Simulation Study of Reentry Dynamics of a Deep-Water Drilling Riser System Based on Model Predictive Control

doi:10.16183/j.cnki.jsjtu.2022.235

Abstract

Abstract:

A marine drilling riser at normal operation condition is required to disconnect the lower marine riser package (LMRP) and blow-out preventer (BOP) in case of severe weather. When the weather gets fine, it must reconnect the LMRP and the BOP. This process is called riser reentry. Marine drilling operations have been driven into extreme deep-waters characterized by severe weather which inevitably leads to a much higher incidence of disconnection. In addition, it requires to accomplish the reentry in a fast way owing to the capricious ocean environment. This study tries to develop a novel reentry control system based on model predictive control (MPC). First, the transverse governing equation of the hanging-off riser system with an end-mass is established based on the modified Hamilton’s principle. The optimization function and constraints in MPC are designed by use of the riser prediction model and the target location. A nonlinear disturbance observer is established for compensation of the model uncertainties and ocean environment disturbances. Finally, simulations are conducted after introducing the dynamic position system (DPS). The riser dynamics employing MPC are compared with that when adopting proportional-integral-derivative (PID) controller. It has found that the drilling riser system based on MPC has a higher response speed, which can complete the reentry process in a faster and more stable manner. It can handle the hydrodynamic force model uncertainties well and has a good robustness for current velocity disturbances. As the flexibility of the riser system is notably enhanced with the significant increase of aspect ratio, the higher-order mode of the flexible hanging-off riser can be triggered in the fast reentry process subjected to the excitations of the mother vessel and ocean environment.

Key words: drilling riser, reentry dynamics, Hamilton principle, Galerkin method, model predictive control (MPC)

CLC Number:

{P756}

ZHANG Chenyu, MENG Shuai. Simulation Study of Reentry Dynamics of a Deep-Water Drilling Riser System Based on Model Predictive Control[J]. Journal of Shanghai Jiao Tong University, 2023, 57(11): 1389-1399.

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