Viscosity Determination of Heavy Oil and Bitumen Using NMR Relaxometry
Notice bibliographique
Résumé
Abstract Knowledge of oil viscosity is important when estimating hydrocarbon reserves and evaluating the potential for waterflooding or EOR processes. This information is especially important in heavy oil and bitumen, as viscosity is usually the major impediment to recovery of these reserves. As oil viscosity increases, obtaining a laboratory measurement is difficult and prone to error, and viscosities measured in the lab may not be representative of field conditions. Nuclear magnetic resonance (NMR) is therefore presented as an attractive alternative method for determining oil viscosity. Several correlations already exist for determining oil viscosity using NMR. Some of these correlations compare the geometric mean T2 relaxation time to oil viscosity, while others relate viscosity to the apparent hydrogen index. This paper examines these different models on a suite of conventional and heavy oil samples. It is concluded that none of the existing models can accurately predict oil viscosity for both conventional and heavy oils, especially for oils with viscosity higher than 20,000 cP. All the measured oil samples show a correlation between oil viscosity and the geometric mean T2 relaxation time, and also between viscosity and relative hydrogen index. This is consistent with what other experimenters have noticed. An empirical model is developed, correlating oil viscosity to both of these parameters. Unlike previous models, this model can accurately predict oil viscosity for both conventional and heavy oil. The wider range of this model makes it useful for laboratory analysis of oil viscosity using NMR. If the results of this model can be applied to in situ oils, NMR can be used as a logging tool to characterize heavy oil and bitumen formations. The model presented in this paper is the first step towards successfully predicting viscosity in situ. Introduction Determination of oil viscosity is extremely important to the development of any potential oil reservoir. If waterflooding is being considered as a recovery scheme, the mobility ratio between oil and water will have a strong effect on the macroscopic sweep efficiency of the waterflood. Likewise, when considering possible EOR schemes, oil viscosity is one of the most serious impediments to the success of these schemes. Oil viscosity is also a required input parameter for reservoir simulation and well testing. In heavy oil and bitumen reservoirs, the high oil viscosity is often the limiting factor to efficient oil recovery. Waterflooding cannot be used in these reservoirs, due to the adverse mobility ratio between oil and water. The oil is so much more viscous than water that injected water will move through the oil in the form of "viscous fingers," which lead to early water breakthrough and poor sweep efficiency. If attempting a miscible solvent or gas flood, knowledge of oil viscosity is necessary for estimating the efficiency of the flood. Due to the negative effects of the adverse mobility ratio, viscosity reduction is the main focus of EOR schemes in heavy oil reservoirs.
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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 | 0,001 |
| 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 ».