Notice bibliographique
Résumé
Technology Focus Enhanced oil recovery (EOR) targets the approximately two-thirds of oil remaining in reservoirs after conventional recovery methods have been exhausted. More than 350 EOR papers were published from October 2011 to September 2012 because two major EOR meetings were held in Tulsa and Oman and a few international meetings had EOR sections as a primary topic, such as the International Petroleum Technology Conference in Thailand and the SPE Heavy Oil Conference Canada in Calgary. I categorized these EOR papers into the topics of EOR screening methodologies, reservoir problem identification and evaluation technologies, chemical EOR methods for conventional oil, chemical methods for heavy oil, gasflooding, conformance control using in-situ and preformed particle gels and foams, thermal EOR methods, smart-water flooding, nanofluid for EOR, EOR for shale oil, and new EOR technologies. Five papers were published to provide methods to screen EOR technologies. More than 20 papers published were related to EOR by altering water salinity and compositions, such as low-salinity waterflooding, seawater flooding, and tuning water salinity and ionic content. More than 10 papers were published to address one recent interest: using chemical methods to enhance heavy-oil recovery. The development of high-molecular-weight polymer and new types of polymer such as associated polymer has made some chemical methods such as polymer flooding feasible for some heavy oils. However, these three types of papers were not featured this time, either because the category was featured in the last couple of years or because the papers are too long or too complex to be synopsized. But these topics, along with some others, such as gas-flooding for shale oil and nanoparticle EOR, are selected to form the list of papers suggested to be read. I have selected the following four topics for the EOR feature this time: experience of alkaline/surfactant/polymer flooding in China, polymer flooding pilot in the Middle East, a review of mobility and conformance control for CO2 EOR, and a new correlation to predict optimum surfactant structure. Recommended additional reading at OnePetro: www.onepetro.org. SPE 141283 Full Barrel Analysis: A Simulation Model Interrogation Tool To Assess Sweep Efficiencies and Identify Targets for Improved Oil Recovery by M.S. Beckman, ExxonMobil, et al. SPE 155546 PDO’s EOR Screening Methodology for Heavy-Oil Fractured Carbonate Fields—A Case Study by Georg Warrlich, Shell, et al. SPE 154218 Four-Phase Equilibrium Calculations of CO2/Hydrocarbon/Water Systems Using a Reduced Method by Saeedeh Mohebbinia, The University of Texas at Austin, et al. SPE 154675 Viscosifying Surfactant Technology for Chemical EOR: A Reservoir Case by G. Degré, Rhodia, et al. SPE/CSUG 148971 Sweep Efficiency Improvement by Alkaline Flooding for Pelican Lake Heavy Oil by Mingzhe Dong, University of Calgary, 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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,002 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 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 ».