Effect of Oil/Brine Ratio on Interfacial Tension in Surfactant Flooding
Notice bibliographique
Résumé
Abstract The difficulty of determining the effective interfacial tension (IFT) in porous media limits the modeling and prediction of surfactant flood performance. Surfactant dilution, adsorption and partitioning - occurring as the aqueous solution is injected into the reservoir and as it contacts the oil - will raise the effective in-situ IFT from the nominal value as measured traditionally. This change will have a corresponding influence on the oil displacement efficiency. A laboratory study of the interfacial tension behaviour of oil/surfactant-brine systems was conducted. The effective equilibrated oil-surfactant IFT - that is, the IFT closest to that actually produced by partitioning effects in the porous medium - was found to change greatly from the nominal values. When the ratio of oil to brine reached 40:60, the effective equilibrated IFT for the systems approached the original value of crude oil/brine without surfactant, apparently losing much of the advantage provided by a surfactant flood. However, the interfacial tensions between equilibrated oils and a fresh surfactant solution indicate that injecting additional chemicals would maintain the IFT at a reasonably low level. This was confirmed with visual micromodel floods: oil displacement efficiency was poor when equilibrated surfactant- brine solution was injected into a model containing equilibrated oil, and then greatly improved by injecting fresh surfactant solution. These findings are important for progress towards designing successful chemical floods. Introduction Enhanced oil recovery (EOR) by surfactant flooding has become more attractive in recent years. Low interfacial tension at low surfactant concentrations, and acceptable adsorption levels are considered to be important design parameters in optimising chemical systems for recovering trapped oil from petroleum reservoirs.[1,2] Ultra-low interfacial tensions of less than 10−3 mN/m have been reported with less than 0.1 wt% surfactant concentration measured by the traditional spinning drop method.[3] However, interfacial tension can be very difficult to accurately extrapolate from laboratory conditions to reservoir-like conditions. In a surfactant flood, the best surfactant performance depends on the characteristics of crude oil and brine, reservoir conditions, and several other stringent requirements, such as low retention, compatibility, and thermal and aqueous stability. Surfactant retention is due in part to adsorption on the rock surfaces, but other loss mechanisms Because there are limitations to studying the effect on interfacial tension of dilution, adsorption and partitioning of surfactant solution upon injection into the reservoir, it is not surprising that many studies use the IFT without considering adsorption and partitioning to predict surfactant flood performance. The traditional method of measuring ultra-low interfacial tensions (down to 10−3 mN/m) between two fluid phases is the spinning drop technique. In this test, a small drop of oil, of which the volume is less than 0.1 cm3, is injected inside a thin tube filled with a surfactant solution (approximate volume 1 cm3), and the tube is rotated at a high speed. The interfacial tension of the oil against water is able to be calculated from the angular speed of the tube and the diameter of the oil drop. The interfacial tension is obtained using a 0.1 oil-to-water ratio.
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Comment cette classification a été obtenuedéplier
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| 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 ».