Understanding the (co)variance in petrophysical properties of CO2 reservoirs comprising sedimentary architecture

Scientific evaluation of CO2 geo-sequestration requires fundamentally understanding the processes associated with CO2 movement and trapping within reservoirs. Fully understanding these processes requires understanding a diverse set of heterogeneous geologic properties that vary at different scales. Establishing basic relationships between the sedimentary architecture in these reservoirs and the variation in petrophysical attributes that can affect plume dynamics and residual trapping is an important step toward understanding reservoir processes. Highly-resolved data sets at well-characterized research sites can be used to establish these basic relationships. In this vein, the sample (co)variance for petrophysical attributes can be quantitatively and deterministically decomposed according to a hierarchy of textural factors that vary among sedimentary facies. A new hierarchical method for the analysis of (co)variance of petrophysical attributes is adapted for this purpose. The results quantify the magnitude that each factor contributes to the (co)variance, and thus clarify their relative contribution within the factor hierarchy. This leads to a basic understanding of how the sample (co)variance arises within the sedimentary architecture, and of which factors are important in defining it. Such an understanding aids in developing parsimonious reservoir simulation models. The method is illustrated using a highly-resolved data set from the lower Mt. Simon Sandstone reservoir.