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Enregistrement W2083558109 · doi:10.2118/04-02-01

Structure/Performance Relationships for Surfactant and Polymer Stabilized Foams in Porous Media

2004· article· en· W2083558109 sur OpenAlexafffund
Susan M. Kutay, Laurier L. Schramm

Notice bibliographique

RevueJournal of Canadian Petroleum Technology · 2004
Typearticle
Langueen
DomaineEngineering
ThématiqueEnhanced Oil Recovery Techniques
Établissements canadiensSaskatchewan Research Council (Canada)University of Calgary
Organismes subventionnairesNatural Resources CanadaNatural Sciences and Engineering Research Council of CanadaChemical Institute of Canada
Mots-clésMaterials sciencePorous mediumViscosityPorosityEnhanced oil recoveryPulmonary surfactantPolymerLaminar flowComposite materialRheologyPermeability (electromagnetism)Chemical engineeringChemistryThermodynamics

Résumé

récupéré en direct d'OpenAlex

Abstract The addition of polymer has the potential to enhance both the viscosity and the stability of surfactant-stabilized foams. However, the degree to which the bulk properties of polymer-thickened foams are retained or enhanced in porous rock is not well understood and is difficult to predict. We have compared the viscosities, at equivalent shear rates, of two different types of polymer-thickened foams in laminar pipeline (bulk) flow vs. the same foams flowing in consolidated sandstone rock. For one kind of foam, the apparent viscosity in the rock is very similar to that in pipeline flow. However, for another kind of foam, the apparent viscosity in the rock is an order of magnitude greater than that in pipeline flow. Low-energy scanning electron microscopy was used to examine the pore-scale morphology of the two foams in the rock. It was found that the morphologies of the two foams explain at least a large part of the observed differences in foam flow properties between bulk (pipeline) flow and constrained (porous medium) flow. This work is important to the specifications and formulation of the most effective surfactants for varying applications including mobility control, blocking, and diverting. Introduction Aqueous foams are used in a variety of the petroleum industry's enhanced oil recovery flooding techniques(1). For example, surfactant stabilized foams have been used as mobility control agents in gas-flooding(2–4). The foam, which has an apparent viscosity greater than the gas, lowers the gas mobility in the swept and/or higher permeability regions of the formation. Thus, the foam will divert some of the gas into other parts of the reservoir formation that were previously unswept, or poorly swept, to recover additional oil. Significant foam stability is a prerequisite for the successful application of foam flooding. There are also many other applications of foams in the petroleum industry, all requiring controlled stability(5–8). Foams have also been used as blocking agents because of their selective ability to reduce the gas permeability(9). Foam that has been developed for a blocking application must meet different requirements than foam that has been developed for sweep efficiency applications. A blocking foam must possess the ability to completely fill a selected volume in all locations where the gas could travel through, and to act as a barrier to flow. The gas blocking foam must stay in place and possess long-term stability, providing the largest possible gas mobility reduction for the longest periods. For the formulation of either kind of foam, one of the challenges that must be met is the proper selection of foam-forming surfactants. The foaming capability of a surfactant relates to both foam formation and foam persistence, which are influenced by many bulk and interfacial properties(10). Unfortunately, it is generally found that the performance of foams in porous media is not easily predicted based on these physical properties(11), although they can be exploited to increase foamability and foam persistence. Harsh chemical environments are sometimes present in oil reservoirs and several reviews have been published identifying desirable foam-forming characteristics for harsh and less demanding environments(1, 12).

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: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,381
Score d'incertitude au seuil0,841

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0020,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
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 Opus0,009
Tête enseignante GPT0,191
Écart entre enseignants0,183 · 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'étudeExpérimental (laboratoire)
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

Citations43
Publié2004
Routes d'admission2
Résumé présentoui

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