Conditional Simulation: Geostatistical Tool Applied to Athabasca Oil-Sands Deposit: ABSTRACT

Abstract

Geostatistical modeling of reservoir variability in the Athabasca oil-sands deposit prior to either surface or in-situ mining can provide valuable information to guide the extraction process. Geologic and engineering characteristics (variables), such as elevations of bitumen-saturated and waste (barren) zones, and percentage bitumen saturation, porosity, and permeability, have a controlling effect on recovery methods. Each geologic variable is considered to be a particular realization of a random function defined within a geologic domain. This function can be inferred from available data (boreholes) under the hypothesis of stationarity. Other realizations (models) of the same random function can then be generated using the technique of conditional simulation, which is End_Page 846------------------------------ a combination of kriging and simulated correlated variables. The statistical models of geologic variables so produced are in conformity with the histogram, variogram, and actual data values, and most important, they mimic spatial variability between sampled locations. The key factor in geologic applications of geostatistics is the translation of geologic reality into mathematical abstraction. Each random statistical function is a function of the physical processes that produced the deposit, which processes in turn varied in both space and time. The deposit under study has been divided into seven domains based on the best available geologic model, and different random functions established for each variable in each domain. Three-dimensional models describing the spatial fluctuation of elevations and bitumen saturations were produced and stored as grids having 25 m (82 ft) vertical and 1 m (3 ft) horizontal resolution. These models will be used to develop strategies for mine planning. End_of_Article - Last_Page 847------------