First Application of Autonomous Inflow Control Valve (AICV) in Libya to Reduce Water Production and Increase Oil Production

Abstract In line with a growing industry trend and as more wells are completed and retrofitted with inflow control technologies, the impact on production efficiency is becoming increasingly evident. This paper presents a case study on operational modeling, deployment, and well operations best practices workflow. A mature brownfield developed with vertical wells, most of which experienced significant water production (for example high water cut), resulted in uneconomical and inefficient recovery. To mitigate the risk of water production and crossflow issues in an existing well, an operator performed a re-entry and completed the well using an Autonomous Inflow Control Valve (AICV). Well B, a deviated observation well with 988 feet of open-hole length in a sandstone reservoir, had been classified as non-producing for 17 years. The operator sought to convert this well into a production well. However, due to the high water cut in nearby offset wells (approximately 71-74%), production was not feasible without implementing an AICV downhole completion to reduce water production and maximize oil recovery. In March 2024, the AICV downhole completion was successfully installed to mitigate the anticipated water production and enhance oil production. Lower completion with AICV effectively shuts off water-producing zones and stimulates oil-bearing zones, significantly increasing oil output. Post-installation results show a water cut of around 3% and oil production of approximately 1,134 bbl/d. Compared to offset wells, water production was reduced by 98% from 1,632 bbl/d to 34 bbl/d. Additionally, water cut dropped from 71% to 3%, while oil production increased by 72%, from 661 bbl/d to 1,134 bbl/d. In line with a growing industry trend and as more wells are completed and retrofitted with inflow control technologies, the impact on production efficiency is becoming ever more evident. This paper outlines key learnings for activities prior to, during, and post deployment of AICV lower completion as applied to this well; it could serve as a guideline highlighting key considerations of AICV understanding and modelling for future AICV applications.