Understanding Trends in Sulphate Concentrations in Produced Water Within Oilfields Under Seawater Flood and With Calcium-Rich Formation Water
Notice bibliographique
Résumé
Abstract Sulphate concentration of produced water is a controlling factor in the scaling tendency of sulphate minerals (BaSO4, SrSO4 and CaSO4). In reservoirs under seawater flood, where the formation water is calcium-rich (>5,000 mg/l), and the reservoir temperature is above moderate levels (>100°C), produced water sulphate concentrations, sulphate mineral scaling potentials and therefore scale mitigation costs are often lower than expected due to deposition of sulphate scaling minerals in the reservoir. To obtain more realistic predictions of sulphate mineral scaling potentials and scale mitigation costs there is significant interest in trying to understand the factors controlling produced water sulphate concentrations and to simulate these data. Various models have been used to simulate produced water sulphate analyses but only reactive transport reservoir simulators incorporate the capability to model the most important factors determining produced water sulphate concentrations: reservoir reactions and mixing in and around the wellbore. However, even in this case the underlying reservoir models are often uncertain and the approach costly and time-consuming. In this study we present a new, two-water mixing model which assumes that water entering a production well is simply a mixture of (a) formation water and (b) an equilibrated mixture of formation water and seawater from which sulphates have precipitated in the reservoir (mixing zone water). This model can be used to explain trends in produced water scaling ions where lower than expected sulphate mineral scaling potentials are observed. By matching trends in produced water scaling ions, the model can be used to determine the variation in production proportions of the two waters, their compositions and seawater contents over time. When applied to wells of the Clyde Field, trends in sulphate and barium produced water analyses are found to reflect a reduction in the proportion of formation water and an increase in that of mixing zone water (and its seawater content) over time. For Gyda wells, the same results were obtained except that later in production, production of formation water ceases and two different mixing zone waters are produced. The model results are what would be expected for wells being progressively affected by a seawater flood and they have also been used to provide reasonable predictions of concentrations of other scaling ions in the produced water. Therefore, although the model is a significant simplification of mixing conditions in and around the well, it does appear to provide reasonable results that are easily obtained. The model results have a number of possible uses including (a) explaining trends in produced water scaling ions and lower than expected sulphate mineral scaling potentials, (b) providing alternative data for undertaking well scaling potential calculations and determination of laboratory MICs, (c) helping identify inadequately preserved samples and (d) potentially constraining the reservoir model.
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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 | 0,001 |
| 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 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 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 ».