Field S located in offshore Malaysia had been producing for more than 30 years with nearly 90% of current active strings dependent on gas lift assistance. Subsurface challenges encountered in this matured field such as management of increasing water-cut, sand production, and depleting reservoir pressure are one of key factors that drive the asset team to continuously monitor the performance of gaslifted wells to ensure better control of production thereby meeting target deliverability of the field. Hence, Gas Lift Optimization (GLOP) campaign was embarked in Field S to accelerate short term production with integration of Gas Lift Management Modules in Integrated Operations (IO). A workflow was created to navigate asset team in this campaign from performing gaslift health check, diagnostic and troubleshooting to data and model validation until execution prior to identification of GLOP candidates with facilitation from digital workflows. Digital Fields and Integrated Operations (IO) developed in Field S provided an efficient collaborative working environment to monitor field performance real time and optimize production continuously. Digital Fields comprises of multiple engineering workflows developed and operationalized to act as enablers for the asset team to quickly identify the low-hanging fruit opportunities. This paper will focus on entire cycle process of digital workflows with engineer's intervention in data hygiene and model validation, the challenges to implement GLOP, and results from the campaign in Field S.

Gas Lift Optimization solutions have improved significantly over the past decades with the introduction of Integrated Operation (IO) in the Oil and Gas industry. Big fields that consist of hundreds of strings, gas lift injection system, water/gas injection system and complex surface facilities (compressors, pumps, choke and valve, etc.) could establish numerous cases from different scenarios to identify production bottlenecks via simulated network models. Using available tools, the user could model the full production system including well, surface network, reservoir, gas/water injection models, gas lift injection networks and process plants to identify bottlenecks and opportunities for optimization. The model is updated continuously using live data feed and automated technical workflow to establish an end to end solution in providing various optimization scenarios e.g. Gas Lift Optimization. This paper discusses how the methodology works and reviews the results of gas lift optimization from four platforms consisting of over 200 strings of which 95% are gas lifted, operated using a new approach that includes live link to field data, integrated model management, and automated technical workflows to identify potential strings and gas lift supply facilities for production enhancement. This paper reviews the setup required to ensure all the necessary inputs are aligned to publish the desired outcome. The approach has resulted in prevention of 480bopd potential deferment at platform level that can be further improved with future field implementation. In addition to gas lift optimization, the workflows have potential to expand to other business needs such as defining an accurate gas demand requirement, determining daily liquid or sand production limitation identifying underperforming wells, optimizing choke configuration, studying the feasibility of low pressure system, water treatment system, and condensate recovery system. This paper should be of interest to those who are planning to implement Integrated Operations to their field with the aim in maximizing its value. It will provide information on the requirements, challenges, ways to overcome, and effective approach during the implementation.