Cold Production: Analysis of Oil Foaminess and Sand Dilatancy
Notice bibliographique
Résumé
Abstract Cold production of heavy and extra heavy oil is a relatively new technology; nevertheless it accounts for a considerable share of total heavy oil production, both in Canada and in Venezuela. In spite of the conspicuous exploitation of this insitu recovery process, a recognized rationale of the underlying mechanisms is still lacking. Two main schools of thought have appeared in the last 15 years in the open literature: the first one has been focused only on the atypical PVT and flow properties of heavy oil below the bubble point (the so-called "foaminess"), while the second one has been concentrated on the peculiar rock mechanics behaviour of unconsolidated sand (sand compaction/dilation and permeability evolutions). In this study models for both aspects were included into a new framework with the aim of better understand the relative weight of each mechanism. Results of this activity allowed to gain new insights into the involved fenomena. Introduction Cold production with sand (CHOPS) contributes for more than half million barrels a day of Canada heavy oil production. To meet demand growth in world fuels in future years requires both the deployment of new technologies and an increase of the performance of existing technologies like cold production. In spite of the fact that big efforts have been addressed through the modeling of cold production of foamy oils, a recognized model able to explain accurately the oil production when sand is allowed to flow is not yet available. This might be explained by the complexity of the process, that involves peculiarities on multiphase (oil/gas/water/sand) flow in porous media, phase separation kinetics (neglected in conventional reservoir modeling) in deformable unconsolidated sands (geomechanics cannot be ignored) In this study some models already used in previous heavy oil literature studies and a recent public rheological model developed for volcano magma flow were picked up. In order to understand the coupling effects between all mechanisms the new model was solved numerically in a full coupling framework [1]. Rational for coupled models Heavy oils show good production in lab tests carried out below bubble pressure due to the high viscosity of oil that prevents gas bubbles to coalesce [2]. The use of conventional reservoir modeling simulators to explain such tests leads to rate dependant relative permeabilities. Although some authors claim that performing lab tests at different flow rates allows to scaleup to field conditions, huge draw-downs are present in the lab experiments that might seldom be realistic in the fields: scale-up will be therefore an extrapolation to very low flow rates. On the other hand geomechanics studies (see [3] and references therein) are able to match field data production histories with porosities and permeabilities which might be not reliable. The need of the coupling of both aspects (foaminess and geomechanics) appears therefore naturally. According to us, in fact, a synergistic effect could take place in particular conditions: if the presence of a high porosity front (sand dilatancy front) couples with the bubble point pressure advance inside the reservoir, a bigger driving force for enhanced foamy oil flow might exist.
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 | 0,001 | 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 ».