Hibernia Q Block - Waterflooding to Increase Field Liquid Recovery with the Presence of a Gas Cap
Bibliographic record
Abstract
Abstract The problem cased by wax deposition during production and transportation of waxy oil has been receiving an increasing attention from the industry, especially with the off-shore projects expansion recently. Due to the high cost of those projects, an accurate modelling on wax precipitation and deposition is imperatively required to facilitate the design, development, and operation of those projects. While the wax precipitation models depict the thermodynamic behaviour of waxy oil, the modelling of wax deposition in production facilities and pipelines focuses on how soon wax would accumulate. The wax deposition simulation appears to be a more challenging task due to the high complexity and limited measured data available in the open literature. In this work, a compositional simulator is introduced to simulate the wax deposition in a pipeline. This model is founded on a thermodynamics model from our previous work and equipped with major wax deposition mechanisms as well as tuning function. Through four case studies, the model, with its prediction and tuning capability, has demonstrated a practical tool in flow assurance simulation. The results also suggest that a promising methodology can be applied in flow assurance study when the simulator is tuned with measurements from the high pressure deposition cell.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".