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Enregistrement W4247209528 · doi:10.2523/84202-ms

A New Method for Measuring Solvent Diffusivity in Heavy Oil by Dynamic Pendant Drop Shape Analysis (DPDSA)

2003· article· en· W4247209528 sur OpenAlex
Yongan Gu

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Notice bibliographique

RevueProceedings of SPE Annual Technical Conference and Exhibition · 2003
Typearticle
Langueen
DomaineChemistry
ThématiquePetroleum Processing and Analysis
Établissements canadiensUniversity of Regina
Organismes subventionnairesPetroleum Technology Research Centre
Mots-clésExhibitionComputer scienceCitationSolventThermal diffusivityProcess engineeringChemistryEngineeringLibrary sciencePhysicsArt historyOrganic chemistryArt

Résumé

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A New Method for Measuring Solvent Diffusivity in Heavy Oil by Dynamic Pendant Drop Shape Analysis (DPDSA) Chaodong Yang; Chaodong Yang University of Regina Search for other works by this author on: This Site Google Scholar Gu Yongan Gu Yongan University of Regina Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Annual Technical Conference and Exhibition, Denver, Colorado, October 2003. Paper Number: SPE-84202-MS https://doi.org/10.2118/84202-MS Published: October 05 2003 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Yang, Chaodong, and Gu Yongan. "A New Method for Measuring Solvent Diffusivity in Heavy Oil by Dynamic Pendant Drop Shape Analysis (DPDSA)." Paper presented at the SPE Annual Technical Conference and Exhibition, Denver, Colorado, October 2003. doi: https://doi.org/10.2118/84202-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Annual Technical Conference and Exhibition Search Advanced Search AbstractThis paper presents a new experimental method and its computational scheme for measuring the diffusion coefficient of solvent in heavy oil under the practical reservoir conditions by dynamic pendant drop shape analysis (DPDSA). In the experiment, a see-through windowed high-pressure cell is filled with the test solvent at desired pressure and temperature. Then a heavy oil sample is introduced slowly through a syringe delivery system to form a pendant drop inside the pressure cell. The subsequent diffusion process of solvent into the pendant oil drop causes its shape and volume to change until an equilibrium state is reached. The sequential digital images of the dynamic pendant drop are acquired and digitized by applying computer-aided digital image processing techniques. Physically, variations of the shape and volume of the pendant drop are attributed to the interfacial tension reduction and the well-known oil swelling effect as solvent gradually dissolves into heavy oil. Theoretically, the dynamic pendant drop profile is governed by the Laplace equation of capillarity and the molecular diffusion process of solvent into the pendant oil drop is described by the mass diffusion equation. An objective function is constructed to express the discrepancy between the experimentally observed and the numerically predicted profiles of the dynamic pendant drop. The solvent diffusivity in heavy oil and the mass-transfer Biot number are used as adjustable parameters and thus determined once the minimum objective function is achieved. This novel experimental technique is tested to measure diffusivities of carbon dioxide in a brine sample and carbon dioxide in a heavy oil sample, respectively. It should be noted that, with the present technique, a single diffusivity measurement can be completed within an hour and only a small amount of oil sample is required. The interface mass-transfer coefficient at the solvent-heavy oil interface can also be determined. In particular, this new technique allows the measurement of solvent diffusivity in an oil sample at constant pre-specified high pressure and temperature. Therefore, it is especially suitable for studying the mass transfer process of injected solvent into heavy oil during solvent-based post-cold heavy oil production (CHOP).IntroductionWestern Canada contains tremendous heavy oil and bitumen resources1,2. Approximately 80% to 95% of the original-oil-in-place (OOIP) is still left behind at the economic limit after the cold production2. This is a large oil-in-place target for follow-up enhanced oil recovery (EOR) processes. After the primary production, most Canadian heavy oil reservoirs cannot be further exploited economically by thermal recovery processes because reservoir formations are thin and/or there is active bottom water. In the literature, some studies have been conducted to evaluate the other recovery methods for these heavy oil reservoirs2–5. Among these methods, vapor extraction (VAPEX) and other solvent-based post-CHOP processes are probably the most promising EOR techniques. In practice, the solvent can be carbon dioxide, flue gas, nitrogen, and light hydrocarbon gases, such as natural gas, methane, ethane, propane and butane. Keywords: coefficient, complex reservoir, interfacial profile, interface, optimization problem, upstream oil & gas, co 2, oil interface, enhanced recovery, heavy oil Subjects: Improved and Enhanced Recovery, Unconventional and Complex Reservoirs, Information Management and Systems, Oil sand, oil shale, bitumen, Artificial intelligence This content is only available via PDF. 2003. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,054
Score d'incertitude au seuil0,922

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,019
Tête enseignante GPT0,286
Écart entre enseignants0,267 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle