Upscaling Flow Properties - Reservoir Model Design - page 129

Fig. 4.17 The pore scale -
example thin section of
pores in a sandstone
reservoir (Statoil image
archive, # Statoil ASA,
reproduced with
permission)

Pixed-based modelling approaches (e.g. SGS,
SIS) can be applied at pretty-much any scale,
whereas object-based modelling approaches
will tend to have very clear associations with
pre-defined length scales. In both cases the
model grid resolution needs to be fine enough
to explicitly capture the heterogeneity being
represented in the model. Process-based
modelling methods (e.g. Rubin 1987 ; Wen et al.
1998 ; Ringrose et al. 2003 ) are particularly
appropriate for capturing the effects of small-
scale geological architecture within a multi-
scale modelling framework.
In the following sections we look at some key
questions the reservoir modelling practitioner
will need to address in building multi-scale res-
ervoir models:
1. How many scales to model and upscale?
2. Which scales to focus on?
3. How to best construct model grids?
4. Which heterogeneities matter most?

behaviour. Numerical modelling at the pore scale
has been widely used to better understand perme-
ability, relative permeability and capillary pres-
sure behaviour for representative pore systems
(e.g. Bryant and Blunt 1992 ; Bryant et al. 1993 ;
McDougall and Sorbie 1995 ; Bakke and Øren
1997 ; Øren and Bakke 2003 ). Most laboratory
analysis of rock samples is devoted to measuring
pore-scale properties - resistivity, acoustic
velocity, porosity, permeability, and relative per-
meability. Pore-scale modelling allows these
measured flow properties to be related to funda-
mental rock properties such as grain size, grain
sorting and mineralogy. However, the applica-
tion of pore-scale measurements and models in
larger-scale reservoir models requires a frame-
work for assigning pore-scale properties to the
geological concept. We do this by assigning flow
properties to lamina-scale, lithofacies-scale or
stratigraphic-scale models. This can be done
quite loosely, with weak assumptions, or system-
atically within a multi-scale upscaling hierarchy.
Statistical methods for representing the spatial
architecture of geological systems were covered
in Chap. 2 . What concerns us here is how we
integrate geological models within a multi-scale
hierarchy. This may require a re-evaluation of
the scales of models needed to address different
scale transitions.

4.3.2 How Many Scales to Model
and Upscale?

Despite the inherent complexities of sedimentary
systems, dominant scales and scale transitions can
be identified (Fig. 4.18 ). These dominant scales