Case History: Innovative Slimhole Techniques Resolve Completion Problems for a Major Operator in the Gulf of Mexico
Bibliographic record
Abstract
Proposal A major operator in the Gulf of Mexico had planned to run a cased, slimhole completion. The formation was sandstone, and thus, gravel packing would be required. The well was drilled, but the liner became stuck at 1500 feet from bottom. The operator did not want to pursue the sidetrack option, and unless another solution could be developed, the well project would have to be abandoned. The service/engineering company working with the operator felt that a solution could be developed that would allow the well to be completed. The operator and service company representatives formed a dedicated team and developed a plan that would provide the perforation needs, solve the packer problem, and perform the gravel pack satisfactorily from a service vessel. This paper will discuss how an unusual solution was planned and executed and was successful in resolving the problems. This case history is an example of how a service company and operator can work together to resolve difficult completion scenarios and provide win/win solutions for all parties. With regards to innovative completion techniques, the completion configuration that was developed using a smaller liner, the small bore tools and compatible gravel-pack design for the smaller liner as well as the unusual use of an enhanced low-profile prepacked (ELP) screen were significant to the success of this completion. The unusual completion was run as planned. The gravel pack was successfully performed with returns throughout the treatment. The well is on line and performing better than expected.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.005 | 0.004 |
| Insufficient payload (model declined to judge) | 0.009 | 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".