High Energy Natural Gas Internal Corrosion Susceptibility Analysis
Bibliographic record
Abstract
Alliance Pipeline operates an integrated Canadian and U.S. high-pressure, rich natural gas transmission pipeline system. Rich natural gas pipelines are unique in that the product transported in these pipelines contains greater amounts of higher molecular weight hydrocarbons than would be transported in a dry natural gas pipeline. The specifications for gas quality however are very similar and require the product to contain less than sixty five mg/m3 water, no free liquids and/or objectionable materials such as bacteria, ashphaltene, gum, etc. The acid gases, carbon dioxide and hydrogen sulphide, are also required to be below certain values (see Table 1). Corrosion is not expected to occur under these conditions due to the lack of free water available for the development of an electrochemical corrosion cell. However, there are instances where the gas quality may vary and this gas enters facility piping for short periods of time. A method has been developed by Pipeline Research Council International (PRCI) to determine the internal corrosion susceptibility for dry gas natural gas pipelines but there are currently no industry accepted models which determine the internal corrosion susceptibility for high energy natural gas (HENG) pipeline systems. Accordingly, it is important for operators of pipelines with high energy natural gas (HENG) to collect and analyze these off specification events and develop a method to determine the relative impact on internal corrosion susceptibility. It is perhaps more important for operators to use this method to develop a strategy to prioritize facility piping for inspection and confirm the absence of internal corrosion. An Internal Corrosion Susceptibility Assessment (ICSA) method has been developed for HENG which considers off specification water, carbon dioxide, and hydrogen sulphide contents in the HENG. The analysis has been enhanced to also consider low temperature operation and hydrocarbon dew-point variations. The model has been effectively trialed over the last number of years to prioritize inspections and has been further tested against PRCI research and models developed for dry gas internal corrosion susceptibility. All internal corrosion models need to identify free water as prime contributor to susceptibility, thus the subject model is considered adaptable to other gas pipeline systems. This paper discusses the methods used to develop the model, the challenges encountered and results of the field inspections conducted.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".