Notice bibliographique
Résumé
Technology Focus A seminal event last year was the Climate Change Conference in Paris, where participating countries agreed to reduce their carbon output “as soon as possible” and to do their best to keep global warming “to well below 2°C.” History will be the judge of whether 2015 turns out to be a turning point in the journey to reducing global warming. There is still a long way to go to turn good intention into substantive action if the world is to transition to a low-carbon economy and ultimately to one of net zero carbon emissions. This challenge is all the tougher given increasing demand for energy, with the International Energy Agency expecting growth by one-third between 2013 and 2040. In the US, there has been a gradual shift in the balance of enhanced-oil-recovery (EOR) production between thermal and gas-injection projects. Since 2006, production from gas injection has outstripped that from thermal, and it is continuing to grow. Worldwide, gas-injection EOR is established as a successful, robust, commercial technology deployed in a wide range of operating conditions from onshore to shallow offshore and, more recently, deep water. A key differentiator of gas injection, compared with other EOR techniques targeting light oils, is the ability to overcome some of the variability in reservoir geology by recycling back-produced injectant. The deployment of gas-injection EOR is limited by the availability of gas; where there is access to a gas market, the use of hydrocarbon gas is generally not attractive, and carbon dioxide (CO2) is not widely available at acceptable prices. Carbon capture and storage (CCS) is a mechanism that can facilitate the transition to a low-carbon economy, and so something of a virtuous circle might exist. The use of CO2 captured for greenhouse-gas-management reasons can enable more-widespread gasinjection EOR. CO2 EOR can provide secure CO2 storage and additional revenues, accelerating the implementation of carbon capture and ultimately the building of a commercial CCS industry that can help realize the aspiration of net zero carbon emission fossil fuels. Even though conditions in the industry remain very tough at present, EOR is expected to be increasingly important in the future, with the possibility of significant further uptake of gas-injection EOR linked to the climate-change agenda. As ever, SPE continues to have a key role in disseminating best practices and project learnings. JPT Recommended additional reading at OnePetro: www.onepetro.org. SPE 169513 Case Study: Steam-Injection Step-Rate Test Run in the Shallow Low- Permeability Diatomite Formation, Orcutt Oil Field, Careaga Lease, Santa Barbara County, California by Ramon Elias, Santa Maria Energy, et al. SPE 174700 On the Road to 60% Oil Recovery by Implementing Miscible Hydrocarbon WAG in a North African Field by I. Maffeis, Eni, et al. SPE 177697 Use of an Integrated Approach To Optimize a Congested Brownfield Facilities Development by C. Roberts, S2V Consulting, et al. SPE 174656 Nano Spherical Polymer Pilot in a Mature 18 °API Sandstone Reservoir Waterflood in Alberta, Canada, by Randy Irvine, Harvest Operations, 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 | 0,001 | 0,001 |
| 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 ».