Prediction of Asphaltene Stability for Live Oils and Chemical Selection to Mitigate Deposition and Fouling
Notice bibliographique
Résumé
Abstract The precipitation of asphaltenes from crude oil can be induced by changes in temperature, pressure and composition. This study reviews a thermodynamic approach to describing the solubility of asphaltenes with a model that accounts for all of these effects. This solubility model can then be used to assess the relative stability of crude oil systems at all stages of production from the reservoir to the tank farm. The impact of changes in temperature, pressure and composition are individually addressed. Increasing temperature only is shown to lower the absolute values of both the oil solubility and onset solubility parameters. Also, temperature has little impact (if any) on the relative stability of the asphaltenes (provided that no chemical changes occur). The effect of pressure on the impact of dissolved gases is captured by the model, and shown to have a potentially strong influence on asphaltene solubility. Finally, examples are presented describing the effect on oil stability due to changes in composition under both pressurized and ambient conditions. Addition of miscible injectant to reservoir fluids, and blending of bitumen with diluents in surface facilities are addressed. In both of these examples, prior knowledge of problematic compositions and blending ratios could help to avoid the occurrence of asphaltene precipitation in operations. 1.0 Introduction Asphaltene precipitation can have a strong, negative impact on productivity and maintenance costs due to plugging of the reservoir formation, well-bore equipment and flow-lines, and due to fouling of surface facilities. Oil instability, leading to asphaltene precipitation, may be induced by changes in temperature, pressure and chemical composition of the produced oil. Pressure depletion above the bubble point causes an expansion/increase in the volume fraction of the dissolved hydrocarbon gases and reduces solvency towards asphaltenes. At pressures below the bubble point, the separation (evaporation) of light ends can improve the solvency of the remaining fluid towards asphaltenes. The development of new wells in the vicinity of existing production facilities may entail commingling of oils, resulting in a mixed fluid of very different composition. This mixed fluid may be unstable, leading to asphaltene precipitation and flocculation (aggregation). Enhanced oil recovery methods by using gas injection / miscible injectant, or carbon dioxide may also adversely impact oil stability leading to asphaltene precipitation and deposition. Ideally, measurements should be made to assess the stability of oils under a variety of conditions. Unfortunately however, the measurement of asphaltene stability at reservoir conditions is rather expensive and may not actually be feasible due to an absence of "live oil" samples and/or due to difficulties in obtaining such samples of suitable quality and size. Consequently, there is continued interest in the development of predictive models to assess the stability of oils, both at reservoir conditions and as a function of pressure depletion. Additionally, it is informative to extend the application of these models to include the effects of dissolved hydrocarbon gases on oil stability and to assess the effect of commingling potentially incompatible fluids.
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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) | 0,000 | 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 ».