Improving the Fatigue Performance of Welded Tubular Connections via Flared and Thickened Pipe Ends

Fatigue is a primary challenge in the design of steel catenary risers (SCRs) and different measures and methods are utilized to mitigate it. Traditional upset ends and steel lazy wave risers (SLWRs) are such methods to mitigate fatigue. SLWRs were first used in 2009 on the Espirito Santo floating, production, storage, and offloading (FPSO) vessel of Shell Company's Parque das Conchas (BC-10) project offshore Brazil. SLWRs have been used increasingly since then and gained popularity especially in recent years. A novel patented tubular connection assembly referred to as Flared Thickened Ends (FTEs) improves the fatigue life of SCRs and welded connections in general. This novel assembly has many advantages. It overcomes the thickness limitation of welding traditional upset ends and reduces offshore welding time, cost, and risk. When FTEs are used in simple SCRs, they render simple SCRs a robustly viable alternative at significantly lower cost, shorter schedule, and with many additional advantages as compared to SLWRs. Of the many advantages, simple SCRs are more straightforward to configure, analyze, design, and install using varied installation methods and vessels. Simple SCRs use less materials and offer better long-term integrity, especially for insulated SCRs. In addition, they have a smaller footprint and are less prone to clashing than SLWRs.

Steel Lazy Wave Riser Optimization Using Artificial Neural Networks and Genetic Algorithm

Over the past few years, a number of deepwater projects that use steel lazy wave risers have been commissioned or are under development. Steel lazy wave risers have an advantage over steel catenary risers as they offer flexibility of use with a floater having severe motion such as FPSO. They also impart lower loads at the interface with the floater compared to a traditional steel catenary riser, and hence can be used in deeper waters. Therefore, design of steel lazy wave risers has gained importance over the years as exploration of oil happens in ever deeper waters. In this paper, artificial neural networks and genetic algorithm are used to automatically generate a steel lazy wave riser design. A dataset of optimized designs of steel lazy wave risers for various inputs such as water depth, pipe OD, wall thickness etc. are generated using genetic algorithm. This dataset is used to train a neural network to automatically output a steel lazy wave riser design. The SLWR configuration that is automatically generated can be used as a starting point for conceptual and pre-FEED studies and help engineers come up with an initial SLWR design capturing the basic requirements without going through rigorous analyses. It has potential for cost savings and meeting schedule demands of fast paced projects as it will speed up the steel lazy wave risers’ design.

Steel Lazy Wave Riser Optimization Using Artificial Intelligence Tool

Use of steel lazy wave risers has increased as oil and gas developments are happening in deeper waters or in parts of the world with no pipeline infrastructure. These developments utilize FPSO’s with offloading capabilities necessary for these developments. However, due to more severe motions compared to other floating platforms, traditional catenary form of risers are unsuitable for such developments and this is the reason Steel lazy wave risers (SLWR) are required. SLWRs have shown to have better strength and fatigue performance and lower tensions at the hang-off compared to steel catenary risers. A suitable Lazy-Wave form of the catenary riser is achieved by targeted placement of a custom configured buoyancy section. The strength and fatigue performance of steel lazy wave risers are governed by parameters such as length to start of this buoyancy section, length of the buoyancy section, hang-off angle and the buoyancy factor. Achieving these key performance drivers for a SLWR takes several iterations throughout the design process. In this paper, genetic algorithm which is an artificial intelligence optimization tool has been used to automate the generation of an optimized configuration of a steel lazy wave riser. This will enable the riser designer to speed up the riser design process to achieve the best location, coverage and size of the buoyancy section. The results that the genetic algorithm routine produces is compared to a parametric study of steel lazy wave risers varying the key performance drivers. The parametric analysis uses a regular wave time domain analysis and captures trends of change in strength and fatigue performance with change in steel lazy wave parameters.

Improved Empirical Formulation for Seabed Trench Profile at Touchdown Zone and its Effects on Fatigue of Steel Catenary Risers

Steel catenary risers (SCRs) offer a cost-effective solution to deep water deployments. Hanging from a floater, an SCR is commonly subjected to large tension at hangoff location and large bending moments at touchdown zone (TDZ) which lead to fatigue damage. Field observations showed that the depth of a seabed trench might reach to a depth of four to five times of the diameter of a riser, however, a flat seabed was often assumed for the modeling of SCRs which surely affects simulations of fatigue behavior of the SCR at the touchdown zone. Studies on the effects of seabed trench on TDZ fatigue conducted by different researchers led to contradictory conclusions, i.e., some studies suggested that considering seabed trench reduced fatigue damage at TDZ of SCRs, while, others drew opposing conclusions. The contradiction may be explained by factors including inappropriate trench profiles and different sea states assumed in the analysis model. An iterative procedure initially developed by Wang and Low and further improved in the present work was used to estimate the position and the length of a seabed trench beneath an SCR and, then, an improved empirical formulation was generated to approximate the profile of the seabed trench. Additionally, dynamic simulations were conducted to study the effects of seabed trench on fatigue behaviors of SCRs encountering variant directional waves.