Maximizing Oil Recovery with Variation in Ambient Temperature

Abstract

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.