In the oil and gas industries, the gas-oil separation plant (GOSP) is operated at fixed operating conditions without considering the effect of ambient temperature (Ta) variations. Temperature is one of the parameters that can affect the GOSP process and its output. Ignoring the variation in the ambient temperature may lead to a loss in oil recovery and corresponding revenue. The separation process is highly affected by the variation of ambient temperature, where the ambient temperature varies greatly from summer to winter. As the plant is operated at a fixed operating condition that is not optimized results in low recovery of the GOSP output. The optimization process of high-pressure separator (HPS) and low-pressure separator (LPS) is required to compensate for the variation in ambient temperature, which leads to maximizing oil recovery and plant revenue. Thus, this study aims to develop an intelligent optimization system to improve the oil production of the Gas-Oil-Separation-Plant (GOSP) considering the variation in ambient temperature. Accordingly, the objective of this work is to provide an intelligent system for the determination of the best-operating set-points of the pressure (optimum pressure) for the high-pressure separator (HPS), low-pressure separator (LPS) at which maximum hydrocarbon liquid recovery can be obtained through the GOSP plant at a given ambient temperature. To achieve the objective of this study, a GOSP model was built by Petro-SIM process simulator software using a typical Saudi Aramco GOSP design. The data from the initial PVT analysis is considered as an input for the process simulator. Then the optimizer tools built in the Petro-SIM are activated to determine the optimum condition of HPS and LPS in an integrated fashion accounting for variation in ambient temperature for maximizing the liquid recovery. The results showed increases in ambient temperature result in a decrease in the oil recovery of the GOSP plant. The oil recovery appears to increase with an increase in HPS pressure reaching the maximum and then decreasing with a further increase in the HPS pressure. Similarly, the LPS pressure affects the oil recovery when LPS pressure increases oil recovery increases reaching the optimum point and then decreases with a further increase in LPS pressure. An intelligent system can be built based on an optimization process for determining the optimum condition of LPS and HPS for compensating variation in ambient temperature.

Summary Maximizing oil recovery of the gas-oil separation plant (GOSP) is intended to increase revenue in the oil and gas industry. The GOSP is an integral part of the petroleum industry, and it consists of multistage separators, a heater-treater, desalination, a stabilization column, and a stock tank of oil. It is conventional practice to operate the GOSP at fixed operating conditions without considering the effects of variation for different parameters such as ambient temperature, chemical composition, reboiler (60°C, 65°C, and 70°C), and stabilization (temperature and pressure). Optimizing the GOSP parameters can help to maximize the GOSP oil recovery and, as a result, increase the revenue and profit. This study aims to optimize operation parameters to maximize the oil recovery of the GOSP at which the maximum oil recovery can be obtained from the GOSP. To achieve the objective of this study, first, a GOSP model was built using Petro-SIM process simulator software for a typical Saudi Aramco GOSP. The input data for the process simulator were the data from the initial pressure/volume/temperature (PVT) analysis. Optimizer tools in Petro-SIM were used to estimate the optimal conditions of the GOSP for achieving maximum oil recovery. The results showed that the optimization of the GOSP parameters such as ambient temperature, high-pressure separator (HPS), low-pressure separator (LPS), reboiler temperature, and stabilization pressure and temperature have a significant effect on the GOSP oil recovery and lead to increased revenues. Adjusting the HPS and LPS pressures to the optimal values at each ambient temperature significantly improves the GOSP oil recovery and can generate extra revenue of more than USD 500 million for 3 months considering the typical climate condition and GOSP (50,000 B/D capacity) in Saudi Arabia.