In the North Sea, carcass failures have over the last years been the largest failure category for flexible pipes, causing multiple riser replacements [1]. The carcass failures could be split into two groups: axial tear-off and collapse. In order to determine the resistance to collapse, a 3D analysis model has been built using the explicit finite element (FE) program LS-Dyna. In addition, the LS-Dyna results were compared with a simplified 2D FE approach, using the non-linear implicit solver MARC. The 3D model allows for more complex sensitivities, such as curved pipe and carcass tension. The FE analyses were based upon measured carcass profile geometries and material data from hardness measurements at several positions along the carcass profile, including effects of strain hardening during manufacturing. Three different carcass profiles of three different risers were analysed. The study includes sensitivities on straight and curved pipe sections, axial preloaded carcass, carcass ovality, radial gap between carcass and pressure sheets and pressure increase velocity. Collapse resistance of axial strained carcass and bent pipe is not well documented and this paper will highlight some of the observed effects. The results from the FE analyses showed good correlation between the vendor data [2] both in shape of the buckling mode and capacity.

Recent failures of multi-layer pressure sheath risers have shown that the carcass may fail in the top termination due to excessive axial loads. This is a new failure mode for flexible risers, recently presented by the authors in more general terms. The present paper explains details of the established load model and the validation against mid-scale tests, risers failed during operation, and operating risers close to failure by this new mode. The key driver in the model is the temperature contraction of pressure sheath layers. Also influenced by changes in polymer properties over the operational history, temperature and time is explained. Other contributing factors in the load model are gravity-component and bore pressure. The prediction model for the carcass loads are developed during Statoils investigation in 2011–12. The model is regarded representative for 20% of the most exposed risers. Several of the input parameters are uncertain and a Monte Carlo simulation approach is selected to study the variability and predict the probability of failure, given that radial contact pressure is sufficiently low. The approach adopted in the model may be applicable to other risers where polymers and steel components act together, and in such circumstances act as a guide for alternative model developments.

Recent incidents on the Norwegian shelf showed that the inner steel structure of a flexible riser, the carcass, can experience extensive axial loading. These events resulted in carcass overload followed by a spin-out and tear-off at the carcass end, eventually followed by shutdown of production. The carcass axial tension capacity has previously not been considered a critical design issue for flexible pipes. The incidents resulted in an extensive program, initiated by Statoil, to find the root cause of the problem. Both analytical and computational efforts validated through extensive testing of carcass axial capacity has been conducted. Advanced finite element analysis was used to establish both the carcass capacity and also the carcass load level as a function of pitch length. The numerical results are compared and validated towards experimental data. The results form a basis to suggest operational policies to mitigate the risk of new failures.

During Statoil’s recent riser replacement project more than 30 used risers have been dissected onshore [1]. The main objective has been to reveal the root cause of carcass axial tearing failures. However, this also gave the opportunity to investigate details of other carcass damages, armor corrosion, annulus environment, external sheath breaches and polymer ageing as described in [5], [6] and [7]. This paper discusses some of the new knowledge obtained from the dissections. New tools and methods have been developed for carcass pitch measurements in order to determine axial movements, maximum load level seen by the carcass and determine the utilization against tearing. Offshore free-volume annulus testing and gas sampling is compared to liquid sampling and actual liquid found when dissecting, with significant deviations observed. Expected annulus environment is assessed in light of actual observed corrosion, with generally less corrosion than expected, however at some few selected areas significant corrosion attacks are found. Residual stresses and condition of polymer layers is quantified, with generally more degeneration and larger changes than anticipated before riser recovery.

This paper describes a live fatigue prediction methodology comprising measured motion response, maritime environment and process data for a Floating Production Storage and Offloading vessel (FPSO) moored in 700m water depth offshore Brazil. The measured data is utilized to improve traditional time domain dynamic analysis models, along with Machine Learning (ML) techniques. The resul of this is significant reduction in uncertainties, enabling live riser fatigue predictions and providing a basis for life extension and improved accuracy of riser and vessel response analysis. The methodology consists of using a combination of autonomous and online motion response sensors directly installed on the riser and interfacing FPSO structures. The measured environmental data, FPSO and riser response data are utilized in a ML environment to build more realistic riser response and fatigue prediction models. As FPSO heading is important for vessel dynamics, especially roll, and the vessel dynamics are a key factor in the riser dynamics at this field, the first focus was directed towards predicting vessel heading relative to swell. The heading model developed by ML showed good agreement and was used as a key tool in a traditional fatigue analysis using OrcaFlex & BFLEX. This analysis was based on historical sea states from the last two years (from EU's Copernicus Marine Environment Monitoring Service). The results show that the fatigue analysis from the design phase is conservative and life time extension is achievable. As the fully instrumented measurement campaign ended after 4 months, the work focused on utilizing all the captured data to give improved insight and develop both traditional simulation and ML-models. For future fatigue predictions based on the developed "fatigue counter", the ambition is to maintain good accuracy with less instrumentation. In the present phase, FPSO and riser response data from a 4-month campaign have been used to establish a ‘correlation’ between riser behavior, environmental data and FPSO heading and motion. Calibration of a traditional numerical model is performed using measurement data along with a direct ‘waves to fatigue’ prediction based on modern ML techniques. This illustrates enabling technologies based on combination of data streams from multiple data sources and superior data accessibility. The correlations established between different field data allow the development of a "live" riser fatigue model presenting results in online dashboards as an integrated part of the riser Integrity Management (IM) system. All relevant stakeholders are provided with necessary information to ensure safe and extended operation of critical elements of the FPSO. The paper illustrates the power and applicability of modern numerical techniques, made possible by combining data from 6 different streaming data sources, ranging from satellites to clamp-on motion sensors.