MPG Simulation of Facies Thicknesses Interpreted through Sequence Stratigraphy – Application on a Carbonate Outcrop

Outcrop models can provide important information about reservoir architecture and heterogeneity. However, geological information from outcrop, because of its great variety and complexity, cannot be integrated to its fullest extent using traditional geostatistics. The conventional variogram-based modeling techniques typically fail to capture complex geological structures. Multiple-point geostatistics encompasses a set of an innovative modeling technique that performs the simulation starting from a training image, a 3D conceptual visual representation of how heterogeneities are believed to be distributed in the actual reservoir. The training image forms a gateway for geological expertise and interpretation to be quantitatively used in reservoir modelling. Training images can be constructed using object-based simulation or using outcrop data. The latter will be the topic of investigation in this paper. This paper presents an application of simpat, a multiple-point stochastic simulation method for generating reservoir facies models by capturing the complex facies series of a carbonate outcrop and anchoring them to subsurface well data. The outcrop consists of a complex depositional sequence of mound and lobe bodies with complex spatial relationships. The idea is to generate reservoir models that reflect the observed geological complexity, yet at the same time are constrained to any available reservoir data. In order to reproduce this complex architecture in such models and to make explicit use of the sequence stratigraphic depositional information, the depositional bodies were not simulated directly but with a new approach relying on the simulation of facies thicknesses interpreted through sequence stratigraphy. The main idea of this new approach is to separate thickness and facies information into two different yet coupled 3D training images, then to rely on the capabilities of simpat to jointly simulate these two properties. This approach can easily integrate complex information regarding bodies’ geometry and sequence stratigraphy and it has the potential to be applied to several different geological depositional system.