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Abstract There are many different techniques available for the detection, quantification and identification of microorganisms to assess the risk of Microbiologically Influenced Corrosion (MIC). Microbiologically Influenced Corrosion (MIC) is a well-known and documented phenomenon that involves microorganisms and affects multiple industries. The global cost of corrosion is estimated to be US$2.5 Trillion, which is equivalent to 3.4% of the global Gross Domestic Product (GDP) (2013)1. This paper presents a successful case study of selecting, trialing and implementing the most appropriate techniques available for assessing the risk of MIC throughout a large oil and gas production network. The study compared several techniques, with data generated from thousands of samples of varying types including both planktonic and sessile samples. The techniques involved in the study included Adenosine Triphosphate (ATP) test kits, Most Probable Number (MPN) serial dilution kits, Quantitative Polymerase Chain Reaction (qPCR) analysis and Next Generation Sequencing (NGS) analysis. To select the most appropriate industry relevant testing methods a comparative market study was conducted. Information on skills required, turn-around time, data output, estimated ‘per sample’ costs and other applicable information for each technique available was collated and compared. This exercise is prudent when selecting a particular technique as several of the techniques are highly specialised and require trained microbiologists/scientists to perform the sampling, analysis and/or result interpretation. All results were trended and assessed against KPIs which were loaded into a risk decision matrix. This highlighted the benefit of using a combination of methods and the need for both culture-dependent and advanced molecular techniques. The outcome of this study was considered successful as the frequency of MIC related failures significantly reduced over time with the improved accuracy of assessing MIC threat throughout the production network. Optimised sampling, analysis and interpretation was achieved so that concise decisions for mitigating the risk of MIC is possible. MIC is known to commonly affect metals, however non-metallics, including polymeric coatings and fibre-reinforced polymeric composites can also be affected by microbiological activity2.