Esmaeil Jahanshahi

Simplified Dynamical Models for Control of Severe Slugging in Multiphase Risers

Abstract In order to prevent the severe slugging flow regime in multiphase transport pipelines, active feedback control is the recommended solution. Instead of elaborated models such as CFD and OLGA ® models, a simple dynamical model with few state variables is required in a model-based control system. We propose a new simplified dynamical model for severe slugging flow in pipeline-riser systems. The proposed model, together with five other simplified models existing in the literature, is compared to the results from the OLGA ® simulator. The proposed model could be able to maintain the main dynamics of the severe slugging flow regime.

Controllability analysis of severe slugging in well-pipeline-riser systems

Abstract Active control of the production choke valve is the recommended solution to prevent severe slugging flow conditions at offshore oilfields. The focus of this work is to find the structure of a simple, yet robust anti-slug control system. In order to find suitable control variables for stabilization, a controllability analysis of the system with different available measurements or different combinations of them was performed. Moreover, for including robustness and performance requirements at the same time, the controllability analysis was extended to a mixed sensitivity ℋ ∞ optimization problem. Two case studies were considered; first, the controllability analysis was performed on a pipeline-rise system using a 4-state model for comparing the results to the previous works. Next, using a 6-state model, the results were extended to a more general well-pipeline-riser system. The controllability results were in accordance with the practical experience in anti-slug control.

Control Structure Design for Stabilizing Unstable Gas-Lift Oil Wells

Active control of the production choke valve is the recommended solution to prevent casing-heading instability in gas-lifted oil wells. Focus of this work is to find a simple yet robust control structure for stabilization of the system. In order to find suitable control variables, a controllability analysis of the system with different candidate control variables and two alternative manipulated variables was performed. Moreover, to include robustness and performance requirements at the same time, the controllability analysis was extended to a mixed sensitivity H1 optimization problem. A control structure using only the available top- side pressure measurements was found to be effective to stabilize this system.

Anti-slug control experiments using nonlinear observers

To prevent slug-flow on offshore oil production units, controlling a subsea pressure is the recommended solution. However, the subsea pressure is not often available as a measurement. The top-side pressure is usually measured but it is difficult to use for stabilizing control, because of its Right Half-Plane zero dynamics combined with nonlinearity. We have used the top-side pressure as measurement for different observers to estimate state variables of the system, and then used the estimated states for control. This scheme was tested in experiments using three types of observers. A simple Luenberger observer with a large gain was found to be more robust than the standard Unscented Kalman Filter (UKF). We modified the UKF to a Fast UKF for time-scale separation of the closed-loop system. The resulting observer was robust, also less sensitive to measurement noise compared to the simple Luenberger observer when measuring the top-side pressure. Surprisingly, the nonlinear observers were not able to work in closed-loop when the subsea pressure was used as the measurement. On the other hand, a linear observer worked very well for this case with a larger operating range compared to that of the top-side pressure.

Simplified Dynamic Models for Control of Riser Slugging in Offshore Oil Production

Summary Elaborated models, such as those used for simulation purposes [e.g., in the OLGA® simulator (Bendiksen et al. 1991)], cannot be used for model-based control design because these models use too many state variables and the model equations are not usually available for the user. The focus of this paper is on deriving simple, dynamical models with few state variables that capture the essential dynamic behavior for control. We propose a new simplified dynamic model for severe-slugging flow in pipeline/riser systems. The proposed model, together with five other simplified models found in the literature, are compared with results from the OLGA simulator. The new model can be extended to other cases, and we consider also a well/ pipeline/riser system. The proposed simple models are able to represent the main dynamics of severe-slugging flow and compare well with experiments and OLGA simulations.

A Comparison between Internal Model Control, Optimal PIDF and Robust Controllers for Unstable Flow in Risers

Abstract Anti-slug control of multiphase risers involves stabilizing an open-loop unstable operating point. PID control is the preferred choice in the industry, but appropriate tuning is required for robustness. In this paper, we define PIDF as a PID with a low-pass filter on its derivative action where the low-pass filter is crucial for the dynamics. We compared a new PIDF tuning based on Internal Model Control (IMC), together with two other tunings from the literature, with an optimal PIDF controller. The optimal PIDF tuning was found by minimizing a performance cost function while satisfying robustness requirements (input usage and complementary sensitivity peak). Next, we considered two types of robust ℋ∞ controller (mixed-sensitivity and loop-shaping). We compared the controllers based on their pareto-optimality, and we tested the controllers experimentally. We found that the new IMC-PIDF controllers is the closest to the optimal PIDF controller, but the robustness can be further improved by ℋ loop-shaping.

Nonlinear model-based control of two-phase flow in risers by feedback linearization

Abstract Active control of the production choke valve is the recommended solution to prevent severe slugging flow conditions at offshore oilfields. The slugging flow constitutes an unstable and highly nonlinear system; the gain of the system changes drastically for different operating points. Although PI and PID controllers are the most widely used controllers in the industry, they need to be re-tuned for different operating conditions. The focus of this paper is to design a model-based nonlinear controller in order to counteract nonlinearities of the system. Feedback linearization based on the riser-base pressure and the topside pressure was used for the control design. Stability and convergence of the closed-loop system was verified in theory as well as by experiments on a test rig.

Comparison between nonlinear model-based controllers and gain-scheduling Internal Model Control based on identified model

Instability and inverse response behaviour make anti-slug control at offshore oil-fields an interesting control problem where a robust solution considering the nonlinearity of the system is required. We tested three control solutions by experiments in this paper. First, we used state-feedback with state estimation by a nonlinear high-gain observer. Secondly, we applied feedback linearization with measured outputs. Finally, we designed gain-scheduling IMC (Internal Model Control) based on linear models identified from closed-loop step test. We compared these three solutions in terms of robustness and their range of operation. The high-gain observer was only applicable by using the top-side pressure measurement in a limited range; it was not stable when using the the subsea pressure measurement in closed loop. The IMC method was more robust against time-delay in the subsea pressure measurement compared to the feedback linearizing controller.

Closed-loop model identification and PID/PI tuning for robust anti-slug control

Abstract Active control of the production choke valve is the recommended solution to prevent severe slugging flow at offshore oilfields. This requires operation in an open-loop unstable operating point. It is possible to use PI or PID controllers which are the preferred choice in the industry, but they need to be tuned appropriately for robustness against plant changes and large inflow disturbances. The focus of this paper is on finding tuning rules based on model identification from a closed-loop step test. We perform an IMC (Internal Model Control) design based on the identified model, and from this we obtain PID and PI tuning parameters. In addition, we find simple PI tuning rules for the whole operation range of the system considering the nonlinearity of the static gain. The proposed model identification and tuning rules show applicability and robustness in experiments on a test rigs as well as in simulations using the OLGA simulator.

Control of the Steady-State Gradient of an Ammonia Reactor using Transient Measurements

Abstract This paper presents the application of a steady-state real-time optimization strategy using transient measurements to an ammonia synthesis reactor case. We apply a new method for estimating the steady-state gradient of the cost function based on linearizing a dynamic model at the present operating point. The gradient is controlled to zero using a standard feedback controller, for example, a PI-controller. The applied method is able to adjust fast to the new optimal operation in case of disturbances. The advantage compared to standard steady-state real-time optimization is that it reaches the optimum much faster and without the need to wait for steady-state to update the model. It is significantly faster than classical extremum-seeking control and does not require the measurement of the cost function and additional process excitation. Compared to self-optimizing control, it allows the process to achieve the true optimum.