AAPG Bulletin, Vol.87, No.12, 1851-1868, 2003
Geostatistical models for shales in distributary channel point bars (Ferron Sandstone, Utah): From ground-penetrating radar data to three-dimensional flow modeling
The hydraulic effects of shales on fluid flow in marine-influenced lower delta-plain distributary channel deposits are investigated using borehole outcrop and ground-penetrating radar data from the Cretaceous age Ferron Sandstone at Corbula Gulch in central Utah, United States. The instantaneous radar amplitude and gamma-ray counts are linearly correlated at well locations (rho = 0.84). This correlation is exploited to model shale occurrence throughout a 150 x 110 x 12-m-thick (492 x 361 x 39.4 ft) radar survey volume. Variograms of shale occurrence computed from radar data have a correlation range of 5 - 8 m (16.4 - 26.2 ft) with no significant areal anisotropy in shale dimensions. The radar-derived variograms are similar to variograms computed from outcrop data. Sequential Gaussian simulations create shale distributions on variably dipping accretionary surfaces. Flow simulations examine the effects of flow direction, variogram range, and shale coverage fraction on breakthrough time, sweep efficiency, and upscaled permeability. The flow simulations compare homogeneous and stochastic geologic models flow in three, coordinate directions, eight geostatistical parameter combinations, and five realizations for each combination of parameters. The effects of shales are modest compared to predictions based on earlier, two-dimensional studies of shales. Upscaled permeability is reduced by 2 -11% (horizontally) and 42% (vertically). Compared to homogeneous models, the time to breakthrough is reduced by less than 5%. 11 The effects on sweep efficiency are smaller. These results imply that, simple models of point-bar accretionary shales may suffice for modeling analogous deposits in reservoirs. If detailed shale models are needed, the geostatistical parameters presented in this article can be used as a starting point for stochastic reservoir modeling.