Integrated Static and Dynamic Big-Loop Modeling Workflow for Assisted History Matching of SAGD Process with Presence of Shale Barriers
Notice bibliographique
Résumé
Abstract Steam Assisted Gravity Drainage (SAGD) has been widely applied to unlock hydrocarbon resources in oil sands reservoirs. This method uses steam, which is generated at the surface, to heat a formation and create a steam chamber around an injector. Past studies have indicated that reservoir heterogeneity is one of the crucial factors that directly affectthe performance of the SAGD process. This paper presents an innovative integrated modeling approach for evaluating, assisted history matching, and production forecasting of the SAGD process with the presence of a complex shale barrier system in oil sands reservoirs. As SAGD is a strongly geological dependent recovery process and, unfortunately, there are many uncertainties associated with reservoir geology in reality. Therefore, it requires generating a large number of geological realizations to capture the critical effects of geology, especially with the presence of shale barriers, in history matching and field development planning of the SAGD process. To quantify the impact and improve the quality of history matching compared with the traditional method, an efficient integrated workflow has been developed in which geological information generated from a geological modeling package is automatically updated for a reservoir simulator and controlled by an intelligent optimizer in a big-loop modeling approach. A detailed workflow on the integrated modeling approach that includes shale barriers for a typical oil sands reservoir is described in the first section of this paper. Shale bodies are geostatistically distributed in the geological models. A comprehensive parametric study was conducted with numerous geological realizations to identify the critical role of shale barriers in SAGD performance including shale geometry, shale length and thickness, shale distribution and proportions. Then the Bayesian algorithm with a Proxy-based Acceptance-Rejection sampling method is employed for assisted history matching of SAGD production profiles. With the presence of complex shale barriers, it requires simultaneous updating of both geological and reservoir engineering parameters. Using the proposed approach, the global history matching errors were drastically reduced in all production wells. Validation results indicate that the integrated modeling approach effectively helps to update the properties and distribution of shale barriers to find the closest geological distribution compared to the true solution. Finally, an ensemble of the best-matched simulation models is used to perform a probabilistic forecasting to capture the uncertainties in future production profiles. Not limited to history matching ofthe SAGD process, the proposed approach can be also applied to different complex problems such as robust optimization for various recovery methods from conventional to unconventional reservoirs.
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 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 ».