Application of Inflatable Packers for Production Testing and Conformance Problems in Algeria
Bibliographic record
Abstract
Abstract Through tubing inflatable packers conveyed with coiled tubing have proved to be ideally suited for multiple zones stimulation, water and/or gas control intervention where accurate fluid placement is essential for the success of the job. The high expansion ratio and sealing capabilities of modern elastomers used today in through tubing Inflatable have allowed operations in more hostile wells than previously possible, increasing job reliability. Conformance problems related to non desired water and/or gas production is drastically affecting the oil production of certain fields in Algeria. The exclusion of this water and/or gas represents a challenging task by itself. Even more under the hostility of multiple zones intervals open for simultaneous production, making the problem diagnosis a key factor for the success of the intervention. This paper presents the successful application of a methodology to diagnose and effectively exclude the non desired production with a novel technique using through tubing inflatable packers. A thorough discussion about the inflatable packers, deployment, inflation procedures, zone isolation and selective placement is presented. In addition, four case studies corresponding to the application of this methodology are discussed in detail. Two corresponding to exclusion of water and gas production, respectively, by selective placement of a x-link rigid polymer gel and two corresponding to production testing of isolated intervals. Finally, results of these interventions are presented. Including stabilized production before and after each treatment.
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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 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".