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 compu- tational tool for the synthesis and optimization of submarine pipeline routes, using computa- tional tools based in Evolutionary Algorithms. In such optimization procedures, each candidate route is randomly generated and is evaluat- ed, 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 con- sidered in the selection of a route, such as total pipeline length; geophysical and geotech- nical 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 hydro- static and environmental loadings; some of these aspects are dealt with by following recom- mendations 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 as- sess 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.