Rigless Intervention Pipe Expansion Method to Seal Gas or Fluid Leaks
Bibliographic record
Abstract
Abstract Starting in April 2023 in the Illinois Basin, unique energetic expansion charge technology was employed to expand pipe sections without compromising pressure integrity. The technology effectively sealed off annular seepages through microannuli and small channels in gas storage wells completed in the 1960s. This rigless method's success at sealing compromised cement seals was confirmed by the absence of pressure buildup on surface vent data on the first three wells in the workover campaign over a monitoring period of 12 months. An additional six wells are being monitored as part of the 12-month monitoring period. The cement repair method used in this operation introduced no restrictions, obstructions, or additional leak paths, maintaining well integrity and full wellbore access post-intervention. No additional well intervention work was required after the wireline-deployed energetic expansion charge operations. This efficient rigless operation remediated annular cement integrity issues in less time than conventional techniques and reduced costs by up to 80%. It also reduced greenhouse gas emissions compared to traditional methods that require rig operations powered by diesel generators. The cement repair results in the Illinois Basin wells, where energetic expansion charge technology was employed, were comparable to cement repair operations results on wells in other U.S. basins where small-footprint, rigless operations are preferred to reinstate well integrity as part of plug-and-abandon or live well operations. Energetic expansion charge operations increase cement density and remediate annular cement integrity issues behind 3.5- to 20-in. OD pipes. The wireline-deployed energetic expansion charges are customized to pipe dimensions, weight, grade, and downhole hydrostatic pressure. This precision lets them reliably expand the pipe to confine cement and reduce cement permeability, effectively closing small stress cracks and microannuli.
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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 | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".