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Enregistrement W2395660182 · doi:10.2118/180745-ms

Technical Benchmarking: A Critical Step in Reducing Costs in a Low Price Environment

2016· article· en· W2395660182 sur OpenAlexaboutno aff
George C. Brindle, Chantel M. Moran, Paul Goolcharan, Jason Perry

Notice bibliographique

RevueSPE Canada Heavy Oil Technical Conference · 2016
Typearticle
Langueen
DomaineEngineering
ThématiqueOil and Gas Production Techniques
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésBenchmarkingScope (computer science)Consistency (knowledge bases)Computer scienceSizingMetric (unit)Identification (biology)Key (lock)Control (management)Measure (data warehouse)Engineering design processRisk analysis (engineering)Construction engineeringSystems engineeringIndustrial engineeringManufacturing engineeringReliability engineeringEngineeringOperations managementBusinessMechanical engineeringDatabaseMarketing

Résumé

récupéré en direct d'OpenAlex

Abstract Objectives/Scope Expertise has brought consistency and cost control to drilling and completing steam assisted gravity drainage (SAGD) well pairs. Data shows that the well pad facilities have not achieved the same degree of consistency in scope. Broad differences in specifications, physical design and execution have existed and continue to exist. We intend to show the benefits of technical benchmarking for scope and specification control in the design and execution of SAGD well pads. Methods, Procedures, Process Our approach is to measure constructed and operating well pad designs with 511 category measures which rollup into 42 key design metric categories. We believe that the operating well pads provide evidence of functionality and show good engineering practice. Our interest is in showing the minimum of each kind of equipment, pipe and instrument building block that is actually required to provide a functioning site. Results, Observations, Conclusions Our data comes to us under confidential contract from many of the SAGD producing companies and engineering firms, either for estimating or for comparative analysis of designs with industry normal prior to sanction. We reviewed well pad design elements, physical measurements, sizes and counts and compared them across both industry and design to reveal opportunities for optimization. Our repeated studies of the operational and regulatory compliant well pad scope show that some projects used many times more items than other projects. Large differences in well pad dimensions were often combined with large differences in equipment sizing. Large differences in bulk materials were also observed. Through the identification of design limitations, a number of project teams incorporated significant reductions in on-pad dimensions, pipe and equipment sizes and reductions in counts of instrumentation hardware. This process leads to simplification of the design, allowing for a reduction in capital expenditure (CapEx) and operating costs (OpEx) while ensuring it is still safe and easy to operate. In a low oil-price environment, it is essential to produce well pads comprised of design elements and execution that have measurable success in all areas. Project managers and executives alike need to know that the design teams are utilizing the minimum practical combination of sizing, redundancies and tonnages of materials in execution. It is our belief that good engineering will show what to include but great engineering shows what can be left out. We propose that a minimum, safe, functional scope when combined with good contract strategy will bring the thermal producers supplemental well pad costs that will meet capital requirements in our new low Western Canadian Select crude oil price environment. NOTE: At no point will the contracting entities or producers be identified in this paper. Novel/Additive Information We have seen no other recent work that uses this approach to control scope or specification. We believe the technique is universally applicable to any unconventional development such as shale gas, SAGD or similar.

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 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)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Autre devis · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,865
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
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,011
Tête enseignante GPT0,222
Écart entre enseignants0,212 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeAutre devis
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2016
Routes d'admission1
Résumé présentoui

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