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  • Internal Corrosion Sample Collections Guidelines (IC-1-6)
In This Newsletter Issue
Alternatives to Current Leak Detection Approaches for Hydrotesting (PL-1-3)
DOT Co-Funded Satellite Program Kicks Off
Development of Improved Crack Depth Measurement Techniques (NDE-2-1)
ILI Tool Calibration on In-ditch Measurement with Related Uncertainty (EC-4-2)
Internal Corrosion Sample Collections Guidelines (IC-1-6)
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Internal Corrosion Sample Collections Guidelines (IC-1-6)

Pipeline liquid and solid samples collected as a part of internal corrosion monitoring and other assessment activities are vulnerable to compositional changes resulting from sample handling procedures. These compositional changes can affect subsequent test results and the usefulness/accuracy of the data. Internal corrosion constituents are known to change as a function of time, temperature, and pressure; however, there are no published guidelines that describe how the sample has changed as a function of handling procedures.

 

The aim of this research is to identify the changes to internal corrosion constituents in pipeline samples (i.e., microbiological, dissolved hydrogen sulfide, dissolved carbon dioxide, pH, and alkalinity) which may occur due to time, sample handling and environmental factors and, based on these findings, develop clear guidelines for internal corrosion sample collection and handling.

 

A set of experiments performed in this study were able to demonstrate some effects of sample holding time, sample holding temperature, and sample container headspace on certain constituents (pH, dissolved CO2, dissolved H2S, alkalinity, culturable bacteria) typically measured during internal corrosion evaluations. The project also identified general considerations for establishing and implementing internal corrosion sampling programs, since other factors in addition changes that occur during handling can affect the accuracy, quality, and utility of test results.

 

The deliverables of this project can be used directly by operators to assess their sampling programs and also provide a foundation from which a comprehensive best practice for sampling programs can be developed.

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