A Comprehensive Mathematical Model for Estimating Thermal Efficiency of Steam Injection Wells Considering Phase Change
Notice bibliographique
Résumé
Abstract Improving thermal efficiency of steam injection wells is an important goal in the process of steam injection for heavy oil recovery. The main objectives of this paper are to establish a comprehensive mathematical model for estimating the thermal efficiency of steam injection wells and to make some suggestions on how to achieve the above goal. The mathematical model is composed of four sections. The first one is about prediction of thermophysical properties of injected steam considering phase change. In this section, if wet steam is not cooled to liquid water, slippage between gas and liquid phases is taken into account in calculating pressure drop based on momentum balance principle. In addition, a complete expression for steam quality distribution in wellbores is derived in detail. However, if phase change occurs, we can obtain an implicit equation for fluid temperature by combining energy balance and Coulter-Bardon equations. In the second section, steady-state heat transfer inside the wellbore and transient radial conduction in the formation are coupled at the cement/formation interface, based on which the wellbore heat loss rate is determined. Next, the thermal efficiency is estimated by using both direct and indirect methods. Finally, the mathematical model is solved iteratively for each segment and a detailed calculation flowchart is also provided. The proposed model is validated by comparing simulated steam pressure, temperature and quality with measured field data from Liaohe Oilfield, and the direct and indirect methods of estimating the thermal efficiency prove to be reliable. Then, using the validated model, we analyze the effects of wellhead steam quality, injection rate and thermal conductivities of insulation materials on thermal efficiency of steam injection wells. The results indicate that enhancing the wellhead injection rate and using low thermal conductivities of insulation materials can greatly improve the thermal efficiency. But it is not a good choice to achieve this goal by improving the wellhead steam quality. Moreover, the paper shows that our methods for estimating the thermal efficiency of steam injection wells can also be applied to concentric-dual tubing steam injection wells. In this paper, the comprehensive mathematical model for estimating the thermal efficiency of steam injection wells may be worthy of more attention, because it has not been widely reported in the literature. More important, phase change from steam/water two-phase flow to liquid water single-phase flow in deep wells is also considered in our study.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».