Through-Tubing Sand Control Repairs Damage to Openhole Gravel Pack in a Subhydrostatic Well
Bibliographic record
Abstract
Abstract Remedial Sand Control is a challenging operation that requires economic judgment especially in brownfields. The operation turns into a greater challenge when the well, that needs to have a damaged gravel pack screen repaired is a sub hydrostatic well. We carried out pioneering repair project that was simple and cost-effective with minimum logistics using thru-tubing sand control. This method adapts thru-tubing tool advantages of coiled tubing to convey and set a smaller sand screen in a damaged gravel pack bore. The operation started by cleaning out in the deviated wellbore, controlling the well from kicks and deploying a long sand screen string in open-well conditions. To use this technique, two main challenges had to be solved. First, a long sand screen string had to be deployed into the wellbore on a production platform without the assistance of the derrick or platform crane. We used a two-stage self-skidding jacking frame with a 4-ton hydraulic winch to deploy the screen string into the well. Each un-deployed component of the screen string was lifted up from the storage rack with an elevator and connected with the string in the wellbore above the Christmas tree by a hydraulic tong. The installed string was held above the Christmas tree by a pneumatic slip and bowl mechanism. Second, the method must control the well from unexpected kicks while the sand screen is being deployed. We used hydraulic hydraulic well control method, which involves spotting "damaged free" lost-circulation material (LCM) fluid along target intervals and topping up with kill fluid, we also prepared a mechanical solution as a back up during job execution.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".