Publications

In Gas Lift operation, optimum gas injected results higher liquid production rate. Otherwise, compressing the gas before injected to the well needs more expenditure to rent or purchase gas compressor facilities. In this paper, technical and economical evaluation is deployed to decide gas injection allocation strategy considering the dynamic oil price. Gas Lift Performance Curve (GLPC) of 5 wells is constructed to determine the relation between gas injection rate and oil production rate of each well. Mathematical modeling is conducted to find mathematical correlation which represents oil production rate (y-axis) as a function of gas injection rate (x-axis) for each GLPC. The highest oil production rate is the main objective of the technical approach. Hence, Genetic Algorithm (GA) finds optimum gas injection rate allocation to gain the highest oil production rate in limited gas allocation. The highest daily operational revenue is main objective of economical approach. Therefore gas availability, oil production rate, gas injection rate, oil price, gas price, operation cost and installation cost are sensitive variables on the economic model. A case study is employed at 37.4 USD/bbl of oil price. At that condition, Gas Lift is recommended to be conducted in low gas allocation (1883 MSCFD) in order to get the highest revenue. Moreover, when the oil price rise up to 100 USD/bbl, the higher gas allocation (5345 MSCFD) is advised to be applied which result in the highest revenue. Gas Lift operation has to consider the dynamic of oil price, operational cost and capital cost of each scenario. GA method has the flexibility to create the economical approach in many cases of the economic condition. It helps to decide if gas lift installation is necessary and to decide how much gas should be injected. In dynamic oil price condition like today, the challenge is not only to gain higher production rate but also to gain highest revenue. Keywords: Gas lift Optimization, Technical Approach, Economical Approach, Dynamic Oil Price, Genetic Algorithm.