Impact of Temperature on Scale Formation in Chalk Reservoirs
Notice bibliographique
Résumé
Abstract Operators are collecting an abundance of produced water data that is often underused. Produced water composition data provide clues as to what geochemical reactions are taking place in the subsurface. This information can be useful for monitoring interwell connectivity, and for predicting and managing oilfield scale resulting from brine supersaturation. Coupling thermodynamic calculations with produced water analysis helps to identify geochemical effects that could impact oil recovery. This work addresses the difference that reservoir temperature has on geochemical reactions in carbonate reservoirs by comparing data from two offshore fields, and identifying the rock/brine and brine/brine reactions that will impact scale management. Two seawater flooded chalk fields located close to each other, were selected as candidates for comparison. The temperature of one field is 130°C, while for the other it is 90°C. 6800 produced water samples from these two fields were analysed, and the compositional trends were plotted to identify deviation from conservative (non-reacting) behaviour. The compositional trends were then grouped to identify if there were common features between wells. This analysis was complemented by one dimensional reactive transport modelling to identify which reactions would be consistent with the observed trends. Two groups of wells were identified within each reservoir based on the produced brine compositional behaviour. Each well group exhibits distinct ion trend behaviour, especially with respect to barium, calcium, strontium and magnesium concentrations – these being divalent cations that are abundant in the formation brines. The breakthrough of sulphate, a component primarily introduced during seawater flooding, varies very significantly between the two groups in each case. In one grouping the sulphate is barely retarded at all, and breaks through at seawater fractions lower than 10%. In the other grouping, however, sulphate does not break through until the seawater fraction in the produced brine exceeds 75%. This retardation of sulphate occurs most strongly in the hotter reservoir, and this may be attributed to the lower solubility of the calcium sulphate mineral anhydrite at higher temperature. The retardation of sulphate then means that barium is produced at higher concentrations, since barite precipitation in the reservoir is thus restricted due to sulphate being the limiting ion. However, some sulphate stripping does occur in the cooler reservoir, despite the higher solubility of anhydrite. Furthermore, in all cases magnesium is retarded, with some groupings exhibiting complete stripping of magnesium from the injected seawater. The magnesium stripping behaviour is reproduced in the reactive transport models when calcium and magnesium replacement reactions are allowed. This phenomenon has been observed elsewhere in coreflood experiments, and also contributes to the sulphate stripping through promotion of anhydrite precipitation within the rock. This process, which is beneficial in terms of reducing the scale risk, is more pronounced at higher temperatures. Higher temperature chalk reservoirs may thus act as natural sulphate reduction plants, reducing scaling, souring risks and so operating costs of the fields.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 | 0,001 | 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 source (Gemma direct ou Codex distillé), 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 ».