Metocean Decision Making Lessons-Learned during an Oil & Gas Construction Project Conducted in a Harsh Coastal Environment
Notice bibliographique
Résumé
Abstract The Hebron Platform was constructed from 2012 to 2017 in the harsh environment of coastal Newfoundland and Labrador. The construction site experienced winds and seas that approached expected values for a 100-year return period event, unusual non-tidal water levels during topsides / GBS mating, and historically extreme sea ice conditions that delayed tow-to-field operations. Topsides marine operations required data collection and forecasting system enhancements more than 2 years in advance due to the sensitivity of the operations, and the complex topography and climate of the site. Installation offshore was limited by winds, seas and long period swells that could reach the site from remote areas of the Atlantic. A summary of metocean support for the Hebron Platform is presented with lessons learned and comparisons made with the Hibernia Construction Project executed 20 years earlier in the same location. Several technologies were applied to the Hebron Project that were not available during the Hibernia Project. Emerging technologies combined with in-situ measurements of atmospheric and oceanic conditions were used to provide operational metocean support for the Hebron Project. Examples of effective processes are described that could apply to similar harsh environments, complex terrains or northern coastal construction projects. There were also technologies attempted which were deemed unfeasible. Complex metocean decision making for an environmentally sensitive oil and gas construction project is described within a quantitative risk assessment framework. Embedded experienced metocean personnel used advanced information behind the scenes to improve forecast accuracy and to provide guidance on the timing and likelihood of threshold-exceedance events. It was demonstrated that an effective metocean decision making process was highly dependent on forecast magnitude and timing accuracy at various forecast horizons. It was found that specific operational parameters and governing, operational weather windows for the Hebron Project were achieved with minimal waiting on weather due to a ‘go/no-go’ decision making process which was based on confidence in the forecast accuracy, and a risk assessment system that embedded metocean specialists with the relevant event-likelihood information. Operational delays due to unreliable forecasting would have led to significant delays, personnel and equipment downtime, and cost over-runs for the Hebron Project. Weather forecasting in support of the Hebron Project demonstrated that metocean analytic and predictive science has improved sufficiently over the past 20 years to effectively support oil and gas exploration and development operations that have moved into harsher environments.
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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 | 0,001 | 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 | 0,001 | 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 ».