Induction Time of Hydrate Formation in Water-in-Oil Emulsions
Bibliographic record
Abstract
Blockage of pipelines due to hydrate formation is a major problem for subsea flow assurance. Induction time for hydrate formation from the multiphase system within a pipeline is a critical parameter to determine whether hydrates may form at a given time. In this work, the induction time for hydrate formation in water-in-oil emulsions was investigated under different conditions. For this purpose, an autoclave with an online viscometer was designed and built. Based on the viscosity variation observed in the experiments during hydrate formation, a new avenue for defining induction time is proposed, which should be more convenient for determining the hydrate formation time in some pipelines. As hydrate formation in emulsions is more complicated than in pure water, the effects of several factors were considered in this study, including water cut of the emulsions, shear rate, driving force, and memory effect. Additionally, wax precipitation is also a common problem in subsea pipelines and can impact flow assurance when hydrate formation and wax precipitation both occur. Consequently, the effect of wax solid particles on hydrate formation was also considered in this work. The presence of wax particles is observed to impede hydrate formation. In this work, it is determined from induction time that the hydrate formation is initiated at the water–oil surface for water-in-oil emulsion. Moreover, the memory effect can shorten induction times of hydrate formation due to the remaining small CO 2 bubbles at the surface of water droplets.
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 | 0.000 |
| 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 | 0.001 |
| 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 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".