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Enregistrement W2533800916 · doi:10.2118/1115-0080-jpt

Wellbore Strengthening in Shales With Nanoparticle-Based Drilling Fluids

2015· article· en· W2533800916 sur OpenAlexaboutno aff
Adam Wilson

Notice bibliographique

RevueJournal of Petroleum Technology · 2015
Typearticle
Langueen
DomaineEngineering
ThématiqueDrilling and Well Engineering
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésOil shaleDrilling fluidDrillingPetroleum engineeringWellboreGeologyChemical engineeringMaterials scienceEngineeringMetallurgy

Résumé

récupéré en direct d'OpenAlex

This article, written by Special Publications Editor Adam Wilson, contains highlights of paper SPE 170589, “Experimental Investigation on Wellbore Strengthening in Shales by Means of Nanoparticle-Based Drilling Fluids,” by Oscar Contreras, SPE, University of Calgary; Geir Hareland, SPE, Oklahoma State University; Maen Husein, University of Calgary; and Runar Nygaard, SPE, and Mortadha Alsaba, Missouri University of Science and Technology, prepared for the 2014 SPE Annual Technical Conference and Exhibition, Amsterdam, 27–29 October. The paper has not been peer reviewed. Wellbore strengthening (WS) is the mechanism of increasing fracture pressure of rock at depth. WS in shale formations is controversial because of the poor understanding of the mechanism and limited field success. This paper presents experimental research in which a significant fracture-pressure increase was achieved in shale and the predominant WS mechanism was identified. The main implication of this work is that WS can occur in shale formations by use of oil-based mud (OBM) with the addition of nanoparticles (NPs) and graphite. Introduction This research presents an original approach based on the use of in-house-prepared NPs and graphite as WS agents in OBM. Catoosa shale cores that are very sensitive to water and air were used. The NPs used in this research are believed to have a high interaction with clays. The NPs locate on top of the clays and fill the gaps or holes in the clay platelets. They are subsequently captured within the clay layers by strong adhesion created as a result of the negative nature of the clay edges. A strong bridge resulting from the interaction between NPs and clay is believed to be a WS agent. WS in shale formations was experimentally achieved in this research. The hypothesis, previously proposed for sandstone cores, that WS is related to mud filtration was also tested. The experimental procedures involved hydraulic-fracturing experiments of a high operational complexity because of the very sensitive nature of the shale. Optical microscopy, scanning electron microscopy (SEM), and energy- dispersive X-ray (EDX) spectroscopy analyses were conducted in cores after testing. Tip resistance by the development of an immobile mass was identified as the predominant WS mechanism on the basis of the post-testing observations and by ruling out the occurrence of stress caging. Fracture-pressure increase was quantified by conducting hydraulic-fracturing tests on 5¾×9-in. Catoosa shale cores. A 9/16-in. wellbore was drilled in the core. Overburden and confining pressures were applied on the cores to simulate a normal-faulting regime. Two injection cycles were applied, allowing 10 minutes for fracture healing after the first cycle. The fracturing pressure was increased by 30% when calcium-based NPs (NP2) were used, whereas iron-based NPs (NP1) resulted in 20% increase. The optimum NP concentrations were identified experimentally. Experimental Analysis Virgin and recycled OBM containing in-house-prepared NPs and graphite were used for the hydraulic-fracturing tests in shale cores. NPs were prepared within the OBM (i.e., in-situ) from solid and aqueous precursors. Graphite was added later. Very low rheology impact was caused by the NPs and graphite at the low levels used in this study.

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 enseignants0,065
Score d'incertitude au seuil0,547

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0010,000
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 Opus0,008
Tête enseignante GPT0,193
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

Citations3
Publié2015
Routes d'admission1
Résumé présentoui

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