Corrosion Management for Aging Pipelines—Experience From the Forties Field
Bibliographic record
Abstract
Summary In 2003, Apache became the operator of the Forties Field. The field has now been in operation for 33 years and much of the infield pipeline system has exceeded its original design life of 20–25 years. Apache intends to continue production in the Forties Field for, potentially, in excess of a further 20 years. With that in mind, they have identified numerous issues with respect to corrosion management of the infield pipeline system. Since late 2006, the Forties Field infield pipeline corrosion and integrity management has been carried out by IONIK Consulting/JP Kenny Caledonia Ltd. Working closely with Apache, the infield pipeline system has been reviewed; a number of issues have been assessed and quantified; and practices with respect to corrosion management, corrosion monitoring, and inspection have been implemented. This document examines the issues identified, the corrosion management strategy put in place, and the inspection actions undertaken. Examples of issues identified with respect to corrosion management systems include a requirement for a dedicated pipeline corrosion management strategy, pipeline corrosion modeling, a corrosion risk assessment of the pipeline system, a review of corrosion inhibition and pigging, and a review of key performance indicators with emphasis on pipeline management. Specific corrosion issues identified include anode depletion, preferential weld corrosion, localized corrosion, and 6 o'clock corrosion. Examples of other factors identified have been potential risks from microbial and underdeposit corrosion caused by low flow rates. This publication provides an overview of these issues and the implementation of solutions, alongside changes to items such as documentation and modification of existing procedures, risk assessment, corrosion management, and the implementation of an intelligent pigging program.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".