Notice bibliographique
Résumé
Abstract Accurate relative permeability data are essential for predicting the performance of two-phase flow through porous media. Many factors, such as the rock and fluid properties, may affect the measurement of relative permeability. However, the saturation levels of the fluids flowing through a porous medium have the largest impact on the shape of the relative permeability curves. Because relative permeability is a strong function of saturation, an accurate measurement of saturation levels in various types of two-phase flow experiments is required. In addition to many non-invasive methods, weighing and volumetric methods are frequently used to estimate the average saturation during steady-state experiments. However, for unsteady-state flow experiments, material balance methods to determine the saturation levels are relatively difficult to use. This article presents a relatively new non-invasive saturation measurement method and the equipment used to obtain dynamic saturation profiles as a function of time and distance along the core-holder. The new saturation measurement system has been found to be equally good for steady-state and unsteady-state experiments. Typical dynamic saturation profiles, the equipment calibration method, and a set of typical relative permeability curves for a co-current flow experiment are presented. Based on the presented experimental results, it has been found that the new saturation measurement method and the equipment is reliable and can reproduce stable dynamic saturation profiles with a minimum level of uncertainty. Introduction Underlying the extension of single-phase flow theory for the simultaneous flow of two or more fluids are the concepts of effective and relative permeability. The effective permeability is a relative measure of the conductance of a porous medium for one fluid phase when the medium is saturated with more than one fluid(1). The relative permeability is defined as the ratio of the effective permeability of a phase to a base permeability [e.g., absolute permeability to air or water, Craig(2)]. Relative permeability data are essential for almost all two-phase flow studies related to reservoirs. The data are used in making estimations and predictions of the productivity, injectivity, and ultimate recovery from reservoirs for evaluation and future development plans. The relative permeability data can also be used to diagnose the formation damage expected under various operational conditions. Therefore, unquestionably, these data are one of the most important data sets required in reservoir engineering studies. Among several methods for obtaining relative permeability curves, laboratory techniques are considered to be the most reliable. These methods for relative permeability measurement are further classified into steady-state and unsteady-state methods. Aleman et al.(3) have concluded that the difference in the relative permeabilities obtained by the two approaches is negligible, provided that the magnitude of the local (not macroscopic) capillary number is larger than a limiting value. Numerous studies have been conducted to investigate the effect of important parameters during the measurement of relative permeability data. In addition to saturation, some of the other important parameters affecting relative permeability are wettability, IFT, flow regime, overburden pressure and temperature. Leverett and Lewis(4), Sarem(5), Saraf and Fatt(6), and Owens and Archer(7) have shown that for strongly water-wet unconsolidated sands the permeability to a wetting phase is dependent solely upon its own saturation.
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 | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 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 ».