Characterization and Control of Halophilic Sulfate-Reducing and Methanogenic Microbial Communities in Shale Oil and Gas Systems
Notice bibliographique
Résumé
In recent years, the oil and gas industry has been revolutionized by the expansion of shale oil and shale gas operations due to the advancement of hydraulic fracturing and high economic benefits compared to other unconventional resources. Several mechanisms have been proposed for the possible roles of microorganisms in shale gas fields. However, there remains a lack of knowledge regarding the key microbial players shared by all shale reservoirs and their involvements in the operations. Three case studies were conducted using samples obtained from various shale oil and shale gas reservoirs on the possibility of reservoir souring, microbiologically influenced corrosion (MIC) and microbially enhanced oil recovery (MEOR) through both culture-dependent and independent approaches. Case study I, for the Bakken shale oil field in Saskatchewan Canada, showed that continuous injection of low salinity source water can alter the microbial and geochemical conditions of the reservoir. There is a dominance of halophilic microbial community in the saline shale formations, in which Halanaerobium can synthesize the substrates used by halophilic sulfate-reducing bacteria (SRB) for sulfate-reduction, and halophilic nitrate-reducing bacteria (NRB) can inhibit the growth of SRB through nitrite production. At low salinity, the microbial community is much more diverse involving Halanaerobium, Desulfovibrio, Thiomicrospira, Dethiosulfatibacter and Arcobacter, with high potential for souring and MIC. In addition, at low salinity, nitrate-mediated souring control cannot be as easily achieved as nitrite is further reduced to N2. Case studies II and III were for the Duvernay shale gas field and Montney shale oil field in Alberta, Canada, which showed high MIC potential involving similar halophilic taxa as found in the Bakken field. Finally, samples from all three case studies indicated higher salinities were associated with higher ammonium concentrations, which is a product of methylotrophic methanogenesis using methylamines. The addition of methylamines in the hydraulic fracturing process can facilitate the possible interactions between the key players identified in all three case studies. Through this work, mitigation and monitoring technologies targeting recurring taxa involved in shale reservoirs on souring and MIC can be developed, which is highly beneficial for the environment and the economy.
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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) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| 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 ».