Thin, irregularly shaped surfaces such as clay drapes often have a major
control on flow and transport in heterogeneous porous media. Clay drapes are often
complex, curvilinear three-dimensional surfaces and display a very complex spatial
distribution. Variogram-based stochastic approaches are also often not able to describe
the spatial distribution of clay drapes since complex, curvilinear, continuous,
and interconnected structures cannot be characterized using only two-point statistics.
Multiple-point geostatistics aims to overcome the limitations of the variogram.
The premise of multiple-point geostatistics is to move beyond two-point correlations
between variables and to obtain (cross) correlation moments at three or more locations
at a time using training images to characterize the patterns of geological heterogeneity.
Multiple-point geostatistics can reproduce thin irregularly shaped surfaces
such as clay drapes, but this is often computationally very intensive. This paper describes
and applies a methodology to simulate thin, irregularly shaped surfaces with
a smaller CPU and RAM demand than the conventional multiple-point statistical
methods. The proposed method uses edge properties for indicating the presence of
thin irregularly shaped surfaces. Instead of pixel values, edge properties indicating
the presence of irregularly shaped surfaces are simulated using snesim. This method
allows direct simulation of edge properties instead of pixel properties to make it possible
to perform multiple-point geostatistical simulations with a larger cell size and
thus a smaller computation time and memory demand. This method is particularly
valuable for three-dimensional applications of multiple-point geostatistics.