Multi-objective Optimization Analysis of Ultra-deep Water Drilling Riser under Harsh Environmental Conditions

Yang, H. and Xiao, F. (2021) Multi-objective Optimization Analysis of Ultra-deep Water Drilling Riser under Harsh Environmental Conditions. In: 31st International Ocean and Polar Engineering Conference, Rhodes, Greece, 20-25 Jun 2021,

[img] Text
252482.pdf - Accepted Version
Restricted to Repository staff only


Publisher's URL:


Drilling systems have become an integral part of oil and gas exploration and production particularly in ultra-deep waters. With increasing drilling depth, heavy weight of the riser system and high-top tension requirement become the potential concern. The study mainly focusses on the optimization of buoyancy settings to achieve better operating performance and lighter weight. The multi-objective optimization of operability envelope is a complicated problem due to the presence of discrete design variables and complex analysis process (emergency disconnection, recoil analysis, drift-off) with different FEA models. In this work, an efficient approach for the multi-objective optimization of operability is proposed for the drilling riser in ultra-deep water. The two main contradictory objective functions include minimize the dry weight of drilling riser system and maximize the area of operability envelopes. Each of these conditions or operational scenarios imposes varying design limits for the riser stack-up. The main riser characteristics related to operational and environmental conditions will be considered. According to suitable criteria and requirements, the operational working envelopes will be defined. The economic cost (weight) and drilling riser system performance (operability window) are considered to obtain the better operational performance with Non-dominated sorting genetic algorithm II (NSGA-II). The use of a RBF metamodel approach could solve two critical problems in multi-objective optimization design, including timeconsuming computation and non-convergent problem during iterative loops.

Item Type:Conference Proceedings
Glasgow Author(s) Enlighten ID:Yang, Dr Hezhen
Authors: Yang, H., and Xiao, F.
College/School:College of Science and Engineering > School of Engineering

University Staff: Request a correction | Enlighten Editors: Update this record