Notice bibliographique
Résumé
Abstract Precise predictions and solutions for tomorrow's needs are the key elements to build a growing, sustainable Refining business. This requires a mixture of vision, strategic risk taking business model and investment in new technology. Refining trends forecast for the next 15 years are useful for predicting its possible landscape by 2030, where in a larger context the main challenge for the industry would be to meet twice the energy levels from today with half the CO2 emissions. Increasing and diversification of world's energy supplies to support the population of more than 8 billion then would be a mammoth task, given that the triangle of energy, food and water will be crucial. Three fundamental factors that will influence and shape this setting are: 1)Global oil products demand growth at 1.1% - 1.4% annually up to 2030 to almost 115 million barrels per day (BPD), with marginal influence of crude oil prices;2)New legislation targeting reduction of greenhouse gas (GHG) / emissions will be strictly enforced3)Cleaner-burning and improved quality fuels will be essential, maximum in the transport sector which accounts 2/3rd of total demand and growth Well-to-wheels GHG emissions would drive unconventional fuels programmes; and countries with insufficient oil resources would attempt to secure supply and reduce dependence by including Gas-derived fuels, besides supplementing with CTL, GTL and BTL into supply chain. In several cases, effect of above three key factors would be multiple and cross-linked. While energy and climate change legislation would impact future growth of middle distillates – the largest group both in terms of refined products (> 30%) and consumption growth (1.6%-1.8%), advances in Refining technology would be influential from supply side, whereas new engine technology and optimized transportation logistics would provide efficiency gains from demand side. During the next 15 years in the field of clean fuels, tremendous improvements in technologies would include hydrotreating and dearomatization, hydrocracking, fluid catalytic and resid cracking, reforming, and alkylation. In the near term, besides new Refining capacity additions, increased NGL supply associated with Middle East gas production and newly commissioned GTL plants will add to the product supplies. Expected robust demand growth in Asia Pacific and Middle East may be outpaced by the supplies, with a structural change after large Middle East firmed up strategic Refinery projects and heavy-oil upgrading projects in Canada, come onstream during 2015-2018. Both gasification and natural gas steam reforming will also grow rapidly to furnish the booming demand for additional H2 to meet the fuel-quality specifications for the future. The process design and operational control would be squeezed as a result and it is invariably the last fraction which would be the most difficult to remove! Refineries will have to bear the rising cost of manpower, software and maintenance, furthermore, tighter regulatory and HSE scrutiny are expected to exert additional pressures on the refiners. Refining and integrated Petrochemicals business forms the backbone of global economic system and meeting the increasing demand with inevitable steady and sustainable profitability remains a major responsibility. Therefore, innovation, operational excellence and implementation of robust strategies are essential for its sustenance and growth. The paper discusses the futuristic and economic unlocking of value by application of technological advancements and best practices in maximization of middle distillate by upgrading bottom of the barrel besides the impact of stringent product specifications on transportation fuels and fuel oil market, competition from natural gas and renewables and the regional infrastructure additions.
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 | 0,000 | 0,000 |
| 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 ».