Determination of Optimal Conditions for Addition of Foam to Steam for Conformance Control
Notice bibliographique
Résumé
Abstract Heat is transferred into the heavy oil reservoirs through steam injection. It reduces the viscosity of the heavy oil and bitumen and makes them mobile for production. Steam oil ratio (SOR) directly affects the cost of operation and is an index of the process efficiency. Steam processes could be optimized through addition of chemical additives to steam to selectively prohibit unfavorable channeling, gravity override and steam loss to the high permeable thief zones. Injection of foam with steam for conformance control is considered as a solution for increasing steam flooding efficiency and optimizing reservoir performance. In this experimental study, a candidate surfactant is used to evaluate the optimal conditions for steam- foam application. Through a separate dedicated screening study at steam condition, one surfactant was identified which passed the required tests on solubility in injecting brine, foam generation, foam stability, surfactant thermal stability and its loss to reservoir rock surface, due to adsorption. This surfactant was co-injected in aqueous phase with steam to produce foam in porous medium. Core flooding tests were conducted at 260°C to evaluate the performance of foam with steam. The focus of this study was on determination of the optimal foam performance in different steam qualities and injection rates using steam (not non-condensable gases). Our tests were conducted in absence of oil and in a 30-cm core of less than 5 mD. Foam performance was monitored through differential pressures along the core as well as analysis of the foam in the effluent. Mobility Reduction Factor (MRF) allowed us to compare the performance of foam steam with steam-only process. Shear velocities of as high as velocity at well perforations and as low as one meter per day were considered and tested at different steam qualities. The range of steam qualities tested was from 3 5% all the way to 100%, which was a slug-format test. Our candidate surfactant produced most foam around 50% quality which seems to be a good balance between the proportion of gas and liquid that produce stable foam texture. Higher qualities leads to drying out the lamella and lower qualities do not introduce sufficient gas to liquid for foam generation. Our tests reveal that there is a critical velocity beyond which foam generation starts and the foam and surfactant fronts are moving separately. MRFs of larger than 10 was determined in our optimal conditions. Different steam qualities are tested in this study using real steam which condenses due to pressure rise along the core. Through these tests, operators could add significantly to their knowledge on how to best operate in adding foam to steam for a better reservoir performance.
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 | 0,002 |
| 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 ».