Elsevier

Corrosion Science

Volume 67, February 2013, Pages 130-141
Corrosion Science

Investigation of the corrosion progress characteristics of offshore subsea oil well tubes

https://doi.org/10.1016/j.corsci.2012.10.008Get rights and content

Abstract

One of the most challenging issues in the offshore oil and gas industry is corrosion assessment and management in subsea structures or equipment. The aim of this study was to investigate the corrosion progress characteristics of offshore oil well tubes used in the production of oil in deep water. A direct measurement database of corrosion damage in terms of pit depth with age (time) in offshore oil well tubes was collated. The corrosion data were statistically analysed to identify the probability density distribution of corrosion damage with time. An empirical formula to predict time-dependent corrosion damage in offshore oil well tubes is suggested based on the results of the statistical analysis. Given that there are few corrosion measurement databases of subsea equipment used for offshore oil and gas production in the literature, this study should prove useful for assessing and managing corrosion damage in deep water offshore oil well tubes, which are key pieces of equipment in offshore oil and gas production systems.

Highlights

► The paper was revised as per the review comments. ► The paper title was changed to more clearly address the aims and scope of the paper. ► Other review comments have already been answered and implemented in the revised paper.

Introduction

Offshore oil and natural gas have long been used to meet the sustained and increasing demand for energy. In recent years, the hydrocarbon resources in shallow waters and reasonably benign environments have been largely depleted, and the oil and gas industries have been compelled to move into more challenging environments such as deeper waters and harsher metocean conditions. These industries will continue to explore and exploit deeper waters as long as the demand for oil and gas continues to increase.

Most of the equipment currently used in the offshore oil and gas industry is approaching the end of its useful life, and the possibility of equipment failing without significant warning is high. Recent oil spills and equipment failures have demonstrated this danger. Various factors contribute to these incidents, including human error, lack of advanced knowledge and corrosion effects.

Generally, ageing is a dominant life-limiting factor for any structure, and corrosion is one is of the most serious features of ageing [1]. It is well known that corrosion is a very complex process, particularly in marine environments where it is significantly affected by many environmental and material factors [2], [3], [4]. Corrosion problems occur in numerous subsystems within the offshore oil and gas production system, including oil well tubes. It is essential to ensure that oil well tube structures are running in a safe and controlled environment. Structures such as ships can be repaired and maintained in a variety of ways, and usually have dry docking procedures for maintenance and inspection. There are no such procedures for the maintenance and repair of oil well tube structures at subsea levels. Corrosion tolerance must thus be carefully considered in the design of these structures. A schematic figure of a subsea system with oil well tubes is shown in Fig. 1.

The aim of this study was to investigate the corrosion progress characteristics of offshore oil well tubes in deep water and to suggest an empirical formula for predicting the time-dependent corrosion wastage of these tubes.

Several relevant studies can be found in the literature. Fu et al. [5] noted that the main factors contributing to oil tube corrosion are sweet corrosion and erosion gas fluids. They used the grey relational method to determine the extent of the correlation between the various factors in a system with uncertain information. Ren et al. [6] used X-ray diffraction, scanning electron microscopy, and electrochemical measurement to investigate the corrosion behaviour of N80 steel tubes in a static solution containing carbon dioxide (CO2) and hydrogen sulphide (H2S). Migahed et al. [7] studied the use of a newly synthesised compound as a corrosion inhibitor during the acidisation process in petroleum production operations.

In studying the effect of flexure on the corrosion mechanism, Melchers and Paik [8] concluded that the corrosion rate increases by 10–15% when a structure is near or beyond the elastic limit of steel. Paik and Tayamballi [9] emphasised that corrosion is one of the factors that may affect the ultimate strength behaviour of steel plate and that careful assessment needs to take into consideration when to accommodate this effect. Many studies have been conducted on the corrosion of pipeline structures, especially pipeline pitting corrosion [10], [11], failure pressure prediction for corroded pipelines [12], [13], [14] and a general overview of pipeline corrosion [15].

Research has also been conducted on corrosion modelling. Paik et al. [16], [17], [18], [19] developed time-dependent corrosion wastage models for ship structures. By statistically analysing corrosion data, they proposed a mathematical function that defines a time-dependent corrosion wastage model. Recently, Paik and Kim [20] developed an advanced method for developing a time-dependent empirical corrosion wastage model that applies the probability density parameter technique to the age of a structure. Melchers et al. [21] statistically characterised corroded steel surfaces exposed to marine environments, and found that the considerable differences in corrosion loss between different exposure zones are statistically dependent on the surface topography. Melchers also reviewed the research on physical corrosion modelling in marine environments [22], [23], [24], [25], [26], [27]. Chernov [28] and Chernov and Ponomarenko [29] developed a corrosion model that takes account of the effect of the environment on corrosion. Numerous other empirical models of ship corrosion wastage have been developed [16], [17], [18], [19], [30], [31], [32].

