Notice bibliographique
Résumé
Abstract Oil and gas companies face great pressure to sustain and/or maximize the recovery of resources, in an environment of global competition, under mounting operating expenses, and with stricter accountability to the environment and public safety. Companies must be vigilant to adopt technological innovations that will deliver a stepwise change to the way they conduct their business in order to deliver capital and operational improvements that produce a measurable financial impact. The Canadian oil and gas industry has been amongst the leaders in technological innovation and been equally quick to adopt innovations necessary to exploit and maximize reserves. This paper discusses how new data communications technology and hardware can be linked with traditional business software solutions to deliver information specific to departments and individuals in an organization. The paper focuses on new technologies for data acquisition, well site monitoring, and data analysis, where information is transfered from a remote location to the desktop. Modelling concepts will be reviewed that show how secure and dependable data communications can disseminate information to personnel within an organization to make informed decisions and reduce response time. Data information can be used to "seed" other traditional software applications that will permit more in-depth analysis. Using the Internet to disseminate data within an organization allows collaboration between individuals and departments, creating opportunities for the integration of engineering services with other departments. Introduction Data communications is one of the most rapidly growing and evolving technologies today. Words such as "satellite," "cellular," and "wireless communications," which were unknown terminology in "oil field" vocabulary only a few years ago, are now commonplace. New data communications technology allows well site information to be communicated from almost any location in the world, cost effectively, reliably, securely, and almost instantly. The Internet is becoming the communication mechanism of choice for data and technology delivery, and for the dissemination of data and information within organizations. At Oracle's OpenWorld 2000(1) Conference, Vice President of Product Marketing and Services, Mark Jarvis, told the 35,000 attendees that in five years' time, no one will buy software as a product-it will exist only as a service over the Internet. Director of E&P Services for EDS Energy Industries Group, Dick Standaert(2), wrote that in two or three years, more than 50% of all oil and gas technical services and scientific information services will be Web-based. He believes that by 2005, the Internet will be the accepted norm for all such services. Reference to such comments should not be dismissed as merely an attempt to elicit some form of "shock" value. The movement described is already underway. The imminent changes alluded to are forcing oil and gas producing companies to reconsider the relationship between their equipment suppliers, consultants, partners, and their employees. Providers of consulting services, field services, hardware equipment vendors, and information providers are questioning how they will remain competitive as the delivery and marketing of their services evolve. Oil and gas production companies are questioning whether they have prepared themselves and their employees to take full advantage of technological and service innovations.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,002 | 0,003 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,009 | 0,007 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,003 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,275 | 0,224 |
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 ».