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The generic term “intelligent well” is used to signify that some degree of direct monitoring and/or remote control equipment is installed within the well completion. An intelligent well has the following characteristics:
- It is capable of collecting, transmitting, and analyzing wellbore production and reservoir and completion integrity data
- It allows remote action to control reservoir, well, and production processes
Until the late 1980s, remote monitoring was generally limited to surface pressure transducers around the tree and surface choke, with remote completion control restricted to the hydraulic control of safety valves and (electro-) hydraulic control of tree valves. The first computer-assisted operations optimized gas lifted production by remote control near the tree and assisted with pumping well monitoring and control. Permanent downhole pressure and temperature gauges are commonly run as part of the completion system and combined with data transmission infrastructure.
With the development, successful implementation, and improving reliability of a variety of permanently installed sensors, it was perceived that the potential to exercise direct control of inflow to the wellbore would provide significant and increased economic benefit. The service industry responded with early complex, high-cost systems designed to provide full functionality, which did not reach wide acceptance because of the perceived low probability of success and resulting high installation risked-cost. To counter these problems, industry responded with lower-cost hydraulic systems, which provided some of the functionality of the initial high-end devices. These systems permit a variety of sensors to be packaged together with the hydraulic control devices to provide a complete intelligent-well completion.
Intelligent well systems
The objective of the intelligent-well system is to maximize value, which could include – increased production, improved reserves recovery, minimized capital and operating expenditures. Systems are monitored and operated to optimize a given parameter by varying, for example, the inflow profile from various zones or perhaps the gas lift rate. Remote monitoring and control capabilities include: pressure and temperature sensors; multiphase flowmeters; flow-control devices.
These points articulate key objectives of the intelligent well system.
- Improved recovery (optimize for zonal/manifold pressures, water cuts, and sweep).
- Improved zonal/areal recovery monitoring and allocation (locate remaining oil and define infill development targets).
- Optimized production (improved lift, acceleration, and reduced project life).
- Minimized capital investment to exploit an asset.
- Reduced intervention and operating costs.
- Optimized water handling.
Intelligent-well technology can deliver improved hydrocarbon production and reserves recovery with fewer wells. Intelligent-well technology can improve the efficiency of waterfloods and gasfloods in heterogeneous or multilayered reservoirs when applied to injection wells, production wells, or both. The production and reservoir data acquired with downhole sensors can improve the understanding of reservoir behavior and assist in the appropriate selection of infill drilling locations and well designs. Intelligent-well technology can enable a single well to do the job of several wells, whether through controlled commingling of zones, monitoring and control of multiple laterals, or even allowing the well to take on multiple simultaneous functions—injection well, observation well, and production well.
Finally, intelligent-well technology allows the operator to monitor environmental conditions and manage well integrity.
Noteworthy papers in OnePetro
Use this section to list papers in OnePetro that a reader who wants to learn more should definitely read
Mohaghegh, Shahab D. 2013. Smart Fields; A Data-Driven Approach to Making Oilfields Smart. https://webevents.spe.org/products/smart-fields-a-data-driven-approach-to-making-oil-fields-smart
Saputelli, Luigi. 2013. Artificial Intelligence Applications in the E&P Industry and an Example of Short-Term Production Prediction Using Neural Networks. https://webevents.spe.org/products/artificial-intelligence-applications-in-the-ep-industry-and-an-example-of-short-term-production-prediction-using-neural-networks
Popa, Andrei. 2015. "Understanding the Potential of Case-Based Reasoning in the Oil Industry." Web Events. Society of Petroleum Engineers, https://webevents.spe.org/products/understanding-the-potential-of-case-based-reasoning-in-the-oil-industry-morning-session.