Advanced Temperature Modelling for Two-Phase Flow
Abstract
This thesis presents an advanced model for temperature predictions of a producing well. With today s low oil price, cost reduction has become paramount for many big oil companies. One way of reducing operational costs are employing accurate temperature models. This helps to ensure correct pressure distributions, fluid density profiles and volumetric flow rates in the tubing. This is crucial for safe casing design, optimizing production facilities, as well as handling flow assurance challenges.The developed model calculates the well temperature in incremental steps from the bottomhole to the wellhead, assuming steady-state heat transfer in the wellbore and transient heat transfer in the formation. Effects related to multiphase tubing fluid is accounted for as the composition, number of phases, densities and volumetric flow rates changes throughout the well. The model does not account for varying specific heat capacities as pressure and temperature varies.A comprehensive sensitivity analysis has been conducted in order to examine the effects of different input parameters on the calculated temperature profile. The validity of assumptions made have also been investigated.The main conclusions from the work performed is that the empirical equations used for the two-phase calculations should be modified in order to be applicable for HPHT data. It is also important to establish an accurate specific heat capacity profile of the tubing fluid, due to its significant impact on the temperature calculations. The model was compared to the ILS, showing a lower temperature at the wellhead. Results from the developed model has not been compared to field data, which causes the validity and accuracy of the model to remain uncertain.Further work should focus on how the phases and specific heat capacities for each component varies as a function of pressure and temperature. Furthermore, a reliable pressure distribution should be developed to improve the accuracy of the developed temperature model.