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of simple trend (vertical or horizontal) could “de-trend" the data, resulting in inadequate
solutions and further complicate the computation and interpretation of variograms. The
next-generation earth modeling reintroduces a graphical method that generates individual
LPCs for each well in the field with the ability to create pseudo-wells to invoke a geological
trend that honors the conceptual depositional model.
a) b)
Fig. 4. Lithotype proportion mapping: a) example of a map view that uses existing
proportion curves, with the ability to create pseudo-wells and impose a trend to honor the
conceptual model, b) example of vertical proportion curves organized into vertical
proportion matrix (VPM), describing how the facies behave vertically and laterally over the
area of the reservoir.
When displayed in the map view (Fig. 4a), the LPCs allow for a quick QC of the vertical
variation of the facies distribution and proportions, even before creating the facies model.
Editing and copy/move functionality allows the modeler to impose an interpretation to
better control trends. The lithotype proportion map (LPM), created from the VPCs, literally
consists of hundreds of high resolution trend maps accounting for vertical and lateral non-
stationarity (Fig. 4b).
2.3 Geologically-driven facies modeling
Facies simulation algorithms, commonly used in earth modeling suffer from a variety of
challenges when trying to generate models based on often sparse real data, particularly
when attempting to honor depositional facies boundary conditions and proportions, capture
depositional overprinting or accounting for geological non-stationarity. For example, the
Sequential Indicator Simulation (SIS) (Caers, 2005), lacks the ability to control facies
boundary conditions, the Truncated Gaussian Simulation (TGS) (Caers, 2005), provides for
only simple facies transitional boundaries and while Object (also termed Boolean)
Simulation (OS) can manage most non-overprinted complex facies sets, it is unstable in the
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