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Enregistrement W1987698143 · doi:10.2118/2004-061

Estimation of Residual Gas Saturation From Different Reservoirs

2004· article· en· W1987698143 sur OpenAlexafffund
Meng Ding, Apostolos Kantzas

Notice bibliographique

RevueCanadian International Petroleum Conference · 2004
Typearticle
Langueen
DomaineEngineering
ThématiqueHydraulic Fracturing and Reservoir Analysis
Établissements canadiensUniversity of Calgary
Organismes subventionnairesCanada Research Chairs
Mots-clésResidualSaturation (graph theory)EstimationEnvironmental sciencePetroleum engineeringComputer scienceStatisticsGeologyMathematicsAlgorithmEngineering

Résumé

récupéré en direct d'OpenAlex

Abstract Residual gas saturation is a crucial number to estimate the gas recovery in gas reservoirs with active aquifers. Water influx in gas reservoirs has long been recognized as an important cause of gas trapping in water-wet reservoirs. In this study, the residual gas saturation to water influx was investigated in 47 core plugs, including 29 sandstone plugs from different areas, 2 Berea sandstone plugs and 16 carbonate plugs. Over 100 different experiments were performed, including spontaneous water imbibition and forced water imbibition tests, primary imbibition and secondary imbibition tests, counter current and co-current imbibition tests. Measurements indicated that the value of residual gas saturation depends on many factors, including reservoir properties, the capillary number, experimental procedures, fluid properties and also very strongly depends on the gas solubility and compressibility. The residual gas saturation value from primary and secondary imbibition tests was also used to compare against literature models. Modified models were developed in order to fit the experimental data better. The residual gas saturation results show that gas recovery should be high under spontaneous imbibition and extremely high under the forced imbibition. However, trapped gas in reservoirs with active aquifers remains as high as 90%. Hopefully this paper can provide some insight for enhance gas recovery in gas reservoirs with active aquifers. Introduction Recovery of natural gas from reservoirs with a naturally occurring underlying aquifer and aquifer gas storage are common projects in gas reservoir engineering. In both types of projects large volumes of gas become trapped and cannot be recovered. Once gas becomes trapped, conventional wisdom dictates that it is very difficult to remobilize. It is very important to calculate the optimum gas recovery and if residual gas saturation values are high, to further develop a strategy of enhancing gas recovery. Experimental research work was presented in Kantzas et al.1, in which experiments were performed in both sandstone and carbonates reservoirs and residual gas saturation was evaluated. Some factors such as wettability, imbibition rate and experimental procedures, which affect the residual gas saturation, were discussed. Also different residual gas saturation predictive models from the literature were applied in their work. Continuation of this research work was presented in Ding and Kantzas 2–4, in which the residual gas saturation evaluation from different reservoirs and at different conditions was addressed. The efficiency of gas recovery by water imbibition was described in Crowell et al5. The different factors, which affected residual gas saturation, were addressed. It was shown that gas recovery is a strong function of the initial gas saturation and that the maximum recovery is obtained at zero initial water saturation. Different sandstone plugs were used in the experiments. It was shown that similar residual gas saturation values were obtained by both free imbibition and imbibition at a constant flow rate. A slight increase in gas recovery with a reduction of interfacial tension was observed in Berea slabs. Suzanne et al.6, 7 evaluated the residual gas saturation through 60 relationships between initial gas saturation (Sgi) and residual gas saturation (Sgr), which covered a large set of sandstone plugs.

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 distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,106
Score d'incertitude au seuil0,937

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,010
Tête enseignante GPT0,214
Écart entre enseignants0,203 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations9
Publié2004
Routes d'admission2
Résumé présentoui

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