Successful in the Lab, Not as Effective in the Field? Uncertainties in the Field Observations of Low Salinity Water Flooding in Sandstone and Carbonate Reservoirs-A Critical Analysis
Notice bibliographique
Résumé
Abstract Low salinity waterflooding has been an area of great interest for researchers for almost over three decades for its perceived "simplicity," cost-effectiveness, and the potential benefits it offers over the other enhanced oil recovery (EOR) techniques. There have been numerous laboratory studies to study the effect of injection water salinity on oil recovery, but there are only a few cases reported worldwide where low salinity water flooding (LSW) has been implemented on a field scale. In this paper, we have summarized the results of our analyses for some of those successful field cases for both sandstone and carbonate reservoirs. Most field cases of LSW worldwide are in sandstone reservoirs. Although there have been a lot of experimental studies on the effect of water salinity on recovery in carbonate reservoirs, only a few cases of field-scale implementation have been reported for the LSW in carbonate reservoirs. The incremental improvement expected from the LSW depends on various factors like the brine composition (injection and formation water), oil composition, pressure, temperature, and rock mineralogy. Therefore, all these factors should be considered, together with some specially designed fit-for-purpose experimental studies need to be performed before implementing the LSW on a field scale. The evidence of the positive effect of LSW at the field scale has mostly been observed from near well-bore well tests and inter-well tests. However, there are a few cases such Powder River Basin in the USA and Bastrykskoye field in Russia, where the operators had unintentionally injected less saline water in the past and were pleasantly surprised when the analyses of the historical data seemed to attribute the enhanced oil recovery due to the lower salinity of the injected water. We have critically analyzed all the major field cases of LSW. Our paper highlights some of the key factors that worked well in the field, which showed a positive impact of LSW and a comparative assessment of the incremental recovery realized from the reservoir visa-a-vis the expectations generated from the laboratory-based experimental studies. It is envisaged that such a comparison could be more meaningful and reliable. Also, it identifies the likely uncertainties (and their sources) associated during the field implementation of LSW.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| 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 | 0,001 |
| 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 ».