Condition assessment, remaining useful life prediction and life extension decision making for offshore oil and gas assets

Abstract

Offshore oil and gas assets are highly complex structures comprising of several components, designed to have a lifecycle of 20-25 years of working under harsh operational and environmental conditions. These assets, during their operational lifetime, are subjected to various degradation mechanisms such as corrosion, erosion, wear, creep and fatigue cracks. In order to improve economic viability and increase profitability, many operators are looking at extending the lifespan of their assets beyond the original design life, thereby making life extension (LE) an increasingly critical and highly-discussed topic in the offshore oil and gas industry. In order to manage asset aging and meet the LE requirements, offshore oil and gas operators have adopted various approaches such as following maintenance procedures as advised by the original equipment manufacturer (OEM), or using the experience and expertise of engineers and inspectors. However, performing these activities often provides very limited value addition to operators during the LE period of operation. This paper aims to propose a systematic framework to help operators meet LE requirements while optimizing their cost structure. This framework establishes an integration between three individual life assessment modules, namely: condition assessment, remaining useful life (RUL) prediction and LE decision-making. The benefits of the proposed framework are illustrated through a case study involving a three-phase separator system on a platform which was constructed in the mid-1970s in West Africa. The results of this study affirm the effectiveness of this framework in minimizing catastrophic failures during the LE phase of operations, whilst ensuring compliance to regulatory requirements.

An overview of maintenance management strategies for corroded steel structures in extreme marine environments

“…The RUL estimation models are either deterministic or probabilistic, but they generally incorporate degradation factors, material properties, and environmental conditions [53]. The RUL estimation models can be classified into four categories: analytical (physics-based), modelbased (data-driven), knowledge-based, and hybrid (fusion) (see Figure 2) [54][55][56][57]. The RUL methods can be further refined into a more accurate maintenance model by the use of statistical and Artificial Intelligence (AI) techniques [58].…”

“…Although the corrosion affects the performance of an assets throughout the life cycle, the extent of the damage varies depending on many factors such as the designed allowance for corrosion loss, the effectiveness of preservation methods, and severity of dynamic environmental conditions [73]. The main function of a reliable maintenance scheme is to identify the critical components, functions, failure modes, causes, effects and consequences, and then recommend a cost- In commercial ships, the operators/owners either rely on OEM's recommendations or seek the expertise of engineers to determine maintenance support requirements [56]. OEM's maintenance procedures are often based on the age of the ships, not real-time degradation data.…”

“…These methods have been instrumental to develop the relations between various dependent/independent process variables and estimate the likelihood of occurrence of events. The statistical/stochastic techniques that are commonly adopted by researchers include: multivariate analysis, regression models, Copulas, Markov process, Poisson process, Monte-Carlo simulation, Cox's approximation, and Weibull analysis [35,56,118,217]. Detailed deliberation on the maintenance procedures, their planning, inspection and prediction trends using various statistical models and methodologies are explained in details in [33,66,[218][219][220].…”

A Holistic Framework for Supporting Maintenance and Asset Management Life Cycle Decisions for Power Systems

“…The natural response would significantly cling on the effectiveness of maintenance and asset management (MAM) strategies. Maintenance can be described as the combination of technical, administrative and managerial endeavours that ensure that industrial assets cost-effectively and safely perform their designated tasks [10][11][12][13][14][15]. Maintenance philosophies can be broadly classified into breakdown maintenance (BM), planned periodic maintenance (PPM) and condition based maintenance (CBM).…”

Structural Health Monitoring (SHM) and Determination of Surface Defects in Large Metallic Structures using Ultrasonic Guided Waves

“…Mechanical structures and their reliability deteriorate continuously under the influence of operating and ambient environmental conditions. The structural degradation processes may occur in different forms of corrosion, fatigue cracks, erosion, and strength reduction [ 1 ]. The extent and severity of these mechanisms depend on the applied static/dynamic loads, operating conditions, and material properties such as corrosion resistance, microstructural features, the crystallographic orientation and the grain-boundary structure [ 2 ].…”