An essential part of an automated managed-pressure-drilling (MPD) control system is the hydraulics model, which, in many cases, is the limiting factor for achievable accuracy of the system. Much effort, therefore, has been put into developing advanced hydraulics models that capture all aspects of the drilling-fluid hydraulics. However, a main drawback is the resulting complexity of these models, which require expert knowledge to set up and calibrate, making it a high-end solution.In practice, much of the complexity does not contribute to improvement of the overall accuracy of the pressure estimate simply because conditions in the well change during MPD operations and there are not enough measurements to keep all of the parameters of an advanced model calibrated.We will demonstrate that a simplified hydraulics model based on basic fluid dynamics is able to capture the dominating hydraulics of an MPD system. Furthermore, we will demonstrate that, by applying algorithms for online parameter estimation similar to those used in advanced control systems in the automotive and aerospace industry, the model can be calibrated automatically by use of existing measurements to achieve a level of accuracy comparable with that of a calibrated advanced hydraulics model. The results are demonstrated using field data from MPD operations in the North Sea and dedicated experiments obtained at a full-scale drilling rig in Stavanger.

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In this paper a reduced order observer that adapts to unknown friction and density, and estimates the bottomhole pressure in a well during drilling, is presented. The design is based on a newly developed third order nonlinear model with a nonlinear output equation containing a product between an unknown parameter and unmeasured state. Based on a Lyapunov approach the pressure estimate is shown to converge to the true pressure under reasonable conditions. Application of the observer to real data from a North Sea oil well demonstrates promising behaviour.

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