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A subsurface reservoir model is a computer based representation of petrophysical parameters such a porosity, permeability, fluid saturation, etc. Given that direct measurement of these parameters is limited to a few wells it is necessary to extrapolate their distribution. As geology is a first order control on petrophysics, it follows that an understanding of facies and their distribution is central to predicting reservoir quality and architecture. The majority of reservoir modelling systems used for the subsurface are based on correlation of seismically-derived surfaces to define reservoir zones. Well data are then used to define further, sub-seismic scale horizons and determine the zone properties which are represented in grid cells. Understanding the distribution of both sub-seismic surfaces and potential heterogeneous geology between them remains a significant challenge. Furthermore as the typical grid cell size is c. 50-200 m2 it is challenging to incorporate small-scale heterogeneities. It is critical, therefore, to use realistic values for both key stratigraphic horizons and internal facies distributions. Depositional facies is a fundamental control on petrophysics. However, facies scale heterogeneities are not resolvable using current seismic methods, and well data provide little or no data on 3D geometries beyond the well bore. Studies of modern sedimentary events can give some indication of the link between depositional processes and facies distribution (e.g., Kenyon et al., 1995); however preserved depositional architecture is also strongly controlled by changes in accommodation through time (Jervey, 1988). Laboratory-based experiments (e.g., Kneller & Buckee, 2000) and process-based modelling (e.g. Aigner et al., 1989; Peakall et al., 2000) further illustrate the link between depositional mechanism and facies architecture. However, such models are typically on a scale that is far smaller than the typical field and are more applicable to upscaling stu

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