Field Measurements of Low Energy Oil Sands Mobility
Notice bibliographique
Résumé
Abstract The bitumen contained in Axe Lake Discovery in Saskatchewan has very high viscosity, well over 10 million centipoises under original reservoir condition. Since bitumen viscosity decreases with increasing temperature even at low temperatures, and since the Axe Lake reservoir is highly permeable and extremely coarse grained, preliminary reservoir simulations indicated that it is possible that effective, early time, communication between production wells at the bottom of the reservoir can be established by efficient low energy heating and intermittent water pressure pulsing. In order to evaluate the heating concept, we measured the response of the reservoir to heating with down-hole heaters at low temperatures (100 °C). A description of the field test is provided. Different analytical formulations and simulation models were used to analyze the results of the field test and the analyses were compared to prior published work. Field results were also used to determine effective thermal conductivities and effective mobilities at low temperatures for different grid sizes using Cartesian, radial and hybrid simulation grids. A comparison to analytical heat transfer formulations under different boundary conditions is discussed. Calibrated simulations show that not only can the heater be used to preheat the formation but also as an efficient bitumen viscosity reduction tool to increase bitumen mobility during the full bitumen production life of the reservoir. Moreover, high temperature heaters can be combined with cold water injection to generate steam in the reservoir directly. The paper concludes with a simple analysis which shows that such a combined technology can produce bitumen more efficiently and economically when compared to conventional SAGD. Introduction Axe Lake Discovery is located in northwestern Saskatchewan, about 90 km northeast of Fort McMurray. The bitumen reservoirs are buried about 200m below the surface. The bitumen is quite heavy and highly viscous, with a viscosity of over 10 million centipoises at original reservoir condition. Since bitumen viscosity decreases when the temperature rises, thermal technologies such as steam and hot water injection have become the preferred means for bitumen recovery. However, the bitumen reservoir at Axe Lake is relatively shallow and the efficient recovery of bitumen may be not possible using high pressure steam and hot water injection. Preliminary reservoir simulations indicated that it is possible to establish effective communication between producers at early time by efficient low energy heating and intermittent water pressure pulsing. Measuring the response of the reservoir to heating with downhole heaters at low temperature 100 °C, a two-stage test was planned and the second stage is currently being implemented. Different analytical formulations and simulation models were used to analyze the results of the measurement. The effective thermal conductivity and mobility of the bitumen at low temperature will be obtained from the results. Simulation studies also indicated that it was possible to obtain bitumen recovery effectively and economically using high temperature down-hole heater combined with cold water injection. This method takes advantage of simple and safe surface facilities and without losing heat outside the wells when compared to conventional steam injection from the surface.
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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 | 0,000 |
| 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) | 0,001 | 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 ».