With the evolution of downhole permanent monitoring techniques, transient temperature and pressure data can play an important role in reservoir description due to their inherent real-time characteristics. Previous studies presented a completely new analysis technique for quantifying permeability and altered zone permeability and radius for multiple commingled layers. However, the previous model mainly applies for single-phase oil flow.
A new wellbore/reservoir coupled flow model has been developed for multilayer commingled gas reservoirs including both damage and non-Darcy skin in each commingled layer. The non-Darcy effects are considered as permeability alteration and are incorporated to the reservoir flow model by using Forchheimer equation. Additionally, this coupled flow model can consider the pressure drop due to friction and kinetic energy changes in wellbore over the producing layers, which yields more accurate transient layer flow rate allocation. This coupled flow model is used to provide the wellbore pressure distribution and the radial reservoir pressure gradient for the coupled wellbore/reservoir temperature model. The temperature model is formulated using wellbore and reservoir energy balance equations considering subtle thermal factors such as Joule-Thomson effect and also using fluid properties which are dependent on in-situ pressure and temperature. The inverse method is adopted from previous study directly and is used for determining formation properties by doing nonlinear regression.
The mathematical model is solved numerically and used to study the sensitivity of transient temperature behavior to formation properties. The results show that transient temperature behavior in the wellbore at strategic locations is very sensitive to formation property values, and has some interesting characteristics similar to oil reservoirs. However, due to the non-Darcy effects, each producing layer in multilayer gas reservoirs has non-Darcy skin more or less, which makes the transient temperature behavior in gas reservoirs show more complexities than the oil reservoir case. In the end, two hypothetical examples are presented to show the performance of the inverse method. The regression results show that the damage skin location and magnitude can be determined correctly using the proposed testing method.