Impact of formulation on the rheological and physiochemical properties of water in oil emulsion: application on drilling mud
Bibliographic record
Abstract
One of the main uses of water in oil emulsions in the petroleum industry is oil-based drilling fluids due to their rheological characteristics and various functions to keep a good drilling process. To achieve these characteristics many researches have been made to establish various formulations to reply to the technical needs and also to reduce the cost of these drilling fluids and their environmental effects. In this study, we prepared five formulations of water in oil emulsions using the additives versawet and versacoat as emulsifiers, organophilic clay VG69, and calcium carbonate CaCO3. Different rheological measurements have been applied to these five formulations to understand the effect of each additive on the rheological and viscoelastic behavior of water in oil emulsions. Studying these formulations allows for choosing better the needed technical drilling fluid with the minimum economical cost and the lowest environmental effect. Microscopic observation shows that the addition of quantities of organophilic clay type VG69 less than or equal to 4 g leading to the stability of the water/oil inverse emulsions, on the other hand, for quantities greater than 4 g, the emulsions are destabilized.
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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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".