Holistic flow and pressure control for underbalanced drilling operations
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This text is targeted towards engineers and researchers working with drilling automation. Though the selected application domain is underbalanced drilling (UBD) the results are applicable to managed pressure drilling (MPD) with or without a two-phase fluid. The control goals are related to pressure and flow management, or the hydraulic model, and not to areas such as geo-steering, automatic pipe handling, weight on bit (WOB), or drill-string vibrations. The main contributions are new results on multivariable control of flow and pressure during UBD. Simple linear models and a more complex non-linear model are used to predict the system behaviour during drilling operations. Both standard model predictive control (MPC) and non-linear model predictive control (NMPC) are used to generate control inputs. The benefits and challenges of both approaches, together with the system performance, are discussed. The main contributions are in the domain application, rather than in control methodology. A main goal of the thesis is to look beyond the control of single sub-systems to a more holistic perspective; where the objectives and constraints of the well and the processing equipment at the surface are considered as one system. This approach will ensure that one part of the system does not take actions which are ill-suited for other parts of the system, and that the system may use more degrees of freedom for control. Manipulated variables range from pump liquid volume rate, choke opening, separator pressure and level set-points, to rate of penetration (ROP); while controlled variables include multiple well pressures, choke pressure, hole cleaning, separator pressure and levels, separator gas flow, choke flow, and the choke operating region. Constraints are included on well stability, production rate, pump liquid rate, separator levels and pressures, choke flow rates, choke pressure, pump pressure, hole cleaning, and gas production. The control problem is configured and solved using industrial MPC software already running in the field. Data is transferred using established industrial standards for communication between process control systems and for model exchange. The control system is implemented using a hierarchical approach, with local stabilization of some of the underlying states. The necessary steps to move towards a full industrial solution are briefly discussed towards the end of the thesis. An MPC solution is presented for control of both well conditions and the topside separation system, using matrices of simple step response models. The models are simple, fast, and easy to understand. The performance is shown to be sufficient when evaluated for several scenarios, including connections and drilling into new production zones. The simple models have limited validity, and will have reduced performance away from the linearization point. However, due to the slow time constants of the operation, it should often be possible to keep the models up to date. For the situations where linear models may not be good enough, an NMPC controller which use a reduced drift-flux model (RDFM) is developed. While the NMPC and the non-linear model are far more complex, harder to understand, and the problem now takes much longer time to solve; it gives back in terms of better predictive capabilities, it is valid over a much larger operating range, and may require less model identification in the field. We also hope that this thesis can serve as an introduction to UBD, with focus on the control challenges and what can be achieved using automated control.