Search
Filters
Close

51312-01111-Cost Efficient MIC Management System based on Molecular Microbiological Methods

Product Number: 51312-01111-SG
ISBN: 01111 2012 CP
Author: Ketil Sørensen
Publication Date: 2012
$0.00
$20.00
$20.00
The tools available for microbiological surveillance of oil field systems have significantly improved during the last decade. The introduction of molecular microbiological methods (MMM) has made it possible to reliably monitor the distribution of microorganisms involved in MIC. Thus the limiting factor in MIC surveillance is no longer the quality of the microbiological data but the conversion of these into a reliable risk assessment. Here we describe a model used to perform such a conversion. The model calculates a MIC risk factor as well as worst-case pitting corrosion rates. The calculations are based on numbers of MIC-causing microorganisms measured by quantitative PCR (qPCR) reactions and stoichiometries for the electron flow at the metal surface and empirically determined cell-specific reaction rates. The microorganisms included in the model are sulfate-reducing prokaryotes (SRP) and methanogens since these microbial groups are known to cause MIC by consuming H2 formed at metal surfaces. The application of the MIC model is demonstrated through field cases from the Danish Sector of the North Sea. The field cases show how MMM-based surveillance in combination with a suitable model for MIC risk assessment allows the operator to take timely precautions in order to prevent production failures due to MIC.
The tools available for microbiological surveillance of oil field systems have significantly improved during the last decade. The introduction of molecular microbiological methods (MMM) has made it possible to reliably monitor the distribution of microorganisms involved in MIC. Thus the limiting factor in MIC surveillance is no longer the quality of the microbiological data but the conversion of these into a reliable risk assessment. Here we describe a model used to perform such a conversion. The model calculates a MIC risk factor as well as worst-case pitting corrosion rates. The calculations are based on numbers of MIC-causing microorganisms measured by quantitative PCR (qPCR) reactions and stoichiometries for the electron flow at the metal surface and empirically determined cell-specific reaction rates. The microorganisms included in the model are sulfate-reducing prokaryotes (SRP) and methanogens since these microbial groups are known to cause MIC by consuming H2 formed at metal surfaces. The application of the MIC model is demonstrated through field cases from the Danish Sector of the North Sea. The field cases show how MMM-based surveillance in combination with a suitable model for MIC risk assessment allows the operator to take timely precautions in order to prevent production failures due to MIC.
Product tags
Also Purchased
Picture for UNDER DEPOSIT CORROSION MITIGATION AND ILI ACCURACY IMPROVEMENT IN A SOUR CRUDE GATHERING AND TRANSP
Available for download

51312-01113-UNDER DEPOSIT CORROSION MITIGATION AND ILI ACCURACY IMPROVEMENT IN A SOUR CRUDE GATHERING AND TRANSP

Product Number: 51312-01113-SG
ISBN: 01113 2012 CP
Author: Mark Mattox
Publication Date: 2012
$20.00
Picture for BENEFICIAL EFFECTS OF CHEMICAL TREATMENT AND MAINTENANCE PIGGING PROGRAMS IN RETURNING PIPELINE TO P
Available for download

51312-01098-BENEFICIAL EFFECTS OF CHEMICAL TREATMENT AND MAINTENANCE PIGGING PROGRAMS IN RETURNING PIPELINE TO P

Product Number: 51312-01098-SG
ISBN: 01098 2012 CP
Author: Daniel E. Powell
Publication Date: 2012
$20.00
Picture for The Application of Molecular Microbiological Methods for Early Warning of MIC in Pipelines
Available for download

The Application of Molecular Microbiological Methods for Early Warning of MIC in Pipelines

Product Number: 51313-02029-SG
ISBN: 02029 2013 CP
Author: Jan Larsen
Publication Date: 2013
$20.00