Modeling of Intelligent Control System for Liquid Level in Multi-Stage Separator Arrangement in Oil and Natural Gas Industry

Abstract

           The control of liquid level in the oil and natural gas industry is a very important subject since it affects the shutdown of the sale and transport of these sensitive products. In the oil separator, because of the mixing of the accompanied water, oil and accompanied gas, therefore, the level of oil must not be exceed a such rang as well as not to be less than a proper level. For this reason, this work is focused in modeling a Simulink and mathematical model for multi-stage oil separator structure and applies the intelligent schemes in order to control the angles of most inlet and outlet valves at the same time. This technique will improve the behavior of the level response in terms of the rise time, maximum present overshoot, settling time and steady state error. Also, a comparison has been implemented between (fuzzy logic, Nonlinear Autoregressive-Moving Average (NARMA-L2)) against conventional control methods such as PID control. Faster response for most oil separator can be achieved as it appears from the simulation results. Also, multi input variable that affect the system outputs can be treated accurately by a proper rule base adjusting in fuzzy logic or adequate training data in the NARMA-L2. The effective factors of fuzzy logic and NARMA-L2 had been optimized and studied where the simulation results had demonstrated that there are special magnitudes for each new application