Notice bibliographique
Résumé
Technology Focus Exploration and development of unconventional hydrocarbon reservoirs continue to grow at a pace that exceeds our understanding of the nature of these ultratight formations and how to sustain longer-term production from them. This is confounded further by the expansion of the industry into the broader and increasingly mysterious realms of liquid-rich and tight oil reservoirs beyond the relatively better- understood tight gas formations with their longer history of exploitation. With this greater breadth of activity, the unknowns, uncertainties, and challenges are increasing. Already, estimates of unconventional hydrocarbon reserves have varied greatly, and the financial and future-energy-outlook implications of such wide-ranging uncertainty are enormous. With the industry moving forward with exploration and development in the broader categories of unconventional resources globally, it is of paramount importance to assess and improve the different methods and tools for estimating reserves, to establish their accuracy and credibility. And this must be accomplished in conjunction with increasing our fundamental understanding of unconventional formations at the nanoscale. This is a considerable challenge but one with significantly greater emphasis and efforts across the academic and industry research-and- development landscape. In conjunction, there is increasing attention on addressing the immediate issue of rapid well-production declines from the often prolific, but short-lived, initial production rates. With that in mind, methods including the use of enhanced recovery fluids and well-pattern schemes, and reactive fluids such as acids in drilling, completion, and stimulation processes, are beginning to receive genuine consideration. The importance cannot be overstated because alternatives to hydraulic fracturing may become a necessity, at least in certain areas of the world. Through special core analysis and flow studies, visualization techniques, and simulation, acid stimulation in carbonate-rich tight oil formations (as one example) may find greater and more-creative application beyond the acid spearheads ahead of hydraulic-fracturing stages. Other strategies for enhancing production and extending production performance, such as through imbibition and post-stimulation shut-in strategies, especially in liquid-rich and tight oil developments, are receiving more attention and are providing new and important learnings, too. The papers featured this month provide new insights and examples in some of these key, and exciting, areas of current focus in unconventional, tight oil and gas, and shale developments. The reader is encouraged to delve into these topics and continue to monitor progress, which is moving at a fast pace. JPT Recommended additional reading at OnePetro: www.onepetro.org. SPE 163814 Prediction of SRV and Optimization of Fracturing in Tight Gas and Shale Using a Fully Elastoplastic Coupled Geomechanical Model by M. Nassir, University of Calgary, et al. SPE 167092 Evaluating Treatment Methods for Enhancing Microfracture Conductivity in Tight Formations by Philip D. Nguyen, Halliburton, et al. SPE 167713 Water Loss vs. Soaking Time: Spontaneous Imbibition in Tight Rocks by Q. Lan, University of Alberta, et al.
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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| 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 | 0,001 | 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 ».