Karstic High Permeability Layers: Characterization and Preservation While Modeling Carbonate Reservoirs

Abstract

Abstract Diagnosis, characterization and modeling of high permeability layers constitute a very challenging issue while building carbonate reservoir models for flow simulation. In karstic reservoirs, the evaluation of the dual permeability behavior is the key to assess reservoir heterogeneity. This heterogeneity is expressed by highly variable and non-stationary reservoir properties. The 3D organization of these reservoir properties depends on the parameters, which drove the karst development (fracture network, sequence stratigraphy, hydraulic gradient). This paper presents an integrated methodology for the evaluation of the karst network and its 3D modeling in single porosity models. In a Middle-East reservoir, a synthesis of dynamic data shows a clear dual porosity/permeability behavior, which is explained both by the core description and the well test interpretation. The karst network is proved to be driven by an early diagenesis along sequence boundaries. The 3D organization of the karst network is assessed from the integration of sedimentological/structural models and dynamic data. Fine gridded models are achieved before the full field simulation to evaluate matrix-drains exchanges. Results from these sensitivity models enable to input realistic reservoir properties in the coarse full field. A methodology for preservation of dual permeability behavior through downscaling process is presented. The reservoir layering is defined in order to preserve the key heterogeneity in the coarse model, moreover, homogeneous equivalent petrophysical parameters are assigned to high permeability layers. A specific modeling of permeability, saturation and Rock-type in karstic layers is performed. The matching of the production history is obtained without any drastic changes in reservoir properties; that confirms the distribution of the karst network. Introduction Building 3D carbonate reservoir models for flow simulation constitutes a very challenging issue in petroleum industry. In these reservoirs, heterogeneity is often driven both by the depositional and diagenetic patterns. When diagenesis processes occur early, stochastic simulations are usually required to resolve these objectives of modeling through the simulation of associated depositional/diagenetic facies prior to the simulation of petrophysics 1,2,3,4. However, in karstic reservoir, the effects of diagenesis strongly modify the initial geological image and initial reservoir properties. The development of the karstic system (epikarst+drains) significantly overprints depositional features. The evaluation of the dual permeability is the key to assess a good representation of flow units, after a classic facies modeling. In this paper, a methodology applied to an oil field in the Middle East is proposed for evaluation of the karst network through a geological modeling prior a reservoir simulation. After a field overview, 3 main steps are described: diagnosis of dual porosity using dynamic data, characterization of the key heterogeneity and 3D reservoir modeling. Then, a methodology for preservation of dual permeability behavior through downscaling process is presented together with the main results of history matching. GUIRIEL field overview General Context. The GUIRIEL oil field, located in the Middle East offshore, was discovered in 1989. The trap consists in Southeast monocline with numerous lineaments and a main unconformity at the top reservoir (Base Laffan erosion). This closure over unconformity with significant hiatus in Turonian (allowing karstification), is sealed by Laffan marine shales (Santonian). General Context. The GUIRIEL oil field, located in the Middle East offshore, was discovered in 1989. The trap consists in Southeast monocline with numerous lineaments and a main unconformity at the top reservoir (Base Laffan erosion). This closure over unconformity with significant hiatus in Turonian (allowing karstification), is sealed by Laffan marine shales (Santonian).