Omniphobic/superhydrophobic surface effect on oil and gas flow: A critical review
Bibliographic record
Abstract
Abstract Flow assurance in the petroleum business of the oil and gas industry ensures the efficient and continuous flow of hydrocarbons from production facilities to consumers. Impurities in oil and gas can cause corrosion and erosion, hydrate formation, scaling, and fouling, resulting in flow limits and reduced operating efficiency. The significant flow assurance issues must be managed through systematic exploration of effective mitigation and management approaches. The objective of this paper is to highlight the latest research in the field of flow assurance, including the application of superhydrophobic or omniphobic coatings to prevent scale growth, asphaltene precipitation, wax deposition, and hydrate formation. This review will provide new perspectives into the basic mechanistic mechanisms of deposition and blockage in oil and gas production systems, assisting in the development of novel methods compared to the employment of commercial chemical or mechanical techniques. Overall, the flow assurance engineers will gain new perspectives from this study regarding how to deal with the risk of pipeline blockage caused by the problems mentioned earlier.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".