Sarawak offshore wells are mostly completed with dual string completion and are heavily relying on gas lift as the primary artificial lift. Dual string gas lift is an economical way to selectively produce from multi-stacked reservoirs in Sarawak fields. However, it poses great challenges in terms of operations, troubleshooting, allocation and optimization as both strings share a common annulus. Dual string gas lift performance diagnosis need to be done from time to time to ensure the strings production are optimized at well level.
Gas injection rate is a critical input in predicting the well performance based on the gas lift performance curve. However, the gas lift injection rate for dual string is measured at well – not at string level. The gas lift injection rate into each string needs to be allocated correctly either through well modelling calibration approach, testing one string while shutting its neighbor or well tracer application. After allocating the gas lift injection rate into each string correctly, well modelling prediction run at done to mitigate multipointing issues, design optimum point of injection, establish optimum injection rate at well level and determine the optimum casing head pressure.
The operator has proposed for a workflow to correct the dual gas lift injection allocation based on well modelling calibration. The workflow was implemented and resulted in multiple optimizations in terms of gas lift valve change program, choke optimization and gas lift rate optimization. Apart from that, the paper will also share on the findings from the well tracer application in correcting the gas injection allocation.
This paper will focus on the production performance check on dual string gas lift performance at well level. The findings from the study are subsequently monetized as quick-gain opportunities while the operator is embarking into long term study on assessing the alternative artificial lift strategy suitable for a brownfield. The lessons learned will also be applicable to oil fields with similar situations to further improve the fields’ production.