«Proceedings of Gubkin University»

Improving reliability of inline inspection results

UDC: 620.179.14
DOI: -

Authors:

¹ Gazprom Diagnostika, Saint Petersburg, Russian Federation
² National University of Oil and Gas “Gubkin University”, Москва, Российская Федерация

Keywords: corrosion, defect, gas pipeline, inline inspection, electrometry

Annotation:

The article is dedicated to the problem of improving the reliability of diagnostic data. The authors made an attempt to combine the results of inline inspection with information obtained during electrometric surveys. To assess the correlation of heterogeneous data and determine the feasibility of developing an advanced comprehensive methodology, a large dataset was processed within the corporate database over several decades. Characteristic metrics were obtained and numerical modeling was carried out to assess the convergence of the results. The outcomes of this work can be used for deep learning of a neural network, which is highly likely to predict the occurrence of defects and their evolution, taking into account the dynamics of electrometric data.

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