Abstract: Combinations of a nitroprusside, such as sodium nitroprusside (SNP; Na2[Fe(CN)5NO].2H2O) and a nitrate, are provided, together with methods for the combined use of the nitroprusside and the nitrate as metabolic inhibitors of microbial cultures. The microbial cultures may include sulfate reducing bacteria (SRB) in aqueous culture. This metabolic inhibition may for example be implemented in the presence of a hydrocarbon, for example in an oil reservoir or in oil field systems and facilities. When applied to an SRB culture in the presence of a hydrocarbon, the combination of the nitroprusside and the nitrate may accordingly be used to ameliorate the biological formation of sulfides, particularly hydrogen sulfide.

Abstract: Combinations of a nitroprusside, such as sodium nitroprusside (SNP; Na2[Fe(CN)5NO].2H2O) and a nitrate, are provided, together with methods for the combined use of the nitroprusside and the nitrate as metabolic inhibitors of microbial cultures. The microbial cultures may include sulfate reducing bacteria (SRB) in aqueous culture. This metabolic inhibition may for example be implemented in the presence of a hydrocarbon, for example in an oil reservoir or in oil field systems and facilities. When applied to an SRB culture in the presence of a hydrocarbon, the combination of the nitroprusside and the nitrate may accordingly be used to ameliorate the biological formation of sulfides, particularly hydrogen sulfide.

Abstract: Provided are methods for diagnosing, monitoring and mitigating microbiologically influenced corrosion (MIC). The methods employ steps to determine the nature and concentration of biological signatures, formed through metabolism of microorganisms, and correlating the biological signatures with MIC. Based on such analyses, appropriate MIC mitigation strategies may be implemented so as to efficiently target MIC at sites of interest. The methods advantageously allow selection of appropriate MIC mitigation treatments that correspond to the level of severity of the MIC and based on historical data correlating particular biological signatures with particular MIC risk.