TX 75083-3836, U.S.A., fax 01-972-952-9435. AbstractThis paper describes the considerations and integrated design process for specifying the Cv characteristics of an adjustable flow control valve for an intelligent well. The paper emphasizes the need to consider the complete well as a control system, including inflow, choke performance and well bore outflow performance.The paper describes a method for establishing the most suitable flow control design for the application. The method combines nodal analysis and choke performance modelling to model the behaviour of the entire well bore system. This analysis is extended to multiple layer or multiple zone intelligent well completions. An example of the analysis is presented.

Intelligent well technology provides the ability to monitor well bore data (e.g. down-hole pressure/temperature) in real time through down-hole sensors, and to control fluid flow into or out of the wellbore at each segment. However, integrating these real-time data into a reservoir management work flow and turning the data into measurable and tangible value is still an elusive and complex task. This paper proposes a technique of integrating down-hole real-time pressure and temperature data to predict and allocate multiphase production in a multiple zone intelligent well system. The technique combines the known position of the installed zonal Interval Control Valves (ICV), measured real-time pressure and temperature data, available production data, and reservoir fluid properties, to estimate the production rate of each zone using customized ICV choke performance models. In order to account for the impact of phase behavior on the prediction, fluid systems have to be corrected to the prevailing in-situ flow conditions. In light of this, an improved multiphase choke model for down-hole ICV is introduced in this study. To demonstrate this technique, one example of a hypothetical two-zone intelligent well completion with multi-phase production is illustrated. The example shows how to use the surface production data, e.g., GOR, WOR, API, Gas S.G., and real-time gauge data with the multiphase choke model to predict production of each phase through the ICV. Introduction A Typical Two-zone Intelligent Production System. Fig.1 is an illustration of a typical two-zone intelligent production system. Two ICVs are installed to control the distribution of the produced fluid. The upper ICV is used for controlling the production of the upper zone; the lower ICV is used for controlling the lower zone. The lower zone ICV is shrouded and its lower tubular side is plugged, for the purpose of separating the production fluid of both zones and also for completion design convenience. An upper fluid loss control device is located in the upper zone gravel pack completion and isolates the upper sand. When the upper completion string (including tubing, packers, ICVs, etc.) is landed, the seal assembly below the shrouded ICV locates in a polished bore between the zones and isolates the upper and lower zones during production. Production from the upper zone passes between the OD of the tailpipe and the ID of the fluid loss control device, out into the casing/tubing annulus space and is controlled by the upper ICV. Production from the lower zone passes through the bore of the fluid loss control device and into the shroud and is controlled by the lower ICV. The green arrow line and sienna (dark red) dashed arrow line in Fig. 1 show the flow direction of the production fluids for the upper zone and lower zone respectively. Available Real-Time Data. In this completion, a triple gauge system is installed above the upper ICV. The gauge system measures real-time annulus and tubing pressure/temperature data at the installed position (above the upper ICV). The annulus measurement can be reasonably assumed as the upstream pressure/temperature data for the upper ICV. The system will also measure annulus real-time pressure/temperature data at the shrouded section of the lower ICV. This is the upstream data of the lower-zone ICV. The tubing measurement above the upper ICV can be approximated as the downstream data for the commingled fluid production. This measurement can be used to estimate downsteam pressure for both the upper and lower ICV based on known zonal produced fluid properties, accounting for hydrostatic column and geometric/frictional effect of downhole components. Neglecting the minor geometry changes caused by the completion products, i.e., packer, nipple, safety valve, etc., the equivalent flow network for this completion is given in Fig. 2.

Intelligent well completion has been used in various applications including but not limited to fields with multiple reservoirs. In such applications, estimation and allocation of downhole flow rates at each reservoir are critical for efficient reservoir management. One way of estimating downhole flow rates is the deployment of dedicated physical zonal flowmeters, using virtual flowmeter techniques based on the architecture of the intelligent well completion or combination of both options. This paper describes the methodology and field wide application of using real time data from an intelligent well to estimate flow rates without the need for a physical flow meter. The real time data are from the installed downhole gauges in the well. This is combined with interval control valves, static and dynamic well information to provide reliable estimate of well production rate. Since downhole pressure, temperature and ICV information is already available in an intelligent well, this technique provides a lower cost option of obtaining zonal and total well production and injection rates. The methodology used incorporates analytical choke equations, tubing performances, and nodal analysis (inflow performance relationship) with other reservoir parameters to build a flow estimation algorithm and model. Various downhole equipment (interval control valves, packers, pressure and temperature sensors etc) and related well information are captured 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. In the field application described, results vary from well to well with field average estimates within +/−10% when compared to measurements from normal surface metering systems. Well tests from the surface measurements were used to calibrate and improve accuracy. The result shows an operating envelope that covers a range of pressure drop across the ICV. The method is capable of handling single and two phase system. Further enhancements are been made to handle multiphase and systems outside the steady state regime. In addition, enhanced data filtering techniques implemented in the system help managed noisy data. The analytical techniques described enhance digital oilfield capability in optimizing production through affordable flow rate estimation for intelligent wells. The technique presented can also be used to increase the reliability of applicable wells since no additional physical hardware is required.

