Synthesis and Optimization of Submarine Pipeline Routes

Abstract

Traditionally, the selection of a pipeline route for offshore applications has been manually performed by the engineer, by a quick inspection of the seabottom bathymetry and the available information regarding obstacles. Eventually the evaluation of a given route could be performed using analysis tools, but in any case the process is highly dependent on the expertise of the engineer. In this context, this work describes the development of a computational tool for the synthesis and optimization of submarine pipeline routes, using computational tools based in Evolutionary Algorithms. In such optimization procedures, each candidate route is randomly generated and is evaluated, in order to determine its "fitness", in terms of several criteria that are incorporated in an objective function. Such function takes into account all relevant aspects that should be considered in the selection of a route, such as total pipeline length; geophysical and geotechnical data obtained from the bathymetry and sonography, including the definition of obstacles and regions that should be avoided; number, length and location of free spans to be mitigated along the routes. Other aspects depend on the structural behavior of the pipe, under hydrostatic and environmental loadings; some of these aspects are dealt with by following recommendations established in the DNV RP-F105 and RP-F109 codes, related respectively to the on-bottom stability and free spans. This work describes the implementation of the optimization tool, beginning with the assembly of the objective function and the definition of the problem constraints, and proceeding with the association of this function and constraints in the framework of the implementation of a Genetic Algorithm-GA. Case studies are presented to illustrate the use of this optimization tool. It is expected that the application of such tool may reduce the design time needed to assess an optimal pipeline route, while reducing computational overheads and providing more accurate results (avoiding mistakes with route interpretation), ultimately minimizing costs with respect to submarine pipeline design and installation.

Parallel Hyperheuristic Algorithm for the Design of Pipeline Networks

“…The introduction of a nature-inspired approach to these studies has proven to increase profits and efficiency. For example, Baioco et al described the development of a computational tool for the synthesis and optimization of subsea pipeline routes using evolutionary algorithms. Besides, de Lucena et al applied genetic algorithms (GA) to improve their analysis for offshore scenarios.…”

Optimization of Submarine Pipeline Routes Considering Slope Stability

“…This considers relevant aspects in a global optimization stage, including total pipeline length, radius of curvature, declivity and obstacles. More recently, related studies of those structural criteria (OBS and VIV-induced fatigue) integrated in a new objective function that considers the production optimization, associated to multiphase fluid flow pressure drop, were presented in [10]. Fatigue induced by vortex induced vibrations (VIV) on free spanss was considered in [8], obeying the screening criteria proposed in the DNV-RP-F105 code [9].…”