Measurement and Modelling of Asphaltene Flocculation From Athabasca Bitumen
Notice bibliographique
Résumé
Introduction Heavy crude oil production is increasing as conventional oil supplies are depleted. However, heavy oils are rich in asphaltenes, which can precipitate, flocculate, and deposit during transportation and processing. Current methods of treating the deposit are often only partially effective. In order to better mitigate asphaltene deposition, a better understanding of asphaltene precipitation and flocculation is required. This project focuses on the formation and flocculation of asphaltene particles in solutions of n-heptane and toluene at 23 °C and atmospheric pressure. Heptane and toluene were selected because toluene is a good solvent for asphaltenes whereas asphaltenes precipitate in heptane. Hence, mixtures with different proportions of precipitated asphaltenes could be investigated at different solvent conditions. EXPERIMENTAL METHOD Athabasca coker-feed bitumen was obtained from Syncrude Canada Ltd. Toluene and n-heptane were obtained from Aldrich chemical Company with 99%+ purity. Asphaltenes were precipitated from the bitumen with the addition of n-heptane at a 40:1 volume ratio of heptane-to-bitumen and non-asphaltenic solids were removed by centrifugation. Details of the precipitation are provided elsewhere [7]. To prepare a solution of asphaltenes in heptane and toluene, the asphaltenes were first added to toluene and sonicated for 1 hr at 23 °C to ensure that all the asphaltene dissolved. Asphaltene precipitation was induced by the addition of n-heptane in 60:40 and 70:30 n-heptane: toluene volume ratios. Asphaltene concentrations of 0.05, 0.08, and 0.1 kg/m_ were considered. The growth of asphaltene floccs was observed over 6 hours using a Brinkmann 2010 particle size analyzer. The particle size distribution is determined from the time of transition of the particles (or flocs) through a laser [5]. Samples were placed in standard 1 cm × 1 cm square optical-glass cuvettes obtained from Hellma cells Inc. A three-speed magnetic stirrer was employed to disperse the asphaltene particles within the cuvette. FLOCCULATION MODEL The probability of flocculation is a combination of the probability of a collision (characterized by diffusion time, τdiff) and the probability of a collision resulting in flocculation (characterized by reaction time, τrxn). In well mixed systems, τdiffdiff < < τrxn and flocculation is reaction-limited. In this limit, particles may collide with each other numerous times before they actually react (flocculate). The problem can then be approached using classical rate equations of the form: Equation (1) (Available in full paper) where Ni denotes a floc consisting of i individual particles. Cluster-cluster addition is the dominant mechanism in reaction-controlled flocculation. Flocculation is opposed by fragmentation, which can be a combination of surface erosion and shattering [3]. For a monodisperse distribution of individual particles, the derivative with respect to time of the number concentration, nk, of flocs of diameter dk is then given by: Equation (2) (Available in full paper) where Fi, j, Si and Ei are the number of reactions per unit volume per unit time that result in flocculation, shattering or surface erosion processes, respectively. The reaction terms are defined as follows: Equation (3) (Available in full paper)
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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) | 0,001 | 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 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 ».