Effect of Squeeze Treatment Stages Mixing During Injection on Lifetime
Bibliographic record
Abstract
Abstract Scale inhibitor squeeze treatments are used to prevent scale deposition in production wells. A treatment consists of injecting a scale inhibitor slug at a concentration between 5 and 15%, referred to as the main treatment, followed by an overflush, which will push the chemical slug deeper into the reservoir. During injection, the stages might undergo some degree of mixing in the tubing. This paper addresses the impact such mixing would have on the squeeze lifetime. A consequence of mixing between main treatment and overflush stages in the well tubing would be that although the same overall mass of scale inhibitor was injected, it would be distributed over a larger volume of water and therefore be exposed to the rock formation at a lower concentration than planned in the design. The degree of mixing in the tubing depends on a number of factors, such as tubing length and diameter, and the pumping rate. The phenomenon is described by the longitudinal dispersion coefficient, which may be calculated. The resulting calculation may be defined as the spreading of a solute along the longitudinal axis, which leads to the spread of an initial high concentration slug with a low spatial variance to a final stage of low concentration with high spatial variance. The main objective of the paper is to study the effect of the degree of mixing of the main and overflush stages on the squeeze treatment lifetime. The net effect of full mixing would be that instead of there being two different stages at very different scale inhibitor concentration, a single stage at a lower concentration might be exposed to the rock formation. Two mixing profiles were considered, a short and long tubing; where the total injected volume is greater than and less than the total tubing volume, respectively. A number of levels of mixing were considered and compared to the base case, where no mixing was allowed. The results showed that squeeze lifetime is not significantly reduced if mixing occurs in a short tubing interval, whereas it can be reduced by up to 20% in a longer tubing interval.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".