Geoscience Reference
In-Depth Information
Horizon interpretations may be extended
down fault planes (i.e. the fault is not
identified independently on each horizon, or
not identified at all)
Faults may be interpreted on seismic noise
(artefacts).
Although models made from such 'raw' seis-
mic interpretations are honest reflections of that
data, the structural representations are incom-
plete and, it is argued here, a structural interpre-
tation should be overlain on the seismic outputs
as part of the model design. To achieve this, the
workflow similar to that shown in Fig.
2.4
is
recommended.
Rather than start with a gridded framework
constructed directly from seismic interpretation,
the structural build should start with the raw,
depth-converted seismic picks and the fault
sticks. This is preferable to starting with horizon
grids, as these will have been gridded without
access to the final 3D fault network. Working
with pre-gridded surfaces means the starting
inputs are smoothed, not only within-surface
but, more importantly, around faults, the latter
tending to have systematically reduced fault
displacements.
A more rigorous structural model workflow is
as follows:
1. Determine the structural concept - are faults
expected to die out laterally or to link? Are
en
echelon
faults separated by relay ramps? Are
there small, possibly sub-seismic connecting
faults?
2. Input the fault sticks and grid them as fault
planes (Fig.
2.4a
)
3. Link faults into a network consistent with the
concept (1, above, also Fig.
2.4b
)
4. Import depth-converted horizon picks as
points and remove spurious points, e.g. those
erroneously picked along fault planes rather
than stratigraphic surfaces (Fig.
2.4c
)
5. Edit the fault network to ensure optimal posi-
tioning relative to the raw picks; this may be an
iterative process with the geophysicist, particu-
larly if potentially spurious picks are identified
6. Grid surfaces against
2.3.2 Stratigraphic Data
There are two main considerations in the selec-
tion of stratigraphic inputs to the geological
framework model:
correlation
and
hierarchy
.
2.3.2.1 Correlation
In the subsurface, correlation usually begins with
markers picked from well data -
well picks
.
Important information also comes from correla-
tion surfaces picked from seismic data. Numer-
ous correlation picks may have been defined in
the interpretation of well data and these picks
may have their origins in lithological, biostrati-
graphical or chronostratigraphical correlations -
all of these being elements of sequence stratigra-
phy (see for example Van Wagoner et al.
1990
;
Van Wagoner and Bertram
1995
). If multiple
stratigraphic correlations are available these
may give surfaces which intersect in space.
Moreover, not all these surfaces are needed in
reservoir modelling. A selection process is there-
fore required. As with the structural framework,
the selection of surfaces should be made with
reference to the conceptual sketch, which is in
turn driven by the model purpose.
As a guideline, the 'correct' correlation lines
are generally those which most closely govern
the fluid-flow gradients during production. An
exception would be instances where correlation
lines are used to guide the distribution of reser-
voir volumes in 3D, rather than to capture correct
fluid flow units.
The choice of correlation surfaces used
hugely influences the resulting model architec-
ture, as illustrated in Fig.
2.5
, and in an excellent
field example by Ainsworth et al. (
1999
).
2.3.2.2 Hierarchy
Different correlation schemes have different
influences on the key issue of hierarchy, as the
stratigraphy of most reservoir systems is
inherently hierarchical (Campbell
1967
). For
example, for a sequence stratigraphic correlation
scheme, a low-stand systems tract might have a
length-scale of tens of kilometres and might con-
tain within it numerous stacked sand systems
the fault network
(Fig.
2.4d
).
