Characterization of Reservoir Heterogeneity Based on Performance of Infill Wells in Waterfloods
Notice bibliographique
Résumé
Abstract Reservoir heterogeneities are known to influence success or failure of infill wells in waterfloods, but no satisfactory ways currently exist for their characterization, quantification, or prediction. In 1950, Dykstra and Parsons(1) presented empirical correlation for waterfloods in certain California reservoirs based on observed variations in permeability. In general, procedures for most reservoir engineering predictions could be greatly improved if heterogeneity could be characterized by one or more terms. However, it is painfully obvious that because of the multitude of reservoir descriptions encountered in any oil prone basin, a single parameter (or a small number of parameters) may not be adequate. This is because of different ways in which heterogeneity impacts the performance of vertical or horizontal infill wells placed to enhance production/ reserves in a variety of waterflood situations. It is postulated that reservoirs are divided into predominantly horizontal or vertical "compartments" due to spatial variations in reservoir attributes such as permeability, thickness, environment of deposition, and post-depositional changes. Oil contained in these compartments, though often not strictly isolated, is not easily contacted or displaced by the injected water. Alternately, flow within the reservoir might be predominantly through certain pathways, some of which might involve cross-flow between various regions or intervals. Horizontal wells do a better job of draining oil than vertical wells in certain situations and vice versa. This paper proposes a method for characterizing reservoir heterogeneity and illustrates its application via four case studies of infill wells in waterfloods in the Western Canadian Sedimentary Basin (WCSB). Comparative performance is presented for infill horizontal and vertical wells placed in these projects during the past 15 years. Introduction In waterflood recovery projects, recovery at any point in time is a product of displacement efficiency, conformance (vertical sweep efficiency), and areal sweep efficiency. Whereas conformance can be estimated using Dykstra-Parson's procedures(1), sweep efficiency largely depends on areal heterogeneity in different intervals, besides factors such as mobility ratio, injected fluid throughput, and flood pattern geometry(2). Effects of areal heterogeneity have largely been approximated by "fudge factors," in the absence of a quantitative methodology for estimating them. Here, we propose an alternate method of characterizing areal or lateral heterogeneity in waterflood projects, based on performance of infill vertical and/ or horizontal wells. Areal or lateral heterogeneity can be characterized using the following data (whenever available):Suitable geological analogs (outcrops or sub-crops as revealed in quarries or mines(3), or logs/cores);Results of pulse/interference tests between various injectors and producers;Inter-well tracer returns data for the specific waterflood project, provided sufficient amount of data are available for various injectors and producers(4); and,Performance of different production wells (vertical and horizontal). Infill vertical or horizontal wells are drilled to reduce interwell spacing and modifying flooding patterns in drive situations, thereby accelerating production, improving volumetric sweep, and recovering some of the otherwise unrecoverable oil(5–7) from individual target locations.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,003 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».