Geoscience Reference
In-Depth Information
a
N/G
res
= 0.36
N/G
res
= 0.88
N/G
res
= 0.83
+146%
+131%
2%
kh
net
= 371md
kh
net
= 826md
kh
net
= 336md
-55%
-60%
kh
simulator
= 304md
kh
true
= 298md
k (md)
4504
Thin-bed
data
Logging
Filter
Blocking
Filter
4505
4506
N/G
res
> 1md
0.2m ave
0.5m grid
b
N/G
logs
= 0.36
N/G
res
= 0.365
Upscale
k
v
/k
h
≈
0.0004
kh
true
= 298md
Upscale
kh
upscaled
= 170md
k
geom
=74 < k
est
< k
arith
=299
k (md)
4504
Data
integration
Thin-bed
data
kh =
f(logs)
Upscaled
blocks
4505
4506
0.5m grid
4507
Fig. 3.36
Application of (
a
) the N/G approach and (
b
) the total property modelling approach to an example thin-bed
permeability dataset
discrete log by blocking the thin-bed data set
(using values for net and non-net reservoir).
The discrete-log N/G
res
estimate is quite accu-
rate, as smoothing has not been applied.
Upscaled cell values (k
h
and k
v
) are then
estimated using functions proposed by Ringrose
et al. (
2003
) for permeability in heterolithic bed-
ding systems (described in Sect.
3.6
below).
These functions represent the numerical (single-
phase) upscaling step in the total-property-
modelling workflow. The TPM approach
preserves both an accurate estimate for N/G
res
