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A sulfur and nitrogen cycle informed model to simulate nitrate treatment of reservoir souring

Nitrate treatment has been widely used in various seawater injection projects to treat biologic sulfate reduction or reservoir souring. To design a promising nitrate treatment plan, it is essential to have a comprehensive understanding of reactions that represent the microbial communities of the res...

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Detalles Bibliográficos
Autores principales: Jahanbani Veshareh, Moein, Nick, Hamidreza M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6525193/
https://www.ncbi.nlm.nih.gov/pubmed/31101870
http://dx.doi.org/10.1038/s41598-019-44033-5
Descripción
Sumario:Nitrate treatment has been widely used in various seawater injection projects to treat biologic sulfate reduction or reservoir souring. To design a promising nitrate treatment plan, it is essential to have a comprehensive understanding of reactions that represent the microbial communities of the reservoir and mechanisms through which the souring process is inhibited. We employ a new approach of evaluating different reaction pathways to design reaction models that reflect governing microbial processes in a set of batch and flow experiments. Utilizing the designed models, we suggest dissimilatory nitrate reduction to ammonium is the main reaction pathway. Additionally, we illustrate nitrite inhibition is the major mechanism of nitrate treatment process; independent of nitrate reduction being autotrophic or heterotrophic. We introduce an inhibitory nitrate injection concentration that can inhibit souring regardless of nitrite inhibition effect and the distance between injection and production wells. Furthermore, we demonstrate that the ratio of the nitrite-nitrate reduction rate can be used to estimate nitrate treatment effectiveness. Our findings in regard to importance of nitrite inhibition mechanism and the inhibitory nitrate concentration are in accordance with the field observations.