4.7 Article

Operational subsea pipeline assessment affected by multiple defects of microbiologically influenced corrosion

Journal

PROCESS SAFETY AND ENVIRONMENTAL PROTECTION
Volume 158, Issue -, Pages 159-171

Publisher

ELSEVIER
DOI: 10.1016/j.psep.2021.11.032

Keywords

MIC management; Reliability-based maintenance; Markov process; Condition Modelling

Funding

  1. Genome Canada
  2. Canada Research Chair (CRC) Tier I Program in Offshore Safety and Risk Engineering
  3. Natural Sciences and Engineering Research Council of Canada (NSERC)

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This paper presents a systematic approach to evaluate the optimal maintenance strategy time interval for a subsea process system influenced by Microbiological Influenced Corrosion (MIC) within multiple defects. The proposed method incorporates modeling of defect generation, pit depth growth, and maximum pit depth, along with simulating maintenance strategies to identify the optimal strategy.
This paper presents a systematic approach to evaluate the time interval of optimal maintenance strategy for the subsea process system influenced by Microbiological Influenced Corrosion (MIC) within multiple defects. The proposed method incorporates the non-homogeneous Poisson, homogeneous gamma, and non homogeneous Markov processes for modeling the generation of multiple defects, the average pit depth growth, and maximum pit depth, respectively. The maintenance strategy comprises industrial procedure, probability of failure detection, errors sizing in-line inspection tools, management actions costs, and failure cost. The developed framework simulates maintenance strategies considering time interval, cost, probability of detection, average pit depth, and maximum pit depth and identifies the optimal strategy. The practical application is demonstrated in a North Sea subsea pipeline system under MIC's influence. This work assists decision-makers in selecting the optimal conditioned-based maintenance strategy for the processing system. While the application is demonstrated to subsea process systems under MIC influence, the developed approach is equally applicable to other process systems. (c) 2021 Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

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