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Intelligent completions were introduced over a decade ago to address completions and reservoir management challenges arising from highly-deviated, extended-reach, multi-targeted, or multilateral wells. Recent advances in exploration and drilling technology are enabling the oil and gas industry to target reservoirs with stratigraphic and depositional complexities in deepwater, subsalt, arctic, and other extreme environments, resulting in the need to develop a new generation of intelligent completion tools. These reservoirs also may be characterized by HPHT, extreme HPHT, or ultra-HPHT environments with multiple components contributing to the uncertainty of recovery.This paper describes how the requirements of current and future reservoir environments and a decade of operational experience have shaped the functional design and qualification of a new-generation Interval Control Valve (ICV) for intelligent completions. The new-generation ICV has higher pressure and temperature tolerances to cater to the new harsher environments while simplifying its operating mechanism and improving inflow performance and debris tolerance. The qualification program included metal-to-metal seal qualification, life-cycle testing, API 14A SCSSV class II-sand slurry based tests, flow coefficient (C v ) test, seal stack qualification, and erosion testing. Descriptions of each qualification test, acceptance criteria and test results that demonstrate the capability of the new generation of ICV to perform in severe service conditions are presented in this paper.Field applications of the second generation valve have shown additional operational benefits not even considered during the design. Technologies such as real time ICV position feedback have further aided in maximizing efficiency by enabling the use of downhole or surface positioning. Surface positioning devices can choke flow by varying ICV positions. The use of surface positioning enhances reliability by reducing the number of tools required downhole. Finally the paper outlines the operational limits of the current design and discusses the design enhancements planned for the next generation ICV. IntroductionAdvances in exploration and seismic imaging technologies have opened up new opportunities for large, deepwater field developments in the Gulf of Mexico (GoM), offshore Brazil, Asia Pacific, and offshore West Africa. The Lower Tertiary Wilcox trend of the GoM alone has over a dozen industry discoveries to date with world-class reserve potential. These discoveries are predominantly subsalt reservoirs at water depths of 5,000 ft to 10,000 ft, with reservoir pressures over 25,000 psi at true vertical depths of 25,000 ft to 33,000 ft. Reservoir temperatures are in the range of 250°F-300°F.With a broad range of heterogeneous reservoir gross intervals from 1,000 ft to 3,000 ft and permeability ranges of 2 md to over 50 md, these fields may not be efficiently developed with the well completions technology used in today's GoM, offshore Brazil, etc. Most of today's completion tools are not ...

Fields with multiple producing reservoir units offer some of the most interesting asset development challenges. Several of these fields are now being completed with intelligent wells that enable commingling of multiple units with reservoir-control functionality. Unit production estimation and allocation of downhole flow rates are critical components of efficient reservoir and asset management.Deploying zonally dedicated subsurface flow meters is the most common way of estimating unit production rates on a real-time basis from an intelligent well. This paper presents results from analytical techniques for estimating unit production rates in real time by combining well architecture information, downhole pressure, and temperature data with appropriate reservoir inflow and interval control valve (ICV) flow equations.Since downhole pressure, temperature, and ICV information is already available in an intelligent well, this technique provides a lower-cost option for obtaining zonal and total well production and injection rates. The methodology used incorporates analytical choke equations, tubing performances, and nodal analysis (inflow performance relationships) with other reservoir parameters to build a flow estimation algorithm and model. Various downhole equipment (interval control valves, packers, pressure and temperature sensors, etc.) as well as related well information are brought into the system to set initial and final boundary conditions. Well-test data can be used to calibrate the system and improve the accuracy of the model.Field data from several wells have been run through the model; well tests from the field were used to calibrate and improve accuracy. Results vary from well to well. The system delivers flow-rate estimates greater than 90-percent accuracy when compared to actual flow-rate measurements from well tests and flow meters for some of the wells. The results show an operating envelope that covers a range of pressure drops across the ICV.Several considerations are being made to improve the results, especially outside the steady-state regime. The enhanced data filtering techniques implemented in the system helped manage "noisy" data. The analytical techniques described enhance digital capability in optimizing oilfield production through affordable flow-rate estimation for intelligent wells.

In digital oil fields in which intelligent completions are used, information that can be provided by the intelligent completion technology is increasing in importance, as intelligent well completions can minimize the need for additional custom datagathering solutions. Thus, industry-data interfacing standards for multiple devices and systems can be reduced. For assets using intelligent completions, solutions are attained by a combination of subsurface and surface or subsea sensors provided by several vendors.Challenges arise when attempting to manage the interfaces required for providing real-time data from all points of interest (i.e., subsurface choke positions, flow, pressures and temperatures, wellhead positions, subsea facility readings, etc.). The design and implementation of an integrated data-applications system that can integrate data from multiple workflow sources for the purpose of maximizing field performance is the focus of this paper. The asset optimization applications acquire operating parameters from all points of interest, making them available to software modules designed to estimate key wellperformance indicators.The asset-optimization application discussed here is an integrated system that performs five services: 1. A data-interfacing methodology acquires data from multiple sources or directly from downhole devices. 2. The integration service converts the subsurface and surface data to engineering units of measured well parameters. 3. The well performance service uses well PVT and device-integration service values to execute complex calculations, like virtual flow metering, water-cut estimates, etc. 4. The human/machine/interface service provides visualization, trending, and querying. 5. The connectivity service facilitates structured data transfer to field historians. The paper will explain how the system works and its implementation into fields of different scales and types to reduce information technology (IT) customization, simplify interfacing of multiple devices or systems, and accommodate evolutions in IT. Additional system benefits that include more efficient management of real-time data security, quality, redundancy, and mirroring will also be provided.