Stochastic Earth Modeling That Integrates All Subsurface Uncertainties
In the previous pages, we have focused on the use of geostatistical conditional simulation for 3D heterogeneity modeling. We saw that GCS provided a satisfactory solution to the problem of generating realistic 3D representations of the subsurface. We also saw that, thanks to GCS, we were able to generate not one, but a large number of realizations, all of which were compatible with the well data, the a priori geostatistical constraints (histogram and variogram), and, in many cases, the seismic data. The variability from one realization to another was a representation of the remaining uncertainty left after constraining our models by all this input information. We will now discuss how this quantification of uncertainties can be applied to all parameters of the earth model to lead to uncertainties attached to gross-rock volume, oil-in-place, reserves, or production profiles (Fig. 6-1). But why should we be interested in quantifying uncertainties?
An uncertainty calculation is a useless exercise if no decision making is attached to it (Fig. 6-2). But which kinds of decisions shall we be able to support with an uncertainty calculation? Fig. 6-3 lists some of the most important decisions geoscientists are led to support with their uncertainty studies (see examples in Tyler et al., 1996 and Charles et al., 2001). Usually, these decisions are related to a significant financial investment. Instead of one production profile, a typical uncertainty study will produce a family of production profiles or the field reserves