Enhanced Sweep Efficiency by Use of Smart Water in Tight Oil Reservoirs
Notice bibliographique
Résumé
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 185032, “Enhance Microscopic Sweep Efficiency by Use of Smart Water in Tight and Very Tight Oil Reservoirs,” by T. Kadeethum, H.K. Sarma, and B.B. Maini, University of Calgary, prepared for the 2017 SPE Canada Unconventional Resources Conference, Calgary, 15–16 February. The paper has not been peer reviewed. In the literature, improvement of oil recovery in smart-water-injection schemes has been shown to be mediated by wettability alteration. This process reduces residual oil saturation, which, in turn, affects microscopic sweep efficiency and leads to subsequent enhancement of overall waterflood performance. Currently, there are few studies on smart waterflooding in tight and very tight oil reservoirs. This work examines smart-waterflood opportunities in such reservoirs. Introduction Residual-oil-saturation reduction improves microscopic sweep efficiency and, therefore, overall waterflood performance. Furthermore, decreasing endpoint water relative permeability diminishes mobility of the water phase such that water production is similarly reduced. Though these circumstances improve oil-production behavior, the primary parameters that lead to this improvement are still not well-understood. Among the statistically significant parameters that can influence smart-waterflood performance is clay content. One plausible explanation for the strong correlation between clay content and oil recovery is the positive correlation between cation-exchange capacity (CEC) and clay content. With higher CEC values, more rock surface may be charged. This results in either the expansion or compression of the double layer, which also induces a wettability alteration. Although tight oil reservoirs have limited flow capability, high CEC values in these reservoirs facilitate the wettability-alteration process. The objectives of the complete paper are to ex-amine the smart-waterflood potential in tight and very tight oil reservoirs, and to identify the CEC effect on smart-water-injection performance. The complete paper provides a discussion of the methodology (procedures and strategies) of the study. Discussion The literature contains evidence of smart-waterflood performance, with some works demonstrating that smart water improves oil recovery by reducing residual oil saturation. Furthermore, it decreases the endpoint water relative permeability. Smart water also improves microscopic sweep efficiency, leading to overall waterflooding efficiency. There is a distinct effect of porosity mean and porosity variance on CEC; there is furthermore a profound effect of CEC upon smart-water performance. Simulation properties relevant to the CEC effect are shown in Table 3 of the complete paper. There are two main types of fluid composition: in-situ fluid composition, which is the initial fluid in the reservoir at timestep zero, and the injected-fluid composition, which is the fluid that is forced into the reservoir at timestep greater than zero. Three homogeneous-reservoir cases with varying CEC values are considered.
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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 | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».