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Enregistrement W2040418288 · doi:10.2118/113686-ms

Predesigned Bottomhole Pressure (BHP) in Aerated Drilling Matches in the Field and Improves Drilling Performance in Carbonate Reservoir

2008· article· en· W2040418288 sur OpenAlexaff
Farid Shirkavand, G. Hareland, Mohammad Behbahani, Vahidreza Mostafavi

Notice bibliographique

RevueAll Days · 2008
Typearticle
Langueen
DomaineEngineering
ThématiqueDrilling and Well Engineering
Établissements canadiensUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésLost circulationDrillingRate of penetrationUnderbalanced drillingDrilling fluidPetroleum engineeringVolumetric flow rateAerationWell controlAnnulus (botany)Environmental scienceGeologyEngineeringMechanical engineeringMaterials scienceWaste managementMechanics

Résumé

récupéré en direct d'OpenAlex

Abstract A field case analysis of under balanced drilling (UBD) in the "A" structure located in Southern Iran has been carried out in the present paper. It was initially reported that 51% of an average well's cost was Non-Productive Time (NPT). Typical recordable NPT categories and key performance indicators used include tight hole, tool failure, hole cleaning issues, well control and lost circulation. It was decided that aerated drilling could be applied with advantages such as higher penetration rates, less lost circulation and overall lower drilling cost. As part of designing these wells the bottom hole pressure (BHP) was minimized. This paper shows that in the planned UBD, pre-simulated BHP is in good agreement with the operational BHP. The well drilling design of mud and air rates and the corresponding pressures are in this paper have been plotted against the field recorded pressures for different mud and air rates. The result of the pre-simulations also revealed that there is an unfavorable range of mud flow rate that provides a low BHP of the aerated mud for different mud rate and air injection rates. By illustrating the BHP (dynamic and static), annulus back pressure and different mud rates, it has been shown that an optimum combination, of mud and air rates must be determined in order to maximize the penetration rate. The design process of BHP includes checking for required cuttings carrying capacity, which is determined by ensuring that kinematics energy per unit volume is enough for all planned rates. The design method presented herein also suggests injecting air into mud during drilling of the lost circulation intervals as the best mud loss controlling method. The methodology and the calculation procedures used to pre-design the operation are presented herein with the field data against the pre-estimated. The results of this approach in the field have given reduction in NPT with some results presented herein. Introduction A well was drilled with an aerated drilling program to reach the "A" structure located immediately to the east of the central Iranian fault along with Dashtak and Kutah structures, in Fars North area. Close by, on the western side of the fault, other fractured gas and oil fields are located. During drilling of well "A-1", the larger challenge was controlling mud weight to avoiding lost circulation, tight hole and wellbore collapse (Figure 1). At the depth of 3850m, loss of circulation with rate of 90–170 bbl/hr was observed, which was controlled with LCM (Lost Circulation Material) after about 3.72 days. Drilling operation continued with 18–42 bbl/hr losses down to the depth of 3890 m and to 3928 m with 67.5 pcf mud and 8–21 bbl/hr losses. At 4242 m the mud weight was decreased to 65.5 pcf and well started to flow at 20 bbl/hr. At this point the mud weight was gradually increased to 67.5 pcf while continuous loss and salt water flow was occurring. It is believed that the well could only have been drilled with aerated drilling practices because of the specific challenges encountered.

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: Empirique
Score de désaccord entre enseignants0,013
Score d'incertitude au seuil0,689

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 Opus0,011
Tête enseignante GPT0,195
Écart entre enseignants0,184 · 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

Citations0
Publié2008
Routes d'admission1
Résumé présentoui

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