NMPC Integrated with Optimization Layer in Offshore Production

Abstract

In offshore oil production, the occurrence of oscillatory flow regime that causes instabilities is very common, resulting in production losses, occasioned by shutdown, and environmental fine due to the violation of quality requirements. In this work, we evaluate the capability of a nonlinear model predictive controller (NMPC) integrated with an optimization layer to maximize production, minimize energy consumption and mitigate impacts caused by slug flow regimes present in offshore processes. The objective function used in the optimization problem is formulated with the oil and gas production as profit and energy consumption as cost. The degree of freedom of the optimization problem are the topside pressure in the processing plant and the gas-lift injection flow rate in each well. The constraints are the BSW and TOG specifications, capacity of the compression unit and the limits of gas-lift injection, in each well and total flow. The simulated offshore production system encompasses the subsea well, the flowline, the riser, and the topside platform. The subsea part, with four wells, was modeled in OLGA simulator and integrated with a simulated platform in EMSO simulator. The control problem was formulated with nine manipulated variable: gas-lift injection and opening choke valve in each well, and interface level in the separator drum. The results show that the controller can reject the slug disturbances, keeping the BSW and TOG inside the limits and driving the process to the setpoints coming from the optimization layer.