Intelligent control of compact multiphase separation system (CMSS)

Performance of compact separators depends on implementation of stable and robust control strategies that are suited for specific applications. In this investigation, an intelligent control system has been developed for Compact Multiphase Separation System (CMSS(c)) which consists of integrated configurations of three compact separators, namely, Gas-Liquid Cylindrical Cyclone (GLCC(c)), Liquid-Liquid Cylindrical Cyclone (LLCC(c)) and Liquid-Liquid Hydrocyclone (LLHC).; In mature oil fields, water handling poses a huge problem. Thus water knock out at the earliest stage helps in significant cost savings during handling, separation and transportation of oil. The specific objective of this CMSS (c) configuration is to knock out free water from the upstream fluids.; A new dual differential pressure sensor system has been implemented and tested for GLCC(c) to eliminate the error in liquid level measurement due to change in watercut. A new watercut based control system using downstream pump, speed control has been designed and tested for the LLCC(c) system. A new cascaded control strategy for change in set-point of differential pressure ratio using underflow quality from hydrocyclone has been designed and developed. A novel fuzzy logic control system has been designed and tested for the cascaded control system for change in set-point of differential pressure ratio in LLHC. Dynamic models have been developed for each of the above mentioned control systems for design of stable PID parameters and these models are used in the development of a dynamic simulation platform (DSP) in Matlab/Simulink(TM) for predicting the transient performance of the integrated system for various input conditions. Steady state mechanistic models of individual devices are integrated to the Matlab/Simulink(TM) platform using look up tables to predict the overall response of the CMSS (c) for different scenarios. This novel intelligent control strategy integrating dynamic control system models, steady state mechanistic models through look-up tables, and fuzzy logic control based on human intelligence is ideal for process control industry.; Comparison of simulation and experimental results shows that the control system simulator is capable of representing the real physical system and can be used to validate the controller design. Fuzzy logic controller has been successfully implemented and tested. Experimental results show a similar trend as the dynamic simulator results for the various input conditions and scenarios. The results from theoretical and experimental studies have shown that Free Water Knock Out (FWKO) CMSS(c) system can be readily deployed in the field using the control system strategies designed, implemented and tested in this study. (Abstract shortened by UMI.)...