Drilling in challenging conditions require precise control over hydrodynamic parameters
for safer and efficient operation in oil and gas industries. Automated managed
pressure drilling (MPD) is one of such drilling solution which helps to maintain operational
parameters effectively over conventional drilling technique. The main goal
is to maintain bottomhole pressure between reservoir formation pressure and fracture
pressure with kick mitigation ability. Real life MPD system has to confront nonlinearity
induced by drilling fluid rheology and flow parameters. To obtain a better
understanding of this operation, a lab scale experimental setup has been developed.
Reynolds number and pressure drop per unit length were considered to obtain hydrodynamic
similarity. A vertical concentric pipe arrangement has been used to represent
the drill string and annular casing region. A linearized gain switching proportional integral
(PI) controller and a nonlinear model predictive controller (NMPC) have been
developed to automate the control operation in the experimental setup. A linearizer
has been designed to address the choke nonlinearity. Based on the flow and pressure
criteria, a gain switching PI controller has been developed which is able to control
pressure and flow conditions during pipe extension, pump failure and influx attenuation
cases. On the other hand, a nonlinear Hammerstein-Weiner model has been
developed which assists in bottomhole pressure estimation using pump flow rate and
choke opening. The identified model has been integrated with a NMPC algorithm
to achieve effective control within predefined pressure and flow constraints. Lastly, a
performance comparison has been provided between the linearized gain switching PI
controller and NMPC controller
