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Enregistrement W4255491136 · doi:10.2118/2007-032

Clarifications on Oil/Heavy Oil Recovery Under Ultrasonic Radiation Through Core and 2D Visualization Experiments

2007· article· en· W4255491136 sur OpenAlexafffundabout
Kamyar Naderi, Tayfun Babadagli

Notice bibliographique

RevueCanadian International Petroleum Conference · 2007
Typearticle
Langueen
DomaineEngineering
ThématiqueEnhanced Oil Recovery Techniques
Établissements canadiensUniversity of Alberta
Organismes subventionnairesNatural Sciences and Engineering Research Council of Canada
Mots-clésVisualizationCore (optical fiber)Ultrasonic sensorPetroleum engineeringEnvironmental scienceComputer scienceMaterials scienceAcousticsGeologyPhysicsTelecommunicationsArtificial intelligence

Résumé

récupéré en direct d'OpenAlex

Abstract Our previous research on the effects of ultrasonic waves on oil recovery conducted at the University of Alberta had showed that capillarity and interfacial tension (IFT) might be responsible for the observed improvements in incremental oil recovery. To investigate this further, Hele-Shaw type experiments had been performed with the same fluid pairs, and significant alterations in the morphology of the fingers with ultrasonic waves were observed. Although the results seem encouraging, questions about the mechanism and effective parameters causing additional recovery still remain. To analyze the influence of parameters other than IFT and capillary forces, we conducted capillary imbibition experiments on cylindrical Berea sandstone core samples under ultrasonic radiation in this paper. Through this experimental scheme, we focused on (a) the effect of initial water saturation for different wettability rocks, (b) oil viscosity, and (c) matrix wettability. The cores were placed into imbibition cells where they contacted with aqueous phase. Every experiment was conducted with and without ultrasonic radiation for comparison. Different intensities of ultrasonic waves were tested as well. To profoundly investigate the acoustic interaction between rock and fluid, we further performed some visualization experiments. We used 2-D glass bead models to clarify the effects of ultrasonic waves on oil displacement process for different oil viscosities and matrix wettability through comparative analysis. The qualitative and quantitative observations and analyses are expected to shed light on the further investigations in the use of in-situ recovery of oil/heavy-oil as well as surface extraction. Introduction Primary production of petroleum by natural reservoir energy does not produce a large fraction of original oil in place. To increase the oil recovery from the reservoirs after conventional secondary recovery, enhanced oil recovery (EOR) techniques such as thermal, chemical and gas injection, should be implemented. In addition to those traditional EOR techniques, unconventional EOR methods have received a great deal of attention, especially after the recent increase in oil prices. Acoustic energy was considered as one of those unconventional EOR methods. Studies have been conducted to understand the effects of acoustic energy on oil recovery over the last four decades. Duhon and Campbell1 performed waterflood tests through cores under ultrasonic energy and showed that the ultrasonic energy improved the oil recovery and displacement efficiency in the cores. Beresnev and Johnson2 reported a critical analysis of the works done in this area by the early 1990's and provided a comprehensive review of the seismic and ultrasonic stimulation studies. They concluded that the elastic wave and seismic excitations to porous media affect permeability and production rate in most cases. Kuznetsov et al. 3 reviewed seismic techniques for enhanced oil recovery. They performed capillary pressure measurements with and without vibration and observed an increase in oil/water relative permeabilities and also oil recovery after elastic vibration. They concluded that this increase is due to fines removal by vibration. Roberts et al. 4 applied mechanical stresses to rock samples which were placed inside a core holder.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

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)0,000
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: Théorique ou conceptuel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,695
Score d'incertitude au seuil0,996

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
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 Opus0,028
Tête enseignante GPT0,286
Écart entre enseignants0,259 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeThéorique ou conceptuel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations4
Publié2007
Routes d'admission3
Résumé présentoui

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