This paper will discuss modeling and compositional simulation of a large gas-condensate field in the Russian part of the Precaspian basin.
The naturally fractured limestone reservoir is highly heterogeneous with complex geology and having high initial pressure. The field was modeled using different reservoir modeling software packages : STORM, TIGRESS and ECLIPSE
The behavior or reservoir was modeled with 3D simulation grid, having corner point geometry. TIGRESS and ECLIPSE compositional models with dual porosity options where used
A lack of geological and laboratory data was complicating the modeling task. Reservoir geometry was obtained only from well observations, using mapping algorithms, implemented in TIGRESS software Dual porosity sigma values was obtained from well test data, using ECLIPSE WELLTEST and TIGRESS pressure analysis software and were history matched. Only total porosity values from petrophysics observations were available in this project At first the total porosity distribution was obtained at fine 3D grid, using STORM stochastic modeling technique and upscaling procedures.
Fractured matrix porosity was calculated from total porosity, using simple constant multipliers, which were then treated as history matching parameters. Permeability distribution was obtained from a little amount of core data and porosity – permeability correlation, using STORM petrophysic properties modeling facilities. Then permeability data was corrected, to be consistent with well tests interpretation results.
Three phase study was initialized, using equilibration algorithms, implemented by TIGRESS and ECLIPSE software
The flow dependent skin factor options for calculation well inflow performance was used to take in account non – Darcy flow to the wells, having high pressure dropdown.
3D visualization tools implemented in RESVIEW, TIGRESS, ECLIPSE software allowed us to view and better analyze our input data and results.
Modem 3D modeling technologies allowed us to achieve a better description of the large and complicated reservoir, giving more reliable predictions of the field production performance