Geoscience Reference

In-Depth Information

This tendency to introduce bias when

upscaling from a fine-scale well-log to the reser-

voir model can lead to significant errors. Similar

blocking errors are introduced for the case of

facies modelling (Fig.
3.31
) - such that modelled

volume fractions of a sandy facies can differ from

the well data (due to blocking) in addition to bias

related to modelling net sand properties. The

errors can be contained by careful tracking of the

correct N/G value in the modelling process.

The common assumption in reservoir flow

simulation is that the N/G ratio is used to factor

down the cell porosity and the horizontal perme-

ability, k
h
, in order to derive the correct inter-cell

transmissibility. However, no explicit N/G factor

is generally applied to the vertical permeability,

k
v
, as it is assumed that this is independently

assigned using a k
v
/k
h
ratio. This is illustrated

in Fig.
3.32
. A potential error is to double calcu-

late the N/G effect, where, for example the geol-

ogist calculates a total bock permeability of

600 mD and the

Continuous log

Discrete log

Upscaled log

f

f

f

N/G
sand

0.55

0.85

0.60

0.25

0.40

Sand flag

Cement flag

Fig. 3.30
Upscaling of net-sand logs

reservoir

engineer

then

is likely to change as a function of scale between

well data and full-field reservoir simulation

model. This is illustrated in Fig.
3.30
for a

simplified workflow. There are several important

biasing factors which tend to occur

multiplies this again by 0.6 to give k
x
¼

360 mD.

When using the N/G approach the main

products from the geological model to the reser-

voir simulation model are as follows:

(i) Model for spatial distribution of N/G;

(ii) Net sand properties, e.g., ø, k
h,
S
w
;

(iii) Multi-phase flow functions for net-sand,

e.g., k
ro
(S
w
);

(iv) k
v
/k
h
ratios to be applied to each cell;

(v) Information on stratigraphic barriers and

faults.

The N/G ratio approach is widely used and can

be consistently and successfully applied through

the re-scaling process - from well data to geologi-

cal model to reservoir-simulation model. How-

ever, significant errors can be introduced and care

should be taken to ensure that the model correctly

represents the underlying assumptions made.

in this

process:

Blocked sand intervals are likely to contain

non-sand, and the converse (blocking refers to

the process of creating a discrete parameter

from a higher frequency dataset).

Upscaling will bias the volume fractions in

favour of the majority volume fraction. This

is illustrated in Fig.
3.30
, where for example

in the top layer the N/G
sand
increases from

0.55 to 0.75 to 1.0 in the transition from con-

tinuous log to discrete log to upscaled log.

Cemented sand is not the same as shale, and

will typically be included as part of the shale

fraction (unless care is taken to avoid this).

Since we require net-sand properties we must

filter the data accordingly. That is, only the

fine-scale net-sand values for k and
ϕ
are

included in the upscaled net-sand values.

We have to assume something about the non-

net sand volume - typically we assume it has

zero porosity and some arbitrary low (or zero)

value for vertical permeability.

3.5.3 Total Property Modelling

Total Property Modelling refers to an approach

where all rock properties are explicitly modelled

and where the cut-offs are only applied after

modelling (if at all). In this way cut-offs, or net to

gross criteria, are not embedded in the process. This