Prevention of Acid-Induced Asphaltene Precipitation: A Comparison of Anionic Vs. Cationic Surfactants
Bibliographic record
Abstract
With the recent proliferation of horizontal drilling specifically targeting oil-bearing reservoirs, high-strength-acid-fracturing treatments in the Beaverhill Lake formation in northern Alberta have increased dramatically in both product volume and number of treatments. The Beaverhill Lake formation is a limestone/calcareous shale that produces a desirable mid- to high-API sweet crude oil. Although the crude oil typically has a low concentration of asphaltenes, the oil is sensitive to acid and/or iron-induced asphaltene precipitation. As the acid strength increases and ferric iron is dissolved into solution, it becomes increasingly difficult to chemically prevent the asphaltenes from precipitating. Acid blends designed to prevent asphaltene precipitation also tend to be emulsifying with the crude oil; therefore, a careful balance between antisludge additives and nonemulsifiers must be found. The objective of this study is to compare anionic and cationic antisludge agents, and to determine if there was an observable benefit in production when using a specific type of antisludge agent in the Beaverhill Lake formation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".