Abstract-Real time knowledge of total mass of gas and liquid in the annulus and geological properties of the reservoir is very useful in many active controllers, fault detection systems and safety applications in the well during petroleum exploration and production drilling. Sensors and instrumentation can not measure the total mass of gas and liquid in the well directly and they are computed by solving a series of nonlinear algebraic equations with measuring the choke pressure and the bottom-hole pressure. This paper presents different estimator algorithms for estimation of the annular mass of gas and liquid, and production constants of gas and liquid from the reservoir into the well during Under Balanced Drilling. The results show that all estimators are capable of identifying the production constants of gas and liquid from the reservoir into the well, while the Lyapunov based adaptive observer gives the best performance comparing with other methods when there is a significant amount of noise.
Abstract:This paper presents a constrained finite horizon model predictive control (MPC) scheme for regulation of the annular pressure in a well during managed pressure drilling from a floating vessel subject to heave motion. In addition the robustness of a controller to deal with heave disturbances despite uncertainties in the friction factor and bulk modulus is investigated. The stochastic model describing sea waves in the North Sea is used to simulate the heave disturbances. The results show that the closed-loop simulation without disturbance has a fast regulation response, without any overshoot, and is better than a proportional-integralderivative (PID) controller. The constrained MPC for managed pressure drilling shows further improved disturbance rejection capabilities with measured or predicted heave disturbance. Monte Carlo simulations show that the constrained MPC has a good performance to regulate set point and attenuate the effect of heave disturbance in case of significant uncertainties in the well parameter values.
Dealing with torsional vibrations and stick–slip oscillations of a drill string system is a challenging engineering task in the oil drilling process because of the harmful and costly consequences of such vibrations. In this article, the drill string system is modeled using a lumped-parameter model with four degrees of freedom, and the bit–rock contact is represented by a nonlinear function of a bit velocity. Also, tracking the desired velocity of a drill string system with known constant input delay is addressed in the presence of external disturbance and parameter uncertainties by applying the Smith predictor–based sliding mode control method. The performance of the smith predictor–based sliding mode control with input delay and disturbance in tracking the desired velocity and controlling the stick–slip oscillations is compared with the sliding mode control with/without input delay. The system output’s sensitivity to the delay parameter is also investigated, indicating how the bit velocity changes concerning the delay parameter. The proper choice of adaptation gain is determinative in the performance of the controller, and its impact is investigated. Moreover, the robustness of the smith predictor–based sliding mode control is shown by changing the weight on the bit parameter. Simulation results demonstrate the effectiveness of the proposed method.
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