Najjar et al. [33] and Jarrah et al. [34] both suggested an advanced method that efficiently predicts the maximum corrosion pit depth using a combination of two statistical methods. In these papers, generalised lambda distributions together with a computer-based bootstrap method were used to determine a model of distribution fitting and to generate simulated distributions that were equivalent to the experimental case. Chowdhury [35] attempted to derive accurate empirical relationships between the mean and standard deviation of any given midship section as simple functions of corrosion loss. He observed that all geometric properties are linear functions of the total corrosion loss, and that there is a single constant relevant to the section that specifies the property completely.

However, all of this previous research on corrosion wastage models is limited to ships and floating structures. To the best of the authors’ knowledge, there are no corrosion wastage models for subsea oil well tube structures. This study aimed to fill that gap by contributing to the characterisation of corrosion progress in offshore oil well tubes. With the help of an offshore oil and gas production company, a direct measurement database of corrosion damage in terms of pit depth with time (age) in offshore oil well tubes was collated. The method of Paik and Kim [20] was then used to derive an empirical formula to predict the time-dependent corrosion damage of the tubes.

Section snippets

Classification of oil well tube corrosion

In general, several types of corrosion are relevant to offshore steel structures, as shown in Fig. 2 [2]. However, the corrosion classification schemes for subsea oil well tube structures are slightly different. There are five types: ring, line, general, isolated and hole corrosion [34]. This corrosion classification is illustrated in Fig. 3.

Collation of the corrosion measurement database for offshore subsea oil well tubes

With the help of an offshore oil and gas production company, a direct measurement database of corrosion damage in offshore subsea oil well tubes was collated. Corrosion measurements for seven oil well tubes with an age range of 5.1–22.8 years were obtained. Details of the corrosion measurements for each oil well tube are given in Table 1. Fig. 4 shows the principal view of an oil well tube. Table 1 shows that the greater the water depth of an oil well tube, the larger the number of measurements

Probabilistic characteristics of corrosion damage

The corrosion measurements in the database were statistically analysed. Fig. 9 shows the probability density distribution (PDF) and cumulative density distribution (CDF) versus pit depth for various ages of oil well tubes. Fig. 9 also compares possible representations of the various probability density functions to the corrosion database.

The probability density function that best represents the corrosion database was determined by a goodness of fit test. The Anderson–Darling [37] test statistic

Concluding remarks

The aim of this study was to investigate the progress characteristics of corrosion in offshore subsea oil well tubes and develop an empirical formula for the prediction of the time-dependent corrosion pit depth. The following conclusions are drawn from the findings.

  • (1)

    Although it is very hard to obtain direct measurements of offshore subsea oil well tubes, the MIT (Multifinger Imaging Tool) system proves useful in this regard.

  • (2)

    The probability density distribution of corrosion pit depth in offshore

Acknowledgements

This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education, Science and Technology (Grant No.: K20903002030-11E0100-04610). The study was undertaken at The Lloyd’s Register Educational Trust (LRET) Research Centre of Excellence (Ship and Offshore Research Institute) at Pusan National University, Korea. The LRET funds education, training and research programmes in transportation, science,

References (38)

  • T. Nakai et al.

    Corroded structures and residual strength

  • J.K. Paik et al.

    Marine corrosion mechanisms

  • B.J. Little et al.

    Microbiologically Influenced Corrosion, Hoboken

    (2007)
  • A.C. Palmer et al.

    Subsea Pipeline Engineering

    (2008)
  • A. Igor et al.

    Pitting corrosion in pipeline steel weld zones

    Corros. Sci.

    (2011)
  • R.E. Melchers et al.

    Effect of flexure on rusting of ship’s steel plating

    Ships Offshore Struct.

    (2010)
  • J.K. Paik et al.

    Some recent developments on ultimate limit state design technology for ships and offshore structures

    Ships Offshore Struct.

    (2006)
  • D.D. Leon et al.

    Effect of spatial correlation on the failure probability of pipelines under corrosion

    Int. J. Press. Vessels Pip.

    (2005)
  • E.S. Meresht et al.

    Failure analysis of stress corrosion cracking occurred in a gas transmission steel pipeline

    Eng. Fail. Anal.

    (2011)
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