A Novel Method for Determining Brine-Induced Incremental Oil Recovery During Waterflooding
Notice bibliographique
Résumé
Abstract A modified analytical model for field application of improved waterflooding through brine concentration is presented. Based on several laboratory studies, many researchers suggested changing the brine concentration during waterflooding offered viable options for improved oil recovery. In this regard, particularly in cyclic waterflooding, several laboratory studies have confirmed the effectiveness of such approach. However, generally, these studies are limited to laboratory studies without much field application. This is based on the fact that most laboratory results did not present clearly defined approach for practical application. This paper analyses the laboratory results presented in the literature and proffers a concise approach for field application. To this end, based on the reinterpretation of the Civan and Knapp model, a modified oil recovery model is developed for field application during cyclic waterflooding. This model would help in monitoring waterflood performance based on the impact of brine injection on increased oil recovery during field application of cyclic waterflooding process. Introduction and Background The process of improving waterflooding performance through brine concentration has obvious practical benefits. Several laboratory studies have indicated increase in oil recovery with change in injected brine salinity. Crude oil properties, particularly the solvency of high molecularweight polar component and modest increase in temperature have been shown to have a major effect on crude oil, brine and rock interacti that selection or adjustment of an injection brine composition to advantageously alter wettability is a novel method for increasing oil recovery at potentially low cost. They demonstrated that laboratory waterflood recoveries of crude-oil/brine/rock (COBR) ensembles are strongly dependent on brine composition and on related COBR interactions. To this end, it was shown that rate and extent of final waterflood recoveries increased with decrease in brine concentration. Tang and Morrow (1999) reported that modification to brine chemistry have resulted not only in changes in the wetting state, but also increasing oil recovery during laboratory corefloods. Another study (4) suggested a significant increase in recovery with decrease in salinity and presented laboratory results on oil recovery from a selected field for potential application. In addition to improved oil recovery, COBR combinations were also found where there was little or no response to injected brine composition. Bagci et al. (2001) studied the effect of brine composition on oil recovery through injection of different composition of brine into packed one-dimensional unconsolidated limestone core using Garzan crude oil and distilled water. They reported only slight response for the limestone core sample used, which confirmed findings that laboratory evaluations are essential to identifying potential candidate reservoirs for application(4). Laboratory testing has identified three key conditions for the waterflooding process to be effective through controlled.
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 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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
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 ».