Notice bibliographique
Résumé
Guest editorial Downturns offer you a choice: panic and shut down all but breathing or make use of the opportunities that desperation has handed you. What? In the good times of a price boom, we have no time, and usually no impetus, to alter the way we work and how we apply science and technology. This activity breeds inefficiency and waste, but the flow of easy profits is like an opioid drug, blinding forward-looking senses that should warn us that a price bust may be around the next corner with a demand reduction, manufacturing slowdown, renewable energy advance, or an upset in political alignments. The world currently needs the energy density and reliability of fossil fuels, but high cost and inefficient use will eventually kill this golden goose. Often, when the good times end, we pull back, believing all the while that the next boom and easy profits are just around the corner if we can just hold on. This is the recipe for bankruptcy. Every wave of a technology powerful enough to alter the economic landscape in any industry has a life span divided into three parts: an often rough beginning, a period of growth where the technology reaches a zenith of efficiency, and the inevitable plateau where we think it cannot be exceeded or replaced. All the while, a new technology is often quietly building that can upset our comfortable operations world. The history of the oil field is littered with the memories of companies that ignored developments by overreaching only for the profits made available by a boom and ignoring the future. While some would like to believe that wildcatters’ luck will drive the next upturn, the promises of unconventional formations will not be unlocked by chance. An attempt to express the problem might start with a small modification to the proverb, “There are none so deaf as those who will not listen.” Better Practices So, what is to be done in a downturn? Those on the science side of production companies can use the time to review each part of well performance with the objective of looking for better practices than the “best” practices that we have unconsciously limited ourselves to. Operators accepting this path often come out stronger after a slump. Gains in efficiency, generated from a better understanding of a company’s well-development practices, remain after oil prices rebound and supplier discounts disappear. The enablers are keeping and supporting a technological staff that is capable of learning prior to and while in survival mode, plus a management team that is wiser about how and where to invest before and after prices rebound. Most of all, it requires tearing down some barriers that “successful experience” has erected to the abandoning of methods with which we have become accustomed.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| 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 | 0,003 | 0,002 |
| 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 ».