Scientific evaluation of CO 2 geo-sequestration requires fundamentally understanding the processes associated with CO 2 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
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