Validation of an Optimized qPCR Workflow for MIC Risk Identification and Oilfield Microbial Monitoring
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Validation of a qPCR assay workflow for oilfield microbial monitoring; assay validation in the laboratory sense (polysemy), not research-methods research.
Here validation refers to an oilfield qPCR workflow, not research reproducibility or methodology.
Industrial qPCR workflow validation for oilfield MIC monitoring; assay validation polysemy, not research integrity.
Résumé
In this work, a scalable workflow for field sample preservation, DNA extraction, and quantitative polymerase chain reaction (qPCR) was developed and validated for accurate and rapid oilfield microbial monitoring and microbiologically influenced corrosion (MIC) risk identification. Validation experiments were performed on a variety of challenging oilfield sample types including produced water and pigging sludge to assess the complete optimized qPCR workflow and eight MIC-related qPCR targets including sulfate reducing prokaryotes (SRP) and corrosive methanogens (micH). The predicted in silico taxonomic coverage of these eight MIC-related qPCR targets were compared to a complete microbial community analysis of the samples using 16S rRNA gene sequencing and were found to capture >95% of the taxa present, indicating method reliability for identifying MIC-related microorganisms. The simplified qPCR workflow validated in this work brings qPCR closer to the field to replace or supplement current microbial monitoring practices for higher information yield, ultimately allowing for optimized mitigation strategies and identification of MIC-risk.
Conservé avec la notice de tri, où il sert de preuve aux étiquettes ci-dessus.
La notice
- Revue
- Thématique
- Drilling and Well Engineering
- Domaine
- Engineering
- Établissements canadiens
- LuminUltra Technologies (Canada)
- Organismes subventionnaires
- —
- Mots-clés
- WorkflowIdentification (biology)Computer scienceComputational biologyBiologyDatabase
- Résumé présent dans OpenAlex
- oui