This reference is for an abstract only. A full paper was not submitted for this conference.
Many studies are recently performed about the fluid flow in gas condensate reservoirs. But the recovery mechanism in a naturally-fractured system of this class of reservoirs needs more investigations. This paper includes the most important mechanisms involve in the production of condensate in a synthetic dual-porosity model which contains a rich gas-condensate fluid. The study focuses on the effect of gravity drainage and gas diffusion mechanisms on the fluid exchange between two mediums: matrix blocks and surrounding fractures network. An inclusive sensitivity analyses are also done on the effect of reservoir properties on these two mechanisms. The simulation results show that the presence of a positive capillary pressure in the matrix system leads to aggregation of condensate in the matrix blocks and hindering the flow of more condensate through the fractures. In the case of moderately permeable reservoirs, the gravity drainage is the predominant mechanism to transfer the condensate from the matrix to the fractures. In such cases, the matrix blocks height is the main effective factor on the performance of gravity drainage; increasing this parameter results in more condensate recovery. Furthermore, the high value of the critical condensate saturation in the matrix may act as a negative factor and obstruct the condensate transfer by gravity drainage. In the reservoirs with extremely tight matrix, gas diffusion has an important role in the fluid exchange between two mediums. This mechanism causes more condensate drop-out in fractures from the gas that diffuses from the matrix. In these reservoirs, increasing the matrix blocks size or fracture spacing as well as decreasing the gas relative permeability in matrix, leads to more gas diffusion and consequently more condensate recovery. These studies express that proper estimation of reservoir properties determines the predominant mechanism in hydrocarbon recovery and gives an acceptable production forecasting.