Estimation of Diffusion Coefficients in Bitumen Solvent Mixtures Using X-Ray CAT Scanning and Low Field NMR
Notice bibliographique
Résumé
Abstract Diffusion plays an important role in both VAPEX and Solvent Injection processes for oil/bitumen recovery. In this paper, X-ray CAT scanning and low field NMR have been used to obtain experimental data for the diffusion of several solvents in bulk bitumen. Low field NMR has been used successfully in determining both solvent content and viscosity reduction in heavy oil and bitumen mixtures with various solvents. NMR is also a potential tool for diffusion coefficient measurement in solventbitumen system (1). In this paper, the results of diffusion coefficient calculated from NMR is further discussed and compared with the results obtained from X-ray CAT scanning. X-ray CAT scanning takes advantage of density contrasts in the scanned sample through the measured CT number. With solvent diffusing into heavy oil or bitumen, the CT number changes during the process and provides the corresponded density of the mixture. Therefore, the concentration gradient distribution with distance can be obtained. A Fick type of equation can be written and an apparent diffusion coefficient can be calculated. This approach and the results of this analysis are presented along with an evaluation of the applicability of the assumptions in Fick's Law. Introduction With more attention for the recovery of heavy oil and bitumen in Alberta based on solvent processes, mass transfer between solvent and bitumen become an important process to be understood. However, only a few experimental values of the diffusion coefficient of various organic substances into bitumen are available in the open literature(2–5). To understand better the mass transfer phenomena, more experimental data are necessary, especially in liquid-liquid systems. This paper presents further research results to previous work(1). Traditionally an optical system is used to record time dependent patterns that can be photographed and then analyzed to yield either binary or ternary diffusion coefficients for the system of interest(6). The work presented here makes use of Xray CAT scanning and low field NMR as the tools for mixing pattern recording. Low field NMR has great potential as a tool for measuring properties of reservoir fluids and produced liquid streams(7). From a single NMR measurement of a fluid stream containing oil and water, the relative fractions of both liquids can be determined(8). As a solvent comes into contact with a heavy oil or bitumen sample, then the mobility of hydrogen bearing molecules of both solvent and oil change. These changes are detectable through changes in the NMR relaxation characteristics of both solvent and oil and can be correlated to mass flux and concentration changes. Fick's second law of diffusion is used to model such mass flux and consequent concentration changes, and an apparent diffusion coefficient can be calculated. This approach was presented in an earlier paper(1). In the present paper, this method is further discussed. Computer-Assisted Tomography (CAT) scanning using Xrays is also becoming an attractive tool for petroleum engineers. The method can give an image of a core in two or three dimensions with a very fine resolution and high accuracy.
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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 | 0,001 |
| 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 | 0,001 |
| 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 ».