Notice bibliographique
Résumé
Abstract Offshore small projects (< $ 20 MM gross) often account for 15-20 percent of Oil and Gas Company's annual capital budget. Poor small project execution increases project costs and adversely affects production. Project management skills and habits developed in small project execution, good or bad, feed large project performance. Using small projects as a training ground for large projects improves small project efficiency and develops project professionals with skills to save hundreds of millions of dollars on a large capital projects program. The small project arena provides a dependable and renewable source of project management professionals at a time when age demographics threaten long term project performance. The following paper describes a small project improvement initiative implemented to improve small project performance. The initiative focused on:evaluating current performancedeveloping common processes and tools andestablishing a global small project network to share best practices and facilitate global interaction. Introduction The offshore oil and gas industry spends billions of dollars annually on small projects. Small projects are defined here as projects with a total installed cost less than $ 20 MM gross. Small projects are often completed on operating facilities that can potentially affect large revenue streams. The cost of small projects is disproportionate compared to their potentially large impact to production and revenue. Taking the time and effort to train small project personnel pays two significant dividends:Small project performance improvesFuture large project leaders are trained and developed Small Project Improvement Initiative There are strong business and economic drivers to improve small project performance. The main drivers include: cost, schedule, results, operability, and safety. The following five-step program was developed to improve small project performance:Develop Standard Format for EvaluationConduct On-site InterviewsEvaluate Small Project PerformanceDevelop Action Plan to ImproveShare Learnings and Best Practices Develop Standard Format for Evaluation. The first step was to develop a standard format to evaluate small project performance on a global basis. A 150-question questionnaire or audit was developed covering the entire project cycle from how the project idea was originated through start-up and project closeout. The questionnaire covers the following areas:Project submission and screening processDecision criteria and selection processProject team formationFront end loading and planningUse of value improving practicesProject execution plan developmentContracting and procurement strategiesProject control systemsProject outcomes and closeoutLessons learned The questionnaire allows consistent evaluation and comparison of small project performance across multiple regions and countries. Conduct On-Site Interviews. Key business units were asked to identify 4-5 small projects for detailed review and to provide summary data on 6-8 other small projects. Ideally, these projects were completed in the last 6-18 months and represented their normal small project workload. A corporate specialist traveled to the business unit location to complete the detailed reviews. Normally, each detailed interview lasts
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 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 | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,002 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».