Control and optimization frameworks for managed pressure drilling process

Managed Pressure Drilling (MPD) process regulates the pressure by means of a control framework and equipments within prescribed limits. As the conventional drilling is risk prone and involves constant monitoring of the system parameters, MPD offers advantages such as improved Rate Of Penetration (ROP), improved safety and higher overall operational efficiency.;This thesis develops an uncertain control-oriented system model for the MPD framework, and proposes both intelligent and robust control frameworks in order to improve the MPD system performance. The process model developed must satisfactorily represent the physical dynamics of the MPD system. The dynamics of an oil well and associated processes are used to obtain models that are suitable for the process optimization. Intelligent and robust control frameworks have been investigated. The bore is sealed and the pressure is regulated using a choke and two pumps, the main mud pump and the back pressure pump. The developed control frameworks uses two control inputs i.e., the main mud pump and the Differential pressure between choke and back pressure pump. Intelligent control is suitable to nonlinear systems such as the MPD process where it is difficult to represent the system dynamics using only system equations. Intelligent control framework has been developed and tested for the MPD application yielding satisfactorily results. Drilling operations involve unexpected disturbances and uncertain parameters. The proposed robust optimization framework design offers improved disturbance rejection as well as guaranteed stability and performance for a family of plants within the design space, with a bounded uncertainty description. Results of both Intelligent and Robust Frameworks are listed, studied and a comparison is made.