Abstract
This paper presents a novel approach to determine optimal maintenance policies for degraded oil and gas pipelines due to internal pitting corrosion. This approach builds a bridge between Markov process-based corrosion rate models and Markov decision processes (MDP). This bridging allows for the consideration of both short-term and long-term costs for optimal pipeline maintenance operations. To implement MDP, probability transition matrices are estimated to move from one degradation state to the next in the pipeline degradation Markov processes. A case study is also implemented with four pipeline failure modes (i.e., safe, small leak, large leak, and rupture). And four maintenance actions (i.e. do nothing, adding corrosion inhibitors, pigging, and replacement) are considered by assuming perfect pipeline inspections. Monte Carlo simulation is performed on 10,000 initial pits using the selected corrosion models and assumed maintenance and failure costs to determine an optimal maintenance policy.
Highlights
Corrosion is the primary failure mechanism of oil and gas pipelines, and among different corrosion mechanisms, pitting corrosion is the most common one (Heidary & Groth, 2021)
An approach is proposed in this paper to identify the optimal maintenance policy for aged oil and gas pipelines undergoing pitting corrosion by using Markov Decision Process (MDP) modeling
Despite different Markov process-based corrosion rate models that have been proposed for modeling pitting corrosion, Markov decision processes (MDP) have rarely been used to find optimal maintenance policies for corroding pipelines
Summary
Corrosion is the primary failure mechanism of oil and gas pipelines, and among different corrosion mechanisms, pitting corrosion is the most common one (Heidary & Groth, 2021). In order to conduct an MDP analysis, we propose a procedure to define the transition probabilities and calculate the probability transition matrix This will enable transition between states of a Markov process for pipeline degradation due to internal pitting corrosion. The prediction of PoF approaches is more reliable when these models are calibrated with reliable data Since they are based on some approximations and simplifying assumptions when the degradation process is complex (e.g., pitting corrosion), it isn’t easy to estimate the model parameters and validate the results (An, Kim, Choi, 2015). It is more practical to use data-driven approaches for integrity management of pipelines undergoing pitting corrosion (Shibata, 1996; Valor, Caleyo, Alfonso, Rivas, & Hallen, 2007). A Markov process-based pitting corrosion model, a requirement to use MDP, is utilized to find an optimal maintenance policy. An optimal maintenance policy is estimated for a case study by using this framework
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