Notice bibliographique
Résumé
Abstract Approximately 80% of the Canadian Oilsands are too deep to be economically mined. SAGD - an in situ recovery technology has come of age and is emerging as the technology of choice in exploitation of these resources. The current major challenge that SAGD faces is the use of expensive heat to generate steam. The authors have previously described an improvement to SAGD - Solvent Aided Process (SAP) that aims to combine the benefits of using steam with solvents. In SAP, a small amount of hydrocarbon solvent is introduced as an additive to the injected steam during SAGD. SAP holds the promise to significantly improve the energy efficiency of SAGD thus reducing the heat requirement. This paper describes field testing of SAP at Encana's Christina Lake SAGD Project. In addition to dwelling on some of the important parameters of a SAP test, it outlines the design considerations for the pilot and associated facility modifications. The design duration of the experiment calls for an assessment of reservoir performance on a long-term basis. However, some preliminary observation and indications are discussed. Additionally impact of (a) timing of solvent initiation and (b) the well pair spacing on process performance is also explored based on modeling exercises. Introduction In SAGD, oil viscosity is reduced by heating with steam1,2. In SAP3,4,5, solvent dilution is also taken advantage of to aid this viscosity reduction. The result is enhanced rate of oil production and recovery leading to superior economics with lower energy intensity and impact on environment. In the context of doing away with the heating requirement, VAPEX - a process similar to SAGD but employing only hydrocarbon vapor instead of steam has been described in literature6,7,8,9, however, its development is awaiting a successful field trial. Use of solvent with steam for oil recovery is also discussed in literature10,11,12,13 with a focus on enhancement of steam displacement or steam stimulation. Using solvent with steam in SAGD context offers some practical advantages. The pressure in the vapor chamber does not need to be supported by a non-condensable as required in some versions of VAPEX. This means that the progression of the vapor chamber in SAP does not get overwhelmed by the heat/mass transfer resistance at the vapor/oil interface. Recently others14,15 have also discussed benefits of using solvents with SAGD in a process similar to SAP. Reference 14,15, advocate use of those solvents that match the condensation characteristics of steam at the operating conditions. Previous description3,4,5 and data, does not suggest such requirements for SAP. Encana has been developing SAP since 1996 and piloted the process first at its Senlac Thermal Project in 2002 and encouraged by the results is presently testing SAP for in situ bitumen extraction at its Christina Lake Thermal Project. In Senlac SAP Pilot, some description of which has been given previously5, solvent (butane) was co-injected in a well pair which was already in SAGD operation. Judging by the production rates at the time of SAP start, the steam chamber had risen to the top of the reservoir already for a few months.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,011 | 0,002 |
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 ».