A Novel Optimisation Algorithm for Inflow Control Valve Management (SPE 154472)

Intelligent Wells are equipped with downhole sensors to monitor the downhole flow and Inflow Control Valves (ICVs) to control the zonal flow rate. These ICVs are operated to increase the hydrocarbon recovery and prevent unwanted fluid production. This objective is simply stated, but optimisation of ICV operation is a complex, non-linear problem. Several commercial software providers have made optimisation algorithms available to the industry. Nevertheless, experience shows that challenges still arise with these algorithms when they are applied to real-field cases. Not only does the calculation time increase dramatically (up to 50 times when compared with non optimal run), but also stability and convergence problem give additional increases in running time as well as providing unrealistic results at random intervals. These problems are particularly acute if the software is applied to production uncertainty analysis where the running of multiple realisations is required. This paper will present a novel method for implementing an ICV control strategy. We chose the direct search algorithm to form the basis for our method since it is not affected by convergence problems. Our control strategy will use the current, zonal inflow rate and water cut data to identify the optimal ICV choke positions. The availability of this data reduces the number of possible choke positions that have to be evaluated at each time step by the simulator. Run times only 2-5 times greater than the base case can then be achieved while, equally importantly, the optimal value identified is similar to the value from other, widely accepted methods. We will show how this method can be used for reactive control of oil production from intelligent wells completed with discrete ICVs and, since this control algorithm is always convergent, fast and sufficiently stable will indicate how it may be used for production uncertainty analysis.