Online optimization for a plunger lift process in shale gas wells

This paper presents a method for efficient optimization of a plunger lift process in shale gas wells. Plunger lift is a cyclic process consisting binary decision as well as continuous and discrete state variables. The time-series data comprising of surface measurements are converted into cycle-wise process-relevant performance outputs, while the binary manipulated variable is transformed into continuous threshold values. These transformed variables are used to develop a reduced order cycle-to-cycle model and corresponding receding horizon optimization problem that maximizes daily production while meeting operational constraints. The efficacy of the proposed algorithm is demonstrated on a simulated plunger lift process.