Optimization of Inflow Control Device Placement and Mechanical Conformance Decisions Using a New Coupled Well-Intervention Simulator

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Abstract To optimize production from long horizontal wells, the completion design engineer must consider reservoir heterogeneity so that water breakthrough can be avoided. Reservoir heterogeneity is even more critical when combined with the presence of a strong aquifer; one of the methods commonly used to control this condition has been to have uniform water movement towards the horizontal well. Traditionally, inflow control devices (ICDs) have been used in horizontal wells to achieve this goal. However, design of the ICDs and now autonomous inflow control devices (AICDs) to achieve optimum productivity from the horizontal well can only be achieved by properly linking the ICD and AICD design to reservoir characteristics. Unfortunately, operators and service companies have often applied ICDs without adequate methods to verify completion efficiency over time, since available tools to quantify reservoir complexities and their effects over time have not been readily available. In this paper, a methodology and a numerical simulation approach that are designed to improve the success ratio of mechanical conformance treatments is presented. This approach combines a comprehensive solution for determining ICD and AICD effects on the wellbore behavior with a reservoir numerical simulator. The methodology considers the following: Placement techniquesAnnular flow controlICD flow size, rate, and number of ICDsReservoir fluid propertiesReservoir permeability distribution effectsFluid-property changes including prediction of water and gas breakthrough over time. A numerical simulator that couples the wellbore and reservoir characteristics has been developed that can provide an efficient means for optimizing ICD/AICD design and initialization. Simulated examples are given for basic conformance phenomena such as coning and channeling. Field cases will be presented that demonstrate the application of this method and how it designed an optimum ICD/AICD completion solution. This method reduced risks associated with ICD design and optimized the system designs through more accurately predicting water and hydrocarbon production.