In Q4 2017, the first extended-reach horizontal oil producer was completed in S-Field, with the horizontal section designed with nine isolation compartments with swellable packers. Each compartment was configured with an inflow control device (ICD) and an integral sleeve (on/off function) attached to the ICD’s joint. This paper discusses the effectiveness of the ICD technology in terms of sustaining incremental cumulative oil production by delaying water-breakthrough and subsequently reducing undesired water cut after water-breakthrough. An extensive post-job evaluation on production performance was conducted to evaluate the performance of the installed ICDs. The workflow was divided into three stages: history matching, forecasting, and post-job ICD evaluation. During history matching, the horizontal well with the ICDs was modeled using a high-resolution numerical simulator, and the reservoir model was calibrated with production data from a well test. Actual production rates and the water-breakthrough time were matched by revisiting key subsurface uncertainties from the sector model, such as aquifer strength, oil/water-contact, and relative permeability using the Corey correlation. The history-matched model was then used for the forecasting stage to predict cumulative production on a longer-term basis. Lastly, the performance of the ICDs was quantified after 4 years of production by comparing the oil increment from the ICD completion to the non-ICD case as baseline that would have been a miss of additional oil cumulative. Over the past 4 years, this horizontal well produced more than expected, with approximately 2–4 times more oil production than the estimated rate provided in the field development plan (FDP), whereby the lower completion is design optimally based on real-time ICD modeling updates. There were few uncertainties in the subsurface parameters such as fluid contact, fluid characterization, and the nature of an aquifer, were incorporated in the history-matching stage using sensitivity analysis and uncertainty range estimation. On the basis of actual and history-matched production performance, the well with the installed ICDs is projected to produce more than the non-ICD OH case with an improved cumulative oil production gain of as much as 6% and an 8% water reduction over 12 years of production. In addition, the ICD enables downhole influx balancing to delay the water breakthrough by 4 months compared to the OH case. The reduction or delay of water production is beneficial to the field to enhance oil recovery from the well. This case study demonstrates a successful ICD deployment under uncertainties, where during a real-time study in 2017, similar uncertainties were incorporated in high-resolution ICD modeling conditioned with real-time petrophysical data from logging while drilling (LWD) measurements. The use of ICD technology in this well demonstrated that zonal control efficiency could be achieved across the horizontal section and increased oil production over time. The ICDs were designed to deter early water breakthrough supported by well tests and manual fluid sampling indicating the water production only occur after 4 years of production and sand-free till to-date.

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.