Online optimization for a plunger lift process in shale gas wells

- A computationally efficient algorithm for online optimization of plunger lift process in a shale gas well is presented.
- The natural gas production is maximized while meeting the requirements on the average plunger rise velocity.
- The binary manipulated variable is transformed into cycle-wise control threshold values and a reduced order model is identified between these transformed input variables and output objectives.
- The proposed algorithm is implementable for both batch and periodic systems, with varying cycle time.

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.