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