SQUEEZE Modelling: Treatment Design and Case Histories
Notice bibliographique
Résumé
SQUEEZE Modelling: Treatment Design and Case Histories E. J. Mackay; E. J. Mackay Heriot-Watt Univ. Search for other works by this author on: This Site Google Scholar M. M. Jordan M. M. Jordan Ondeo Nalco Energy Services Search for other works by this author on: This Site Google Scholar Paper presented at the SPE European Formation Damage Conference, The Hague, Netherlands, May 2003. Paper Number: SPE-82227-MS https://doi.org/10.2118/82227-MS Published: May 13 2003 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Mackay, E. J., and M. M. Jordan. "SQUEEZE Modelling: Treatment Design and Case Histories." Paper presented at the SPE European Formation Damage Conference, The Hague, Netherlands, May 2003. doi: https://doi.org/10.2118/82227-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE European Formation Damage Conference and Exhibition Search Advanced Search Abstract Modelling of scale inhibitor squeeze treatments is routinely performed to assist with chemical selection and to optimise treatment design, many examples having been presented in the literature previously. However, the modelling techniques are not always used to best effect, due to lack of experience, time or a methodical procedure for calculating sensitivities.This paper presents a systematic approach to the use of squeeze models that makes use of laboratory data and field experience to assess, simply and effectively, the options for treatment design. Examples are presented that demonstrate the use of such models in aiding the selection of an appropriate inhibitor and the design of the first treatments as part of an integrated scale management philosophy. Very good accuracy in modelling the core flood is usually achieved. While the match between the model prediction and the first squeeze treatment is typically less accurate, history matching of the model parameters based on the first treatment is shown, by means of examples from two North Sea fields, to enable accurate predictions of numerous subsequent treatments in the same formation. The ability to accurately model treatments means that squeeze performance can be predicted with a high degree of confidence, and thus the treatment design may be optimised. This ability to accurately predicted treatment life is critical as wells mature, and the focus on cost per barrel of treated fluid becomes more critical. The most sensitive parameters are shown to be inhibitor type, inhibitor volume and overflush volume, and the paper discusses how they should be optimised to achieve the desired protection while striking a balance with chemical cost and deferred oil production. Keywords: sorbie, return concentration, oilfield chemistry, inhibitor, production chemistry, scale inhibition, hydrate remediation, isotherm, mackay, inhibitor squeeze treatment Subjects: Production Chemistry, Metallurgy and Biology, Improved and Enhanced Recovery, Formation Evaluation & Management, Inhibition and remediation of hydrates, scale, paraffin / wax and asphaltene Copyright 2003, Society of Petroleum Engineers You can access this article if you purchase or spend a download.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».