Modelling and Analysis of Autonomous Inflow Control Devices
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Gas and water coning is a significant problem in many oil fields. Inflow control technology is used to limit the negative effects of coning, and newer technology is regularly introduced. This thesis investigates Autonomous Inflow Control Devices (AICD) and Autonomous Inflow Control Valves (AICV). Laboratory test data has been found for two types of AICDs: (1) Statoil s RCP-valve and (2) Halliburton s Fluidic Diode Valve. Four models has been tested for both datasets: Statoil s AICD-model, the Bernoulli model, Sachdevas model and Asheims Model. The latter three models are originally intended for flow through chokes and simple valves. The Statoil model was found be to fit the datasets better than all the other models, with an average error of 21.8% and 11.3% average relative error for datasets 1 and 2, respectively. A new method was suggested to improve the modelling of AICDs in reservoir simulators. The method consist of splitting the Statoil model up in 4 datasets each representing oil, gas, water and multiphase flow and merging the models in a VFP-table. A tool to do this was made in Excel, and VFP-tables for AICDs specific for Troll conditions was made and attached. The use of the tables has not been tested or confirmed in Eclipse. A one-dimensional steady state well performance analysis was performed. A horizontal producing well typical of the Troll field was created, and a representative inflow and GOR-Model was made to represent a coning well. The analysis was done for three different reservoirs, for three different gas-coning models with three different completions. Open hole, AICD and AICV completions were analyzed. AICVs were assumed to behave identical to AICD; but capable of shutting off above a certain gas or water volume fraction. The results suggested that wells completed with AICD and AICV significantly increased oil recovery, while AICDs were slightly better than AICVs.