Geoscience Reference
In-Depth Information
Fig. 2.40
Vertical
probability trends; each
colour represents a
different reservoir element
and the probability
represents the likelihood of
that element occurring at
that point in the cell
stratigraphy
(
blue
¼ mudstone;
yellow
¼ sandstone)
of the reservoir (rarely the case and never prov-
able) this is not a problem, but the modeller
should be aware that hydrocarbon volumes are
effectively being adjusted up and down away
from well control. The adjustments therefore
require justification which comes, as ever, from
the underlying conceptual model.
3. The 2D map is hand-edited to represent the
desired concept, with most attention being paid
to the most poorly sampled areas (in the exam-
ple shown, the trend grid is also smoothed - the
level of detail in the trend map should match the
resolution of the sand distribution concept);
4. The trend map is input to, in this case, an SIS
algorithm for rock modelling;
5. As a check, the interval average net-to-gross
is backed-out of the model as a map and
compared with the concept. The map shows
more heterogeneity because the variogram
ranges have been set low and the model has
been tied to the actual well observations; the
desired deterministic trends, however, clearly
control the overall pattern.
The influence of the trend on the model is
profound in this case as the concept is for the
sand system to finger eastwards into a poorly
drilled, mud-dominated environment. The oil
2.7.4.2 Horizontal Trends
Horizontal trends are mostly simply introduced
as 2D maps which can be applied to a given
interval. Figure
2.41
shows the application of a
sand trend map to a low net-to-gross system
following the steps below:
1. Sand elements are identified in wells based on
core and log interpretation;
2. A net-to-gross (sand) value is extracted at
each well and gridded in 2D to produce a
map illustrating any sand trend apparent
