MétaCan
Menu
Retour à la cohorte
Enregistrement W1989053043 · doi:10.4043/17685-ms

Casing Drilling Rig Selection Process For The Stratton Field

2005· article· en· W1989053043 sur OpenAlexaff
D. Bickford, M. Mabile

Notice bibliographique

RevueOffshore Technology Conference · 2005
Typearticle
Langueen
DomaineEngineering
ThématiqueDrilling and Well Engineering
Établissements canadiensApache (Canada)
Organismes subventionnairesnon disponible
Mots-clésCasingDrillingProcess (computing)Selection (genetic algorithm)Computer sciencePetroleum engineeringField (mathematics)EngineeringGeologyEngineering drawingMechanical engineeringArtificial intelligenceOperating systemMathematics

Résumé

récupéré en direct d'OpenAlex

Abstract Apache Corp. was investigating new methods to efficiently produce trapped gas in its Stratton Field in South Texas. Recent wells drilled conventionally did not achieve the desired commercial and operational objectives. Casing drilling was selected as a method to achieve these objectives through the operational efficiencies it achieves1 and the ability to minimize lost circulation. Two options were considered during the rig selection phase of the project. The first option was to utilize a purpose built casing drilling rig and the second option was to convert a conventional rig to drill with casing. The project also dictated that a retrievable casing drilling system2 be used to meet logging requirements. Specialized equipment to drill with casing and to retrieve bottom hole assemblies was required on these rigs. Key components of the analysis included the commercial implications of the rig choice, operational performance, and rig crew experience with casing drilling. Introduction The Stratton Field discovered in the late 1930's3, is a gulf coast field located about 45 miles west of Corpus Christi. To date, approximately 495 wells have been drilled in the Stratton Field on a spacing of 20 to 40 acres. The previous drilling program conducted in 2000/2001 yielded below average results both commercially and operationally. The below average performance can be attributed to three main areas. The first area of concern was the amount of drilling fluid lost to the well bore during drilling and its effect on well production and well economics. The second was well bore stability through the Anahuac shale section. The third area was a low drilling rate of penetration in shale sections of the wells. A pilot project utilizing casing drilling was selected as a possible solution. Casing drilling was selected as a method to drill the wells with minimum losses and in turn less risk. The analysis also determined that the wells could be drilled in less time minimizing time dependent well bore stability problems in the Anahuac shale. Casing drilling was also selected based on the analysis that the wells could be drilled more efficiently and with equal or greater rates of penetration than with conventional drilling. A three well program was conducted to test the casing drilling technology and its ability to lower costs, minimize lost circulation, and lower drilling risks. Due to certain requirements of the drilling and completion program, a retrievable casing drilling system was selected. This required the use of a rig capable of using a retrievable casing drilling system. The rig selection centered on two options; utilization of a rig purpose built for casing drilling or a conventional rig converted to handle casing drilling with retrievable systems. This paper explores the rig selection process and its effect on the drilling program. Required Equipment for Casing Drilling Critical to the analysis were the actual additional rig components required to drill with casing. The additional components included a top drive, casing drive assembly, split crown block, split traveling block, wireline winch, and wireline blowout preventers.

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 candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Simulation ou modélisation · Signal consensuel: Simulation ou modélisation
GenreSignal candidat: Empirique · Signal consensuel: aucune
Score de désaccord entre enseignants0,861
Score d'incertitude au seuil0,511

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 recherche0,0000,000
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 Opus0,014
Tête enseignante GPT0,244
Écart entre enseignants0,230 · 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.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSimulation ou modélisation
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

Citations2
Publié2005
Routes d'admission1
Résumé présentoui

Explorer davantage

Même revueOffshore Technology ConferenceMême sujetDrilling and Well EngineeringTravaux en français237 207