Notice bibliographique
Résumé
After serving two terms for a total of 6 years, my time writing this column is coming to an end. This issue of JPT marks my last opportunity to share my thoughts, recap my observations, and make note of some final touch-ups to the research conducted over this 6-year period with regard to recent heavy oil practices. Here are some highlights to keep in our minds over the coming years. Despite all the recent negative and serious changes affecting the whole world and our industry, life goes on and we will increasingly be needing energy. One should recall that statistics predict oil will continue to be the main source of energy for the next 2 decades, with heavy oil constituting a great portion of that. That means that, while the oil industry is going through unprecedented and even unpredictable economic downturns, the status of heavy oil is still unquestionable. However, we have to face the fact that this energy should be tapped in a cheap, clean, and sustainable way. The best aspect of this effort is that heavy oil technologies have been established and tested over a long period of time, unlike other unconventional resources. Lowered steam consumption, down to zero if possible, has been under consideration to minimize the emission of greenhouse gases (GHGs) while simultaneously producing heavy oil. This green effort leads us to nonsteam techniques such as the use of water with chemicals (mainly polymer) and noncondensable gases and certain unconventional methods such as solvent injection and electromagnetic heating, the latter being unavoidable especially for extraheavy oil and bitumen. These areas have been critically considered by researchers and practitioners with a considerable number of applications existing at the field scale. At the same time, the oil industry must deal with mature steam projects in the near future. We have accumulated so much heat energy over the decades, yet a substantial amount of oil remains in these reservoirs. What can be done to reuse this energy? Can we recover different forms of energies using methods with no GHG emission? The current practices encountered in field-scale operations to improve the heavy oil recovery in mature steam applications use noncondensable gases; mainly, these techniques serve to pressurize steam-assisted gravity drainage wells, improve sweep and microscopic displacement by adding chemical additives to the steam (or hot water), and re-engineer well designs (flow control for efficient heating and sweep). My final example highlighting new practices is the increasing trend of offshore heavy oil practices. Of particular interest is polymer injection through vertical and horizontal wells and pilot steam applications, methods that are effective even if they occur at the pilot stage of the process. Recommended additional reading at OnePetro: www.onepetro.org. SPE 199947 - Enhanced Oil Recovery in Post-Cold Heavy Oil Production With Sand Heavy Oil Reservoirs of Alberta and Saskatchewan Part 2: Field Piloting of Cycling Solvent Injection by Gokhan Coskuner, Consultant, et al. SPE 199925 - Scalable Steam Additives for Enhancing In-Situ Bitumen Recovery in SAGD Process by Armin Hassanzadeh, Dow, et al. SPE 199927 - The Myth of Residual Oil Saturation in SAGD - Simulations Against Reality by Subodh Gupta, Cenovus Energy, 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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,008 | 0,005 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,006 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,298 | 0,216 |
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 source (Gemma direct ou Codex distillé), 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 ».