Predictive Assessment of External Corrosion on Transmission Pipelines

2008 ◽  
Author(s):  
Gae¨l Pognonec ◽  
Vincent Gaschignard ◽  
Philippe Notarianni
Keyword(s):  
Growth Rate ◽  
Oil And Gas ◽  
Electrochemical Corrosion ◽  
Software Tool ◽  
Probability Of Failure ◽  
Entropy Method ◽  
Probabilistic Methods ◽  
Optimal Interval ◽  
Annual Probability ◽  
Cross Entropy Method

Oil and Gas operators have to deal with the ageing process of their transmission pipeline grid. Some of these pipelines can be inspected using In Line Inspection (ILI) tools. In order to maintain an acceptable integrity level, re-inspection operations have to be performed. This process needs to be optimized in terms of resources and cost. Gaz de France R&D Division has developed a methodology which prioritizes rehabilitation operations on a pipeline after in-line inspections, and determines the optimal interval for re-inspection. A reliable help decision software tool which applies the methodology has also been developed. Dealing with defects assimilated to external electrochemical corrosion, the developed methodology is based on: • pigs information in order to assess a probable corrosion growth rate; • probabilistic distribution of input parameters (geometrical characteristics of defects, characteristics of the pipe and corrosion growth rate); • probabilistic methods of calculation : the probability of failure is calculated with the Monte-Carlo method. The convergence of the calculation is accelerated with the Cross Entropy method. The calculation results take the form of three probabilities of failure: • a punctual probability of failure for each defect; • an annual probability of failure for each defect; • an annual probability of failure per kilometer of pipe. To interpret the results, the annual probability of failure per kilometer of pipe is then compared with threshold values.

Subset Simulation for Structural Reliability Analysis of Pipeline Corrosion Defects

2020 ◽  
Author(s):  
Daryl Bandstra ◽  
Alex M. Fraser
Keyword(s):  
Monte Carlo ◽  
Structural Reliability ◽  
Oil And Gas ◽  
Probability Of Failure ◽  
Computational Effort ◽  
Probabilistic Methods ◽  
Direct Monte Carlo Simulation ◽  
Metal Loss ◽  
Subset Simulation ◽  
Small Probabilities

Abstract One of the leading threats to the integrity of oil and gas transmission pipeline systems is metal-loss corrosion. This threat is commonly managed by evaluating measurements obtained with in-line inspection tools, which locate and size individual metal-loss defects in order to plan maintenance and repair activities. Both deterministic and probabilistic methods are used in the pipeline industry to evaluate the severity of these defects. Probabilistic evaluations typically utilize structural reliability, which is an approach to designing and assessing structures that focuses on the calculation and prediction of the probability that a structure may fail. In the structural reliability approach, the probability of failure is obtained from a multidimensional integral. The solution to this integral is typically estimated numerically using Direct Monte Carlo (DMC) simulation as DMC is relatively simple and robust. The downside is that DMC requires a significant amount of computational effort to estimate small probabilities. The objective of this paper is to explore the use of a more efficient approach, called Subset Simulation (SS), to estimate the probability of burst failure for a pipeline metal-loss defect. We present comparisons between the probability of failure estimates generated for a sample defect by Direct Monte Carlo simulation and Subset Simulation for differing numbers of simulations. These cases illustrate the decreased computational effort required by Subset Simulation to produce stable probability of failure estimates, particularly for small probabilities. For defects with a burst probability in the range of 10−4 to 10−7, SS is shown to reduce the computational effort (time or cost) by 10 to 1,000 times. By significantly reducing the computational effort required to obtain stable estimates of small failure probabilities, this methodology reduces one of the major barriers to the use of reliability methods for system-wide pipeline reliability assessment.

A Z-number integrated weighted MULTIMO-ORA method for risk prioritization in FMEA

2021 ◽  
pp. 1-15
Author(s):  
Weizhong Wang ◽  
Yilin Ma ◽  
Shuli Liu
Keyword(s):  
Risk Analysis ◽  
Risk Evaluation ◽  
Oil And Gas ◽  
Weighted Average ◽  
Entropy Method ◽  
The Self ◽  
Analysis Problem ◽  
Risk Prioritization ◽  
Self Confidence ◽  
Evaluation Information

Current risk prioritization approaches for FMEA models are insufficient to cope with risk analysis problem in which the self-confidence of expert’s judgment and the deviation among risk evaluation information are considered, simultaneously. Therefore, to remedy this limitation, this paper reports an extended risk prioritization approach by integrating the MULTIMOORA approach, Z-numbers and power weighted average (PWA) operator. Firstly, the Z-numbers with triangular fuzzy numbers are applied to reflect the self-confidence and uncertainty of expert’s judgment. Next, the PWA operator for Z-numbers (Z-PWA) with similarity measure is proposed to obtain the group risk evaluation matrix by considering the influence of the deviation among risk evaluation information. Then, an extended version of MULTIMOORA method with developed entropy method is presented to calculate risk priority ranking order of each failure. Finally, the equipment failures in a certain oil and gas plant is utilized to test the extended risk prioritization approach for FMEA model. After that, the sensitivity and comparison studies are led to illustrate the availability and reliability of the proposed risk prioritization approach for FMEA based risk analysis problem.

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