Simulation of Depressurization for Gas Production From Gas Hydrate Reservoirs
Notice bibliographique
Résumé
Abstract Gas hydrates as a significant resource of natural gas have attracted considerable attention in recent years. However, the severe environmental conditions of gas hydrate reservoirs and the solid form of hydrates require extensive technological development before commercial gas production becomes possible. Numerical studies often give useful information for predicting the potential and technical viability of a recovery process. This paper presents a 2D cylindrical simulator for gas production from hydrate reservoirs. The model includes the equations for gas-water two-phase flow, conductive and convective heat transfer, and intrinsic kinetics of hydrate decomposition. The simulator is used to model a hydrate reservoir where the hydrate- bearing layer overlies a free gas zone, such as those discovered in the arctic. A well is drilled and completed in the free gas zone. Pressure reduction in the free gas zone leads to the decomposition of the overlying hydrate and subsequent production of the generated gas. In this paper, we study the impact of the overlying hydrate in improving the production performance of the underlying gas reservoir and investigate the effect of various parameters on gas production behaviour. The rate of gas generated and produced, pressure, temperature, and saturation distributions are studied to investigate the sensitivity of results on individual input parameters. The results suggest that the development of gas reservoirs with overlying hydrates can lead to significant production rates and that the top hydrates have a large impact on increasing the reserve and improving the productivity of the underlying gas reservoir. Introduction Today, increasingly more stringent environmental considerations require that clean sources of energy be found. It is therefore anticipated that the demand for natural gas will continue to increase significantly. Some studies indicate that the amount of methane trapped in gas hydrates in natural settings is 100 times that of conventional gas reserves(1, 2). Therefore, gas hydrates are being considered as a potential source for natural gas production. However, it is not clear what percentage of this huge resource is recoverable, and the technologies for recovering natural gas from hydrates are still under development. Sloan(3) has presented an extensive review of some suggested methods, including depressurization, thermal stimulation, and inhibitor injection. The least energy intensive process is thought to be the depressurization method, since in this method the heat of decomposition is provided by the surrounding formation. Modelling of gas production from hydrate reservoirs involves solving the coupled equations of mass and energy balances. A review of analytical and numerical models given by Hong et al.(4) suggests that two approaches with respect to conditions at the decomposition zone have been taken: equilibrium and non-equilibrium. In models using the equilibrium approach, the three-phase hydrate-gas-water interface is at a thermodynamic equilibrium. The underlying assumption in these models is that the intrinsic rate of hydrate dissociation is fast enough so that the overall rate of hydrate dissociation is controlled by other mechanisms, i.e., fluid flow or heat transfer. In non-equilibrium models however, the condition at the hydrate-gas-water interface is kinetically approaching equilibrium.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 source (Gemma direct ou Codex distillé), 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 ».