A New Semi-analytical Model for Predicting Steam Pressure and Temperature in Annuli
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Bibliographic record
Abstract
Abstract An excellent design of steam injection projects requires accurate prediction of bottomhole steam pressure, temperature and quality. However, it is not always easy to meet the requirement when we design concentric dual-tubing steam injection schemes due to the complexity of downward steam/water flow in annuli. Also, previous methods for estimating pressure gradient in annuli, such as mechanistic models and empirical correlations, are either time-consuming or inaccurate. In this study, we present a new semi-analytical model to predict steam pressure and temperature in annuli. It is based on Coulter-Bardon equation and on mass and energy balances in the wellbore. A more rigorous thermodynamic behavior of steam/water mixture is taken into account. More importantly, one-to-one correspondence between pressure gradient and temperature gradient of saturated steam is reasonably developed and applied in our further derivation and simplification. It is because of the simplification that we do not have to use mechanistic models or empirical correlations to separately calculate the pressure drop in annuli, which is significantly different from previous work, including Sagar et al. (1991), Alves et al. (1992) and Hasan et al. (1994) models. Our solution procedure is straightforward, the equations of steam pressure, temperature, quality, steady-state heat transfer in the wellbore and transient heat transfer in the formation just need to be coupled and solved iteratively for each segment. Our model is validated by comparison with measured field data from Liaohe Oilfield, Petro China. The results indicate that the direction of heat transfer between inner and outer tubing depends on wellhead conditions and temperature drop in each tubing. We also show that the equivalent hydraulic diameter is not always a suitable characteristic dimension for steam/water flow in annuli. Moreover, the paper shows that our method can also be applied to single-tubing steam injection design. The predicted results from our modified model are also compared with those from CMG simulator and previous work in our study.
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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 it