Simulação do escoamento com transferência de calor em válvulas de completação inteligente

Abstract

Industry and academia have been researching new ways to enhance techniques and strategies of oil extraction. Amidst technologies developed to optimize production is Intelligent Completion, in which Interval Control Valves (ICVs) are broadly used to control the oil production in multi-zone open-hole wells. Previous studies have shown that the temperature profile of the wellbore is useful in predicting flow composition as well as water and gas cuts. The flow distribution can then be regulated based on the monitored temperature behavior to achieve the required flow conditions. The present work aims to model and simulate heat transfer in ICVs assembled in an intelligent completion that produces from three different zones, presenting a steady-state analysis of the flow in terms of velocity and temperature profiles. Results for the temperature, velocity magnitude and pressure profiles are plotted based on Computational Fluid Dynamics simulations with the k-epsilon realizable model considering a fully turbulent and incompressible fluid with rheological and thermophysical properties sourced from existing literature models. The modeling assumes the flow as one-phase. The wellbore temperature profile is calculated using a steady-state model with temperature-dependent thermophysical fluid properties. Two production scenarios were compared. For the first scenario, the flow rate at the deepest zone represents 1/8 of the total production, the flow rate at the intermediate zone equals 3/8 of the total production and, at the zone closest to the surface, the flow rate is equal to ½ of the total flow rate. For the second scenario, the flow rate at each zone represents 1/3 of the total production of the well. In both scenarios the total flow rate is 40,000 barrels per day and the geothermal gradient is 4.782°C/100 m rate zone. Results showed that the distribution of the production between zones influences greatly the temperature profile of the well. Comparing measured temperature with the model predicted temperature might help detecting nonconformities on the production.