Barium Sulphate Scaling and Control during Polymer, Surfactant and Surfactant-Polymer Flooding
Notice bibliographique
Résumé
Abstract Barium Sulphate (BaSO4) scale is a serious problem that is encountered during oilfield production and has been studied mainly for fields undergoing water flooding. Chemical Enhanced Oil Recovery (cEOR) processes involve interactions between the injected brine and the formation brine, rock and oil. Very little work has appeared in the literature on how cEOR processes can influence the severity of the mineral scaling problem that occurs in the field and how this can be managed. This study investigates barium and sulphate co-production behaviour, the deposition of BaSO4 in the formation and in the producer wellbore, and its inhibition during polymer (P), surfactant (S) and surfactant-polymer (SP) flooding cEOR processes. Reservoir simulation has been used in this study, employing homogenous and heterogeneous 2D areal and vertical models. Data from the literature are used to define the parameters controlling the physical and chemical functionality of surfactant and polymer (e.g. oil-water interfacial tension, IFT, polymer viscosity and surfactant and polymer adsorption). Assessment is made of the minimum inhibitor concentration (MIC) required to control scale that is predicted to occur due to changes in brine composition induced by the water and chemical flooding processes. The expected retention and release of a phosphonate scale inhibitor during squeeze treatments in the production wells is modelled. The high viscosity and more stable polymer slug reduces the mixing between the injected and the formation brines, reducing BaSO4 scale precipitation in the formation and delaying the potential scale risk in the producer wellbore compared to normal water flooding. Polymer adsorption causes retardation of the polymer front compared to the sulphate front, accelerating the scale risk in the wellbore. Polymer with low salinity make-up brine and low sulphate concentration not only improves polymer viscosity and enhances recovery, it also delays and reduces the scale risk in the formation and the producer. During surfactant flooding, from an oil recovery perspective, the optimal phase type and salinity can be any of the three microemulsion phase types, depending on the system multiphase parameters. However, the scaling risk can be different to that in the water flooding case, depending on the IFT, ME phase type, the injected salinity and sulphate concentration. In SP flooding, low salinity make-up brine is preferred to enhance oil recovery, and it also delays and reduces scale risk. The impact of the changing brine composition due to ion reactions affected the required MIC values over time. The impact of the MIC and salinity changes on inhibitor retention and release then influences the treatment volumes required to control scale over field life. The study shows that barium and sulphate co-production and the evolving scale risk depend on the mobility ratio (which is determined by the injected brine and oil viscosities), on the oil-water IFT and on the level of chemical adsorption. The severity of the scale risk is also impacted by the flood techniques utilised, with the extent of reservoir reactions have an effect on the MIC required to control scale and the squeeze treatment volumes required to maintain production after breakthrough.
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) | 0,001 | 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 ».