Intelligent Completions To Optimize Waterflood Process in a Mature North Sea Field
Authors: Denney Dennis 
Published: February 2015

This article, written by Technology Editor Dennis Denney, contains highlights of paper SPE 101935, "Application of Intelligent Completions To Optimize Waterflood Process on a Mature North Sea Field: A Case Study," by A. Ajayi, SPE, and M. Konopczynski, SPE, WellDynamics Inc., and O. Tesaker, Statoil, prepared for the First International Oil Conference and Exhibition in Mexico, Cancun, Mexico, 31 August-2 September 2006.
A dynamic-reservoir-modeling study was performed on field implementation of intelligent-well technology (IWT) in a mature North Sea field. The purpose was to quantify the use of the technology for redeveloping the field. The study examined applying IWT to multiple production and injection wells to accelerate production, reduce well count, extend the production-plateau period, and reduce well intervention. The study estimated potential increase in oil-recovery factor ranging from 0.48 to 6.1% of the original stock-tank oil in place over the life of the field.

Introduction
The main objective of this study was to identify the best application of IWT for the field. The conventional system commingled production without zonal control. The study assessed the capability of IWT to maximize oil production while managing water breakthrough and to commingle production from multiple sands while minimizing effects on reserves. The case study detailed in the full-length paper used a reservoir-simulation model having a value-driven concept to assess the feasibility of intelligent-well systems. This concept was adopted to customize the model to address a specific solution. The drivers were accelerating production, reducing well count, extending the production plateau, and reducing well intervention. For each driver, specific reservoir models were constructed to address the capability of the IWT to provide a viable solution. The reservoir simulation focused on the incremental improvements in reservoir performance for the intelligent-well case compared with the conventional case.

Case Study and Model Description
The simulation model consisted of 55×100×19 grid cells in the x, y, and z directions, respectively. A black-oil pressure/volume/temperature table generated from laboratory data and validated with historical production data was used to describe the reservoir-fluid system. A cross-sectional view of the reservoir structure is shown in Fig. 1, while a 3D saturation graph is shown in Fig. 2 (oil in red, water in blue).
The producing wells (in both the base case and intelligent-well case) were constrained by maximum liquid-production rates of 6000 std m3/d and minimum bottomhole pressure of 4000 kPa. The injectors were constrained by maximum bottomhole pressure. The intelligent wells have 5 1/2-in., five-position interval-control valves with a maximum internal diameter (ID) of 4.6 in. The conventional wells are completed in 7 1/2-in. tubing with an ID of 5.95 in. Each well is allowed to produce to a maximum water cut of 95% before it is closed in for high water production. The reservoir model was initialized with a water/oil-contact depth of 2495 m and reservoir pressure of 38 MPa at 2469 m reference depth.