Abstract
Reservoir heterogeneity is a key factor in modelling reservoir performance. Heterogeneity measures can be calculated for a given permeability field, but not straight forward to reverse the process. Detailed heterogeneity can be built into a fine-scale model but can be lost during upscaling to a coarse-scale, no matter which method is chosen from simple averaging to flow-based. This paper proposes a method of heterogeneity modeling and heterogeneity-based upscaling with the aim of solving these problems.
Unlike the traditional geostatistical method used to generate a permeability field that is not directly linked to a desired heterogeneity coefficient, the proposed method creates a heterogenous permeability field directly using LCC (Lorenz coefficient and curve). Using a given LCC as input, the expected heterogenous permeability field can be generated via the proposed steps and equations. Using the proposed heterogeneity-based upscaling method, the LCC defined from the fine-scale model can be preserved exactly during upscaling such that gas-oil-ratio and water-cut can be matched between the fine- and coarse-scale models without using pseudo functions.
The proposed method has been successfully applied in modelling a giant carbonate oil field in the Caspian Sea consisting of a matrix dominated platform and a fracture/karst dominated rim. Due to the field's complex geology and high H2S content, a dual porosity, dual permeability compositional model has been created to model compositional flow within/between matrix and fracture/karst initialized with an abnormally high reservoir pressure. The field surveillance data shows that reservoir heterogeneity (LCC) is a key component for the field reservoir characterization and simulation. The LCCs can be estimated from the cores and logs, but the challenge is how to preserve the characteristics of the LCCs during modeling, upscaling, HM, and Uncertainty Analysis (UA). Application of the new method has demonstrated its ability to overcome this challenge and has significantly improved the quality of the field's reservoir modeling, upscaling, HM, and UA. The fine-scale model LCCs were directly applied to calculate the coarse-scale permeability. The range of the LCCs estimated from cores and logs were used to generate a range of heterogeneous permeability fields for UA. Regional LCCs were adjusted based on the mismatches of GOR and/or water-cut and new heterogeneous permeability fields were generated to improve the HM quality.
