Graphical Analysis of Laminated Sand-Shale Formations in the Presence of Anisotropic Shales

Abstract

Laminated sand-shale models with anisotropic shales have been discussed extensively. The interpretation methods are written in elaborate mathematical equations. However, there has not been a clear procedure to determine key parameters such as shale anisotropy, to guide the choice of multiple solutions, and more important, to recognize the circumstances in which a solution is robust or sensitive to errors. This paper explains the analytical solutions through interactive crossplots. We believe a graphical crossplot gives better insights into petrophysics than a set of equations, while interactivity allows instant visualization of the solutions, thereby helping the petrophysicist in the most effective way. The objectives of the graphical analysis are 1) to determine the shale anisotropy parameters and whether it is necessary to create multiple zones, 2) to define the crossplot region boundaries where each analytical solution is applicable, 3) to illustrate the effect of data outliers on the results, and 4) to quickly perform sensitivity tests. Pay region and non-pay region are subsequently defined in the crossplot, which allows a visual assessment of the hydrocarbon potential of the thin-bed sections from the crossplot. Examples are shown in which the shale anisotropy is the same or greater than the anisotropy of the thin-bedded sections, where initially analysis of such sections seems hopeless. Another example shows the need to define multiple anisotropic shales where the challenge is to determine the number of shale points and their respective anisotropy. A further example shows no 100% shale point to pick parameters directly. The graphical method allows successful interpretation of the resistivity anisotropy data under these difficult conditions. The results are corroborated with imaging logs, nuclear magnetic resonance results and core data. It is also found that the graphical analysis is a valuable tool to quality control (QC) the resistivity anisotropy data.