Optimization of a Scale Treatment in the Uinta Basin—A Case History
Bibliographic record
Abstract
Abstract The precipitation and accumulation of scale deposits is a major concern for production companies in the Uinta Basin. Since 2003, conventional hydraulic fracturing treatments with scale inhibitor pumped simultaneously as an additive have been offered to this region. This service proved to be very effective in the Permian Basin using borate crosslinked fracturing treatments (with scale inhibitor concentrations as low as 5 gal/mgal). However, these design criteria and formulation of the scale treatments had to be changed significantly to be effective in the typical Uinta Basin gas well environment: low permeability (<0.1 md), multi-layered, commingled gas reservoirs. Typically, a well completed and placed on production without any scale inhibitor in the Uinta Basin may show signs of scale buildup in as little as 30 days. The effects of the scale accumulation can be seen everywhere from an exaggerated production decline to scale deposition on production equipment. This paper outlines the learning procedure and present designs, testing and monitoring results from scale treatments together with a case study from the Uinta Basin.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".