Use of Smart Controls in Intelligent Well Completion to Optimize Oil & Gas Recovery

  • Afuekwe A
  • Bello K
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Abstract

For the past few years, the oil and gas industry has faced several economic, geographic and technical challenges largely due to decline in crude oil prices and market volatility. In the quest to address some of these challenges to accelerate production and subsequently maximize ultimate recovery, operators are limited to remote hydraulic and electro-hydraulic monitoring and control of safety valves providing the means of obtaining downhole production data which demands periodic well intervention-based techniques with risk of loss of associated tools. This has highlighted the need for companies to adopt new technology to take advantage of low crude oil price environment, optimizing recovery without interventions and with minimal production interruption. One of the recent improvements in production technologies which can remedy these problems having unique capabilities to do so is the Intelligent Well Completion (IWC) technology. In this paper the utilization of IWC to optimize oil recovery was evaluated. The use of a reservoir simulator, the Schlumberger ECLIPSE-100 simulator, was employed to model an intelligent well. Case study simulations were performed for an active bottom-water drive. Modeling of the Intelligent Well Inflow Control Devices (ICDs) and downhole sensors for the multilaterals was achieved using the Multi-Segment Well model. Optimal IWC technology combination for maximum hydrocarbon recovery and minimal water production was determined using the reactive control strategy (RCS) which indicated a drastic reduction of about 52.1% in water production with a slight drop of 1.5% in field oil efficiency (FOE). The simulation results obtained clearly showed that the utilization of intelligent well-ICDs in Production wells can significantly increase the cumulative oil production and reduce water production.

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Afuekwe, A., & Bello, K. (2019). Use of Smart Controls in Intelligent Well Completion to Optimize Oil & Gas Recovery. Journal of Engineering Research and Reports, 1–14. https://doi.org/10.9734/jerr/2019/v5i416930

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