The Rock Model - Reservoir Model Design - page 15

Fig. 2.1 To model rocks, or not to model rocks? Upper image : porosity model built directly from logs; middle image :a
rock model capturing reservoir heterogeneity; lower image : the porosity model rebuilt, conditioned to the rock model

and many reservoirs do not require rock models.
Figure 2.1 shows a porosity model which has
been built with and without a rock model. If the
upper porosity model is deemed a reasonable
representation of the field, a rock model is not
required. If, however, the porosity distribution is
believed to be significantly influenced by the
rock contrasts shown in the middle image, then
the lower porosity model is the one to go for.
Rock modelling is therefore a means to an end
rather than an end in itself, an optional step
which is useful if it helps to build an improved
property model.
The details of rock model input are software-
specific and are not covered here. Typically the
model requires specification of variables such as
sand body sizes, facies proportions and reference
to directional data such as dip-logs. These are
part of a standard model build and need consid-
eration, but are not viewed here as critical to the
higher level issue of model design. Moreover,
many of these variables cannot be specified

precisely enough to guide the modelling: rock
body databases are generally insufficient and
dip-log data too sparse to rely on as a model
foundation. Most critical to the design are the
issues identified below, mishandling of which is
a common source of a poor model build:
￿ Reservoir concept - is the architecture
understood in a way which readily translates
into a reservoir model?
￿ Model elements - from the range of observed
structural components and sedimentological
facies types, has the correct selection of
elements been made on which to base the
model?
￿ Model Build - is the conceptual model car-
ried through intuitively into the statistical
component of the build?
￿ Determinism and probability - is the bal-
ance of determinism and probability in the
model understood, and is the conceptual
model firmly carried in the deterministic
model components?