Returning Pipelines to Service Following a Mw7.5 Earthquake: Papua New Guinea Experience
Notice bibliographique
Résumé
Abstract The Papua New Guinea Liquefied Natural Gas (PNG LNG) project is a joint venture with participation by ExxonMobil, Oil Search Limited (OSL), Kumul Petroleum, Santos, JX Nippon Oil and Gas Exploration and Mineral Resources Development Company, and began production in 2014. As described in a previous IPC paper, the project, operated by ExxonMobil PNG Limited (EMPNG) sustained a M7.5 earthquake and approximately 300 aftershocks in 2018, epicentered directly under key facilities. Around 150 km of high-pressure gas and condensate pipelines in the rugged PNG highlands were affected but did not lose containment or pressure. Immediately following the M7.5 event, EMPNG began efforts to assess and inspect the pipelines in order to ensure public safety, and, at the appropriate time, restore LNG production. The technical efforts took place along the pipeline Right of Way (ROW) in a remote jungle environment, which, following the earthquake, was also a disaster zone in which the few available resources were prioritized towards humanitarian relief. Due to resource constraints, the pipeline field inspection team typically numbered only two or three specialists. The inspection team drew heavily on analysis work, ongoing since project startup in 2014 and in progress when the earthquake occurred, that simulated the condition of the ROW and pipe stress state following earthquake events similar in magnitude to what actually occurred. The body of existing analysis work allowed the field team to compare aerially observed ROW ground movements to previously modeled cases, and rapidly infer pipe stress state without actually measuring pipe deformation on the ground. Due to resource constraints, that latter activity, if required before startup, would have significantly delayed project restart. The worldwide network of technical resources that had been assisting with ongoing simulations was quickly re-directed to analyzing actual observed ground deformations, efficiently supporting the small field team from outside the disaster zone. After restart, field inspection activities continued, observations were categorized, and an Earthquake Recovery (EQR) organization was initiated to execute ROW repairs. Just as the initial inspection work was aided by pre-earthquake analyses, EQR activities have been expedited by the extensive ROW maintenance program that had been ongoing prior to the earthquake. This paper and accompanying oral presentation present details of the inspection and recovery, and show that the extensive simulations, preparations and maintenance programs supported by EMPNG during project operations prior to the earthquake enabled a rapid and efficient response when the earthquake actually occurred, and thus provided enormous value to the business.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,003 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,002 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,007 | 0,001 |
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 ».