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Enregistrement W1971804921 · doi:10.4043/23930-ms

Real-Time Subsea Fiber-Optic Monitoring

2013· article· en· W1971804921 sur OpenAlex

Pourquoi ce travail est dans la base

Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.

affAu moins un auteur déclare une institution canadienne dans l'instantané OpenAlex épinglé.

Notice bibliographique

RevueOffshore Technology Conference · 2013
Typearticle
Langueen
DomaineEngineering
ThématiqueOffshore Engineering and Technologies
Établissements canadiensIntecsea (Canada)
Organismes subventionnairesNational Aeronautics and Space Administration
Mots-clésSubseaSoftware deploymentAgile software developmentSystems engineeringComputer scienceAdaptabilityOptical fiberEngineeringTelecommunicationsSoftware engineeringMarine engineering

Résumé

récupéré en direct d'OpenAlex

Abstract Commercially available fiber-optic sensors provide key information for well, reservoir and infrastructure surveillance. These fiber optic systems are now considered robust and see routine application in onshore and platform wells. Engineering, economic and project management challenges, however, delay the extension of these monitoring systems into the subsea environment. We illustrate the value of fiber optic monitoring, describe where fiber optic technology has significant potential in subsea development projects and identify the significant technology gaps which challenge subsea implementation of existing in-well fiber-optic sensing systems. We then define an approach to systematically address these gaps within the time frames of many current subsea projects, while preserving the necessary integrity of the subsea system and associated project delivery. The approach borrows from the Agile project management method and focuses on staged delivery of the fiber optic technology, maturing the technology by deploying select portions and then advancing in subsequent stages to the deployment of more-complex or more slowly evolving technologies, rather than attempting to fully mature the technology off-line prior to any deployment. It operates according to the following principles:–Deploy the more easily or readily adaptable portions of the technology first.–Ensure that each incremental deployment economically provides significant benefits, meeting business and technical surveillance targets.–Ensure that each deployment delivers technology maturation learnings that can be used to evaluate newly developed technology, with direct actionable feedback into further development plans.–Ensure that project plans contain sufficient adaptability and capacity for incorporating late-breaking or unforeseen technology advances, as well as contain contingencies to back off from portions of the technology deployment should best judgment dictate. In addition to accelerating technology advance, this approach assures further progress and technology acceptance along the way. We take inspiration from an historic application of such a method: NASA's journey to safely land men on the moon. In the staged development-deployment of the Gemini and Apollo programs, NASA consistently delivered tangible results with each launch, thus capturing and maintaining the support of the public, their primary stakeholders, throughout the program, as well as quickly making significant technical strides which ensured the accomplishment of their goal. Introduction Subsea wells represent expensive, high profile and high risk investments. It's no surprise that any suggestion to include new technology, such as fiber optic monitoring, in a subsea well is quite frequently rejected almost immediately despite value recognized by subsurface engineering and geoscience experts. Like all proponents of new technology, we share in the frustration that many people experience when greeted with this response. We acknwledge and appreciatethat the rationale for such strong resistance stems from the primary commitment of project managers, technical authorities, and subject matter experts to deliver the subsea project without delay, cost overrun or addition of unmanaged or unmanageable risk. We also observe that while the in-well technology advocates might seem to be at odds with installation project management, both groups actually have the same goal: to see the installation succeed in every respect while deliverying a well with high value.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict), Charge utile insuffisante (le modèle a refusé de juger)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,459
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,003

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.

Tête enseignante Opus0,009
Tête enseignante GPT0,201
Écart entre enseignants0,192 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle