Prediction of temperature, pressure, density, velocity distribution in H‐T‐H‐P gas wells
Bibliographic record
Abstract
Abstract In this paper, we build a model of coupled differential equations concerning pressure, temperature density and velocity in H‐T‐H‐P (High Temperature‐High Pressure) gas wells according to the conservation of mass, momentum and energy. We present an algorithm‐solving model by the fourth‐order Runge–Kutta method. Basic data from the Dayi Well, 7100 m deep in China, are used for case history calculations and a sensitivity analysis is done for the model. Gas pressure, temperature, velocity and density along the depth of the well are plotted with different productions, different geothermal gradients and different thermal conductivities, intuitively reflecting gas flow law and the characteristics of heat transfer in formation. The results can provide a dynamic analysis of production for H‐T‐H‐P gas wells. © 2011 Canadian Society for Chemical Engineering
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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 | 0.000 | 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".