This paper describes a stochastic approach to the design of interval control valve choke trims for an intelligent well system. The paper builds on the deterministic approach of specifying the Cv characteristics of a multi-position control valve. The probabilistic method considers reservoir uncertainties in productivity indices, zonal pressure drawdown, expected production (or injection) rates and field production operation philosophy. This design approach allows the control valve to meet the expected control objectives and ensures that the design trim is applicable to a wide range of well performance. The probabilistic method is demonstrated using real data from field examples. The probabilistic design methods described in this paper are applicable to all intelligent well systems using variable choking valves, on both production wells and injection wells. The methodology is also applicable to intelligent well systems targeting reservoirs with characteristics that are widely uncertain. This method will enable the engineers to design an interval control valve (ICV) that incorporates reservoir uncertainties with field control philosophy leading to an optimized well delivery system. Introduction Intelligent well downhole control valves are used for many purposes in different field applications. Downhole control valves can be used to control production commingled from multiple zones, to balance production between contributing zones and to implement field operating strategies. The number of intelligent well installations using variable flow control rather than binary (on/off) valves has increased to the point where variable flow control is the preferred solution in the majority of installations. The use of intelligent well technology in field development has been addressed by several authors. Oberkircher1et. al presented a review of different applications and integration of intelligent and multi-lateral well systems. The authors highlighted benefits and drawbacks and potential solutions of selected applications. Haugen2et. al. also discussed a field development that integrates intelligent well systems with multi-lateral technology in three horizontal subsea wells in the Gullfaks South Stratfjord field. The implementation resulted in estimated reserve increase to 5.4 MM Sm3. The main attraction for using the technology was to provide required flexibility to control contribution from different branches of the multi-lateral wells. In a satellite offshore Malaysia field, Bogaert3et. al. described an integration of gas lift optimization with intelligent well systems for real-time flow estimation and remote process control. This application resulted in about 10% production gains and 2% additional reserves. In each of these applications, the performance of the downhole ICV is determined by the valve trim design. The trim is described by its valve coefficient, Cv, which quantifies the relationship between flow rate and pressure drop of the valve as a function of position. In order for the ICV to provide the necessary degree of flow control required, it is necessary to incorporate information about the intended application and operating environment of the ICV in the design process of the trim Cv. This means information about the reservoir for which the ICV will be used to control production or injection needs to be used in the design process. The process of incorporating the reservoir performance with other engineering constraints results in an ICV with a customized choke trim design that meets the requirements of the particular application. A choke trim customization method involving the use of nodal analysis and engineering design constraints is given by Konopczynski and Ajayi4. This method can be used to customize downhole chokes for specific applications. The authors indicated that the objective of the customized design is to specify a choke trim that provides good flow control sensitivity across the range of valve positions based on the reservoir information. This design process challenges the engineers to consider the operating conditions for the IWC application.

The paper describes the study conducted to evaluate the number of wells (producers and injectors) required to develop a small segment of an offshore field. The development plan consisted of both conventional and intelligent well completions. The main objective was to identify the best application of intelligent well technology in the field and quantify the gains from such applications. The technical performances of these cases are compared using the same base reservoir simulation model. Binary and multiple position downhole flow control valves are considered to determine the right level of "smartness" required for the field. The study has shown that application of intelligent well completion (IWC) technology in selected wells will add value through control of produced water after breakthrough and manage subsurface uncertainty by mitigating unexpected well performance. We estimated incremental oil gain of 2.5% to 26% within the first two years after water breakthrough. The results also demonstrated the capability of the IWC system to maximize asset productivity in cases where breakthrough occurred early and when it occurred somewhat later. In the former case, the non-offending intervals are able to easily complement the effect of choking back the offending zone resulting in significant gain. Introduction Intelligent well technology provides an operator the capability to remotely control, monitor and manage multiple horizons in a well.The technology provides significant value through the ability to control multiple zones independently, reduce total number of wells required for a development, reduce costly well intervention, accelerate production and/or alternate production between zones to maintain a production rate plateau for an extended period of time. Asset development teams are often required to economically justify the additional capital expense of IWC hardware in addition to demonstrating maximum operational value-addition of the technology.Large numbers of these teams have difficulty making this justification. A major reason is the lack of reservoir evaluation tools that can effectively model the intelligent well components and desired operations. Konopczynski and Ajayi[1] described other issues and challenges relating to intelligent well technology in field development. Several authors have presented ways of using reservoir simulation to quantify potential gains from using IWC in field development. Yeten Burak et al.[2] used a conjugate gradient optimization method connected to a numerical reservoir simulator to control intelligent multilateral wells.The work predicted a substantial increase in oil ultimate recovery when compared to conventional methods.Brouwer et al.[3] presented a study in which the optimization technique focused on reducing the difference in time of flight from the injector to producer in a water flood environment. The method involved manipulating the well segment productivity index to maximize total well production. Gai[4] developed a valve performance relationship based on inflow performance to optimize the valve settings in multilateral IWT completion. Ajayi and Konopczynski[5] presented a dynamic optimization technique to optimize multi-zone commingle production. The results showed substantial benefits of intelligent completions over conventional systems.Naus et al.[6] presented a study that used a sequential linear programming technique to develop an operational strategy for commingled production.They tested their algorithm on two reservoir settings which resulted in accelerated production when compared to conventional system. This paper presents how intelligent well systems in selected candidate wells added value through control of produced water after breakthrough, thereby accelerating oil production. There is also potential value in managing subsurface uncertainty by mitigating unexpected well performance. These benefits will be maximized by using systems with multi-position variable flow control valves. This is the level of "smartness" recommended for the field.