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Fig. 6.17 Tidal deltaic sand log shown alongside the corresponding seismic section, where only the thickest sands are
evident on seismic
bad reservoir facies becomes quite a challenge.
Furthermore, the integration of thin-bedded well
logs with seismic data in such units is simply
difficult (Fig. 6.17 ).
In reservoir modelling, it is conventional to
model the reservoir (the foreground facies)
and to neglect the non-reservoir (the background
facies), but in heterolithic, tide-dominated
reservoir systems, there is often a gradation
between reservoir and non-reservoir. In tidal
deltaic systems, it is therefore essential to
represent both background and foreground
facies explicitly (e.g. Brandsæter et al. 2001a , b ,
2005 ).
It was in this context that many of the
concepts for total property modelling ( cf . Fig. 3.
33 ) and multi-scale modelling ( cf . Fig. 4.1 ) were
developed, and when working these fields it is
quickly evident that multi-scale modelling is not
optional for tidal-delta systems - it is essential.
Some form of effective flow property has to
be estimated for the heterolithics, because neither
core data, well logs or seismic give direct
indicators of the presence of sandstone or high
quality reservoir zones. There are many possible
approaches to multi-scale modelling in such
systems, but as a guide, Fig. 6.18 illustrates the
workflow for upscaling heterolithic tidal deltaic
reservoir systems, developed by Nordahl et al.
( 2005 ) and Ringrose et al. ( 2005 ). Core data is
interpreted, ideally with the aid of near-wellbore
models to allow rescaling of core and wireline
logs to the lithofacies REV. Rock property
models (at the lithofacies REV) are then used to
estimate flow functions. These could be perme-
ability as a function of mud/sand ratio [e.g. k v ¼
f(V m )] as shown in Fig. 6.18 , or any other useful
function such as acoustic properties as a func-
tion of porosity or water saturation as a function
of k h . Upscaled flow functions are then applied to
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