Gas Lift Design Optimization Using Intelligent Gas Lift Valves a KJO Case Study

Abstract

Abstract Gas lift is becoming a big consideration in most of oil field as an economic, sustainable means of artificially lifting weak/dead oil wells. This is especially considered in high volume wells. Gas lift is employed, by injecting gas into the well tubing through gas lift valves, to reduce the hydrostatic pressure of the produced fluid column in oil wells, leading to a lower flowing bottom-hole pressure. The increased pressure differential induced across the sand face from the in situ reservoir pressure, assists in lifting the produced fluid to the surface. Optimizing the level of injected gas is important in maximizing the production, and hence the financial performance of the well. The challenge for most oil and gas producers is that they do not effectively maximize production with the most efficient use of gas lift resources. The challenge is that there is a lack of accurate and timely production data from the well tests. The optimal inject rate for a well is based on a ratio of injected gas rate to the liquid production rate. Under injecting the gas decreases the well production rate. The objective of optimization in gas-lifted wells is to achieve optimal production rate with minimal gas injection volume to spare gas for other wells, when the compression capacity is limited. Optimally allocated injection gas helps reduce unnecessary strain on your facility and maximize performance, this in turn enhances the life of production assets significantly. This paper presents a case study from Khafji Joint Operation fields, utilizing the intelligent digital gas lift valve to optimize the design and performance of the gas lift wells. The case study demonstrates the value proposition by using the digital intelligent gas lift system to maximize well performance whilst reducing injected gas, in addition to acquired real-time data that help assess the process. That optimization was achieved on well level by optimizing the well parameters such as point of injection, injection rate, and injection pressure. All these aspects have been investigated and presented in this study by using field data and flow simulations. Results showed the potential added value of the system.