Gas Tight Production Casing Remediation via Expandable Steel Patches
Bibliographic record
Abstract
Abstract A major operator in the Middle-East faced a casing integrity issue on a well drilled in 2015, due to several leaking production casing connections determined through analysis of a number of data sets including pressure test results, casing connection torque turn charts and caliper logs. Potential remedial solutions were limited to those that did not involve directly remediating the production casing as the number of suspect connections made these solutions high risk. Potential solutions were also required to meet a V0 "gas-tight" pressure integrity requirement to meet the need for gas lift production as well as provide a post remedial ID suitable to deploy the upper completion equipment through. Lastly, any solution identified was to have a high probability of success through existing qualification testing and field deployments. The solution identified and selected was an expandable tubular technology called "Expandable Steel Patch", deployed with a deformable element hydraulically inflated, called "Inflatable Packer". When pumped from surface into this high-pressure balloon, the outer diameter increases, applying a force inside a steel pipe. This pipe, the Expandable Steel Patch, is pushed against the casing and stressed above the material plastic limit. The deformation is permanent. An outer skin of elastomer creates both a gas tight seal and anchoring in order to lock the patch in place and restore the integrity of the covered section. The final expanded ID of the patch is sufficiently large to allow standard upper completion equipment to be deployed through the patch. This paper will highlight the application limitations that had to be met, the solution selection process and the operational deployment of a record five expandable patches in a single wellbore. Deployment results and technology experience will be reviewed.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.004 | 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".