This paper describes the application of “digital pigging” procedures for converting field measurements of pipeline geometry (e.g., top of pipe survey profiles), results from geometry pig surveys, or analytically generated pipeline centerline profiles into corresponding profiles of pipeline curvature and bending strain. Application of digital pigging procedures to pipeline elevation and/or inclination profiles developed from accelerometer based geometry pigs provides a basis for performing the additional calculations required to develop bending strain profiles which may not be a part of the geometry survey deliverable but are required for pipeline structural integrity evaluations. This paper presents examples of digital pig runs over analytical pipe centerline profiles to illustrate the important effects of feature length, pig length and curvature gage length. Comparisons of the results from digital pig runs over actual geometry pig data profiles and digital pig runs over the corresponding known analytical profiles will illustrate how basic pattern recognition concepts can be used as a basis for improved synthesis of real pig data signatures. This paper also presents examples of digital pigging calculations performed on geometry pig survey data that show how low-pass filtering can be used to reduce the effects of noise in the survey data as well as the influence of curvature gage length on the computed curvature/bending strain profiles.

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