Case Study: Shallow Surface Casing Corrosion Mitigation Evaluation
Bibliographic record
Abstract
Abstract Shallow surface casing failures have occurred in some wells in the Kuparuk oil field located on the North Slope of Alaska. A previous investigation into these failures has shown that they are caused by shallow external corrosion of the surface casing within the conductor annulus. The corrosion is believed to be caused by the presence of oxygenated surface water in the annulus and exacerbated by the extremely corrosive environment created when this water mixes with the ion-rich cement. To combat this issue a field wide corrosion mitigation program began in 2006. The program focuses on injecting a corrosion inhibiting compound into the outer most annulus. At the time of this paper, 870 out of 1270 wells have had the mitigation completed. The goal of this compound is to coat the pipe and stop the influx of water into the annulus; without the water influx the corrosion should be reduced. Concurrent with the mitigation program, a memory logging tool was used to monitor corrosion rates. This tool surveys variations in pipe metal thickness by measuring variation is velocity and amplitude of alternating magnetic waves. The log results display total metal volume by calibrating the tool at a depth that is assumed to be undamaged. The accuracy of this tool was verified for specific casing configurations on 14 wells that were excavated and inspected after logging. Since then, this log has been run several months prior to, at the time of, and several months after injecting the corrosion inhibitor into the annulus on various wells. Using the data available from the logs and surface casing failures, the effectiveness of the corrosion mitigation program was evaluated. The main focus of this paper will be the methodology and conclusions obtained from the evaluation. This paper will: Review the cause of shallow surface casing corrosion.Discuss current mitigation methods for reducing this corrosion.Detail how these methods vary based on well head design.Discuss the logging tool, its limitations, and how it was used for evaluation.Summarize the results of the evaluation.Discuss recommendations for improving the effectiveness of corrosion mitigation project on remaining wells.Outline the future of the corrosion mitigation project.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".