robotic unmanned and remote-controlled systems, be they underground, on the ground, or in the air.
2020 NACE, 6" x 9" trim size, B&W, perfect bound, 62 pages
In-Line Inspection (ILI) technology is considered one of the safest and most efficient and reliable inspection method to inspect hydrocarbon pipelines. The retrieved data are usually validated and verified upon successful completion of the inspection. This paper is intended to introduce a new approach to validate the ILI run based on a statistical analysis comparing the new ILI run with a previous ILI run of the same pipeline by leveraging a root mean square (RMS) model to quantify the similarity between the datasets. API-1163 and Canadian Energy Pipeline Association (CEPA) offer consistent criteria as a validation methodology for a new ILI run. Also, this paper will demonstrate a new scoring criterion for accepting Magnetic Flux Leakage (MFL) runs with partial data loss as number of MFL runs experience unexpected data loss, which might affect the minimum reporting threshold of the tool. The approach will help pipeline operators to identify the criticality of the missed data via a detailed comparison with the previous MFL run for the same pipeline and detailed analysis of the behavior of the tool during the run. The scoring criteria is aligned with the Pipeline Operators Forum (POF) requirements for data loss. Multiple case studies extracted from actual data will be presented throughout the paper.