Decision Support System for Optimizing GOSP Operation

Abstract

It is very important to consider all the units and operating parameters of the individual units in the gas-oil-separation-plant (GOSP) optimization process. For many processes, optimum parameters for the individual units are difficult to implement in the real operation especially for GOSP in which all the units are connected to each other and establishing the optimum control condition for the individual unit will be difficult to implement. The objective of this project is to develop a generic integrated framework for maximizing the oil recovery by optimizing the gas-oil-separation-plant (GOSP) parameters. A typical Saudi Aramco GOSP plant has been considered as the candidate for the project. In this project, a model consists of multi-stage separators, and stabilization units along with the stock tank to mimic the oil train. Amongst the various parameters, only the controllable parameters such as pressure, and temperature were considered as optimization parameters to achieve the maximum oil recovery. The GOSP plant model was developed using OmegaLand software. To evaluate the effect of the various parameters many runs were initiated for generating the data. A model is developed by applying artificial intelligence techniques to the data generated by the simulator. The model served as a tool for optimizing the controllable parameter to achieve the maximum oil recovery which is the ultimate goal of the GOSP plant. The generic integrated framework serves as a guide to set the optimum operating condition for maximizing the oil recovery. The optimized parameters can be adjusted by Operation Decision Support System (ODSS).