Phase state variations for supercritical carbon dioxide drilling
Bibliographic record
Abstract
Abstract A phase state prediction model during supercritical carbon dioxide (SC‐CO2) drilling is established, considering the enthalpy changes caused by the flow work variations and changes in kinetic energy, as well as the potential energy caused by the fluid velocity along with physical property variations. The results show that variations in the flow work affect the temperature field of the SC‐CO2 fluid significantly. Phase state transitions of the fluid in the drill pipes and the annulus exist; in this example, the depth of the phase transition point in the drill pipes is in the range of 600 to 1000 m, while in the annulus, it is in the range of 400 to 700 m. Different results are observed when the phase state prediction is conducted by adjusting the discharge capacities, injecting temperature and pressure. When the discharge capacity is increased, the phase transition points in the drill pipes and the annuluses move downward; the pressure of the bit nozzle upstream increases gradually, while the pressure of the bit nozzle downstream changes slightly. When the wellhead back pressure is increased, the depths of the phase transition points in the drill pipes and the annulus decrease. Moreover, the pressure variations of the bit nozzle upstream and downstream can be divided into two stages: the fast growth stage and the slow growth stage. When the injection temperature is increased, the depths of the phase transition points in the drill pipes and the annulus are reduced; the temperature drop and the pressure drop at the nozzle change slightly. © 2015 Society of Chemical Industry and John Wiley & Sons, Ltd
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".