Notice bibliographique
Résumé
Technology Focus Benjamin Franklin once said, “When you are finished changing, you’re finished.” Our industry must continue to improve and evolve to face the challenges of economic and commercial viability, greater transparency, environmental responsibility, and social acceptance. The papers in this month’s Reserves Management feature explore new and novel ideas to maintain social and environmental relevance, maximize value from unconventional projects, and ensure that exploration and appraisal activity is designed to optimize decision-making in resource project management.• Paper SPE 195298 describes a methodical way to show resource project movement through the recently updated (2018) Petroleum Resources Management System (PRMS) and Canadian Oil and Gas Engineering Handbook (COGEH). Not only does this facilitate a consistent approach for entities to classify their resources, but also provides guidance about how to subclassify resources through a technical and commercial analysis. Subclassification on the basis of project maturity is now recommended by the PRMS 2018 to provide greater transparency of the chance of commerciality, particularly for contingent resources. Moreover, it is important to be able to describe the associated chance of commerciality and defend the reasonableness of development assumptions and resource assignment; otherwise, projects should be considered Unrecoverable. Each entity will need to develop the process to their own specific needs. Paper SPE 191455 is an excellent case study using data analysis to evaluate how the industry has evolved through continuous improvement over the last 12 years. The study was conducted using multivariate analysis tools to try and look objectively at the data, and with 12,000 wells to draw from, there was a significant amount of data to analyze. It is a lesson in what is required in determining the best completion technique for the right reservoir; one needs to drill a great many wells. While the study is related to improvements of projects already in the Reserves class, it illustrates the principles of the Technology Under Development process as it applies to Contingent•resources. Paper OTC 28312 is an excellent Australian example of the oil and gas industry collaborating with scientific research institutions to collect data that can be used not only to assess the integrity of subsea infrastructure to guide decommissioning strategies, but also to contribute to a broader understanding of our oceans and marine ecology. In an increasingly complex and uncertain global environment, it makes sense for oil and gas entities to look at ways of collaborating with scientific institutions and other industries for mutual benefit. This should facilitate greater community acceptance and can demonstrate that industry is undertaking responsible scientific, social, and environmental management. A win-win! Recommended additional reading at OnePetro: www.onepetro.org. SPE 193717 Economic Benefits of Implementing Alternative Energy:• A Heavy Oil Fields Case Study by Mohammad Al-Yatama, Kuwait Oil Company, et al. IPTC 19506 Total Well Management: Maximizing Well Life Cycle Value—A Regulator Perspective by Ryan Guillory, Petronas, 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 | 0,001 |
| 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 | 0,000 | 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 ».