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Remaining useful life assessment for ageing offshore conductors

TWI developed a statistical and probabilistic model to enable a Member company in the Middle East to assess the remaining useful life of its offshore oil and gas wellhead conductors. The resulting insights will underpin life extension decisions and allow the client to make more efficient use of maintenance resources.

The offshore conductor pipes in oil and gas wellhead towers provide a stable structural foundation for the oil well, and their structural integrity must be maintained for the plant to continue operating. These conductors are ageing, and corrosion is one of the main damage mechanisms. The sections of the conductor pipes situated at the mean sea splash zone are especially vulnerable.

With no design documents or operational information available, TWI used a non-destructive technique called saturated low-frequency eddy current (SLOFEC™) to measure the remaining wall thicknesses of the Member company’s conductors.

TWI then analysed the resulting data, using a statistical approach to make useful inferences to help the operators understand the fitness for service of the conductors, and estimate their future corrosion levels and remaining useful life.

Peak-over-threshold extreme value analyses

TWI used the peak-over-threshold (POT) method to model extreme observations (severe defects) in the corrosion data of the conductors. First, the corrosion data was mapped into a matrix (Figure 2) for statistical evaluation. TWI then used statistical

methods to determine a severe-defect threshold (u). Any defect depth readings (exceedances) that exceeded u (Figure 3) were fitted with generalised Pareto distribution (GPD), allowing the maximum defect depth to be estimated.

DBSCAN de-clustering

The growth of one defect is highly likely to influence the growth of neighbouring defects. These defects are said to be “locally dependent”. TWI used density-based spatial clustering of application with noise (DBSCAN) to de-cluster the corrosion data and filter out the dependent observations, such that the remaining exceedances were approximately independent. Figures 4 and 5 show the defect data before and after de-clustering, respectively.

Stochastic defect depth simulation

Because localised corrosion exhibits stochastic behaviour, it is inappropriate to use a constant corrosion rate to predict future defect depths on a component. TWI therefore applied a stochastic simulation using geometric Brownian motion (GBM) and POT to model the corrosion growth beginning from the conductor’s commissioning date. Once the simulation showed a maximum defect depth had grown beyond the maximum allowable depth, it was considered at the end of its useful life (Figure 6).

Probabilistic remaining useful life

TWI also developed a probabilistic remaining useful life assessment model for the client. It integrated the limit state function of conductors by using Monte Carlo and importance sampling methods to approximate the target probability of their failure. The remaining useful life was identified by the difference between the current and the target probability of failure, as shown in Figure 7.

As a result of this work the operator was able to extend the life of its offshore conductors and predict where failures were most likely to occur, enabling optimal use of maintenance and inspection resources.

Figure 1. Severely corroded offshore conductor pipe
Figure 1. Severely corroded offshore conductor pipe
Figure 2. Corrosion data mapping
Figure 2. Corrosion data mapping
Figure 3. POT model only the defect depths that exceed the threshold,
Figure 3. POT model only the defect depths that exceed the threshold,
Figure 4. Defect depth data before de-clustering
Figure 4. Defect depth data before de-clustering
Figure 5. De-clustered defect depth data
Figure 5. De-clustered defect depth data
Figure 6. Remaining useful life estimated with geometric Brownian motion simulation
Figure 6. Remaining useful life estimated with geometric Brownian motion simulation
Figure 7. Probabilistic remaining useful life assessment using importance sampling
Figure 7. Probabilistic remaining useful life assessment using importance sampling

For further information about Integrity Management, and to find out more about TWI’s services to the oil and gas industry, please email contactus@twi.co.uk

Avatar Tan Hwei-Yang Senior Project Leader – Asset and Fracture Integrity Management

Tan joined TWI in 2014 as a Research Engineer in the Asset and Fracture Integrity Management team, where he now works as a Senior Project Leader. He manages a range of projects related to statistical analysis of corrosion samples and risk-based inspection. His main area of work is on risk-based assessment for equipment in the oil and gas industry using various probabilistic and statistical techniques. Before joining TWI, Tan obtained an undergraduate degree in computer sciences, followed by a PhD in the Department of Mechanical, Aerospace and Civil Engineering at Brunel University London.