Short-Term Production Optimization for Electric Submersible Pump Lifted Oil Field With Parametric Uncertainty

Abstract

This paper uses a scenario-based optimization method to address the Daily Production Optimization from an Electric Submersible Pump lifted oil field under the presence of uncertainty. The primary contribution of this work lies in addressing the presence of uncertainty in short-term production optimization of the oil industry, a significant aspect that is frequently overlooked. It has been shown that using the dynamic model of the plant in the optimization problem is too computationally expensive, even in a deterministic case. Therefore, the steady-state model of the system has been used in a robust optimization framework. The necessity of considering uncertainty in the optimization problem and the promising results of the proposed robust method is compared with the deterministic optimization counterpart. An additional novelty of this study involves the utilization of a scenario-based optimization framework to explore various forms of uncertainty, including uncertainty in well flow parameters and oil price. It has been shown that the uncertainty in oil price does not affect the optimal solution during normal operation, at least in short-term optimization such as Daily Production Optimization. On the contrary, the uncertainty in the well parameters is important to be considered since well flow parameters influence the optimizer in preferring one well over the other. Consequently, the economic objective for the lucrative business of the oil industry will be translated into production maximization, and the optimizer's task involves allocating the total production capacity among the different wells to maximize the proportion of the oil to water in the produced fluid.

Sensorless control of submersible permanent magnet synchronous motor under long-line cable model

“…At present, domestic and foreign research on sensorless control methods are mainly divided into two categories: One is based on the convex polarity of the permanent magnet synchronous motor to achieve the extraction of rotor position and speed information, which can be divided into high-frequency rotating voltage injection [3] and high-frequency pulsating voltage injection [4] according to the difference of the injected coordinate system. The other category is to process the magnetic chain or reverse potential with the help of the mathematical model of the motor, and such methods have better estimation effect on the high-speed sections, including the magnetic chain estimation method, the model reference adaptive method [5] , the sliding mode observer method [6] , the extended Kalman filter method [7] , etc.…”