Pourquoi ce travail est dans la base
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Notice bibliographique
Résumé
Technology Focus Of the top 10 largest discoveries in 2013, half are natural-gas discoveries and all are in offshore environments, primarily in Africa (Mozambique, Angola, and Tanzania), Far East Asia (Malaysia), and transcontinental countries (Egypt), with estimated resources of more than 4,000 million BOE. The rest of the discoveries are mainly light oil, very likely containing associated gas. To bring gas from remote locations to the markets will remain an imposing task, with unavoidable challenges in terms of exploration, production, processing, and transportation, especially now when both oil and gas prices are low. The leading countries in natural-gas production in 2013, the same as in 2012, were the US (687.6 billion m3, 20.6% of total world gas production), the Russian Federation (604.8 billion m3, 17.9%), and Iran (166.6 billion m3, 4.9%). On the consumption side, the natural-gas consumption growth rate has been steady in the past decade (2003–13) with an average growth rate of 2.6%, while 2010 had a negative growth rate of -2.1%; 2011 had the highest rate at 7.6%; and, in 2013, the growth rate was 1.4%. The US is, by far, the leading country in natural-gas consumption (737.2 billion m3, 22.2% of total world gas consumption), followed by the Russian Federation (413.5 billion m3, 12.3%), China including Hong Kong SAR (164.2 billion m3, 4.95%), and Iran (162.2 billion m3, 4.8%). China had the highest gas-consumption incremental of 15.3 billion m3 from 2012 to 2013, followed by the US (14.2 billion m3), Brazil (5.9 billion m3), and Germany (5.3 billion m3). On the transportation side, the numbers are similar: Approximately 1035.9 billion m3 of gas was transported in 2013, which was a 1.5% increase over 2012. Of that, approximately 68.6% was transported by pipelines and the rest was by liquefied natural gas (LNG) in 2013 vs. 68.0% for pipelines and 31.8% for LNG in 2012. The Russian Federation, Qatar, Norway, and Canada are the top four countries in exporting gas (225.5, 125.5, 106.2, and 78.9 billion m3, respectively) and accounted for more than 51% of total world gas movement. The Russian Federation remains the dominant player in pipeline transportation, moving approximately 30% of total global pipeline gas, while Qatar moved more than 32% of the total LNG worldwide. With so many new gas discoveries in offshore locations, transporting gas across water will remain one of the major challenges in gas monetization, and pipelines and LNG (including floating LNG) will remain the primary means of natural-gas transportation. More information will be presented at the SPE Workshop on Gas Field Developments— Pushing the Limits, which is scheduled for 8–11 March 2015 in Kota Kinabalu, Malaysia. JPT Recommended additional reading at OnePetro: www.onepetro.org. OTC 24674 Accurate Phase- Equilibria Predictions for Hydrates of Multicomponent Natural Gases by Prathyusha Mekala, Indian Institute of Technology, Madras, et al. OTC 25413 Qualification of a Cryogenic Floating Flexible Hose Enabling Safe and Reliable Offshore LNG Transfer for Tandem FLNG Offloading Systems by Vincent Lagarrigue, Trelleborg, et al. SPE 172079 Improving Gas/Condensate Recovery Factor and Addressing the Flow- Assurance Issue With an Innovative and Highly Accurate Fluid Sensor for Wet-Gas Business by B. Pinguet, Schlumberger
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.
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 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 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 découle