Full Field Chemical EOR in a Mature Southern Alberta Water Flooded Reservoir - The Little Bow Case Study
Notice bibliographique
Résumé
Abstract Despite the recent focus on unconventional resources such as shale gas and tight oil in North America, large unrecovered volumes of oil remain in conventional reservoirs making them viable candidates for chemical enhanced oil recovery processes. Replacing or following traditional water flooding with aqueous chemicals that use both surfactant & alkali to reduce interfacial tension and polymer to improve sweep efficiency has been successful in recovering incremental oil from these reservoirs. However, designing the chemical injection scheme is complex, and must be tailored to specific reservoir rock and fluid properties. A strategic design methodology can help provide an optimal, well-performing chemical formulation, even for challenging reservoirs. Currently, there are around ten Canadian chemical injection projects in operation with the latest being the Little Bow Upper Mannville "I" Pool. An ASP EOR project was initiated in this reservoir in March 2014 in a multiphase development plan. When the project was initiated, Little Bow oil (Phase 1&2) production was around 350 bbl/day. Successful implementation of this project is expected to result in incremental recovery of 5.2 million barrels of oil (12% of the OOIP) over the base waterflood. As of January 2016, 6.648 million barrels of ASP solution has been injected in the reservoir and the field is now showing first signs of incremental production. This paper presents a workflow that integrates laboratory results, geological and geophysical data and production history into an effective forecasting model. Complex geology and a long production history of the partly depleted Little Bow reservoir have presented a challenge for history matching the primary and water-flood production. Through an iterative process, a full field model was built, history matched, then used as a base case to determine an optimal operational design for the full field. A multidisciplinary team including geologists, exploitation and reservoir engineers collaborated to develop a 3D geological model and achieve the history match using an iterative approach; resulting in an idealized workflow and a superior history matched model. Using this model and an advanced optimization algorithm, a full field ASP operation design was optimized (based on NPV) for slug sizes, chemical concentrations, pattern design for injection/production wells locations, and drilling & workover locations. The optimized ASP injection scheme is implemented and some field results from January till June 2016 are presented in the paper.
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 ».