Understanding the (co)variance in petrophysical properties of CO2 reservoirs comprising sedimentary architecture. (August 2016)

• Record Type: Journal Article
• Authors: Ritzi, Robert W.; Freiburg, Jared T.; Webb, Nathan D.
• Is Part Of: International journal of greenhouse gas control. Volume 51(2016:Aug.)
• Page Start: 423
• Page End: 434
• Publication Date: 2016-08
• Subjects: CO2 geo-sequestration -- Reservoir heterogeneity -- Fluvial architecture -- Analysis of variance -- Mt. Simon Sandstone; Greenhouse gases -- Environmental aspects -- Periodicals; Air -- Purification -- Technological innovations -- Periodicals; Gaz à effet de serre -- Périodiques; Gaz à effet de serre -- Réduction -- Périodiques; Air -- Purification -- Technological innovations; Greenhouse gases -- Environmental aspects; Periodicals; 363.73874605
• DOI: 10.1016/j.ijggc.2016.05.001
• Languages: English
• ISSNs: 1750-5836

Abstract

Highlights: Heterogeneity in petrophysical attributes is linked to sedimentary architecture. The (co)variance in petrophysical attributes is decomposed, with a new method, according to textural sedimentary facies. Parsimonious models for petrophysical parameters, linked to facies models, result. The method is illustrated with highly resolved data from the lower Mt. Simon Sandstone. Abstract: 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.