Pigging Previously Unpiggable Pipelines
Notice bibliographique
Résumé
Abstract The efficient and safe transportation of fluids through pipelines has been a cornerstone of modern infrastructure for decades. However, pipeline operators often face challenges when it comes to inspection, maintenance, and cleaning. These challenges are often addressed through pigging programs; however, a large portion of existing pipelines are considered "unpiggable." This is primarily due to pipeline size, complex geometry, or unique operational conditions. In recent years, the need to maintain and ensure the integrity of all types of pipelines, including those previously considered unpiggable, has grown significantly. The paper begins by defining what makes a pipeline "unpiggable" and delves into the common reasons for this classification. It will then explore the challenges associated with pigging previously unpiggable pipelines and some innovative solutions for pigging this type of infrastructure. One of the primary challenges in pigging unpiggable pipelines is the development of suitable pigs and technologies. Traditional pigs are often designed for pipelines with standard dimensions and features. The paper discusses how the industry has responded to this challenge through the development of specialized pigs tailored to the unique requirements of unpiggable pipelines. This includes a summary of the development of various cleaning and product recovery solutions, such as foam pigs and swabbing devices, designed to address the unique challenges posed by unpiggable pipelines. Additionally, the paper includes information on the use of small, single-body inspection tools that the industry has developed to allow for in-line inspection in these applications. Another significant challenge surrounds the changes required to update and modify existing pipelines to include the necessary pig launching and receiving infrastructure and remove or update features that hamper successful pig runs. The paper highlights the challenges associated with data collection on existing historical pipelines and some of the changes required to ensure successful pigging operations. Specifically, the paper outlines how the use of pipeline Pigging Valves and Multi-Pig Launchers can be used as an innovative alternative to traditional barrel-style pig launchers or receivers in previously unpiggable applications. In addition to technological advancements, the paper delves into the operational, regulatory, and environmental considerations faced during pigging activities in unpiggable pipelines. These challenges include access to the pipeline, transportation and deployment of pigging equipment, high-frequency pigging, emissions regulations, and safety considerations. In conclusion, pigging previously unpiggable pipelines presents a compelling challenge that demands innovative solutions. This paper provides an overview of the challenges faced and the technological advancements, operational strategies, regulatory compliance, and economic factors that must be considered. By understanding these complexities, pipeline operators and industry professionals can make informed decisions and effectively address the unique requirements of pigging previously unpiggable pipelines, ensuring the continued safe and efficient transportation of vital fluids in our modern infrastructure.
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 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,002 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,006 | 0,002 |
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 ».