Mukerji, Tapan1, Manika Prasad1
(1) Stanford University, Stanford, CA
ABSTRACT: Analysing Acoustic Microscope Images to Estimate Textural Scales and Anisotropy in Kerogen Shales
Microstructural characteristics of organic rich shales can give important insights on the maturation processes. Since changes in shale texture and in hydrogen content are closely linked with kerogen maturity, a correlation between them would enhance methods for detecting and prospecting of kerogen rich shales. The problem is complicated by the fact that the intrinsic anisotropic texture of the shales is enhanced by kerogen distribution in the shales.
We apply different statistical methods for characterizing heterogeneity and textures from scanning acoustic microscope (SAM) images of shale microstructures. We analyzed SAM images from Bakken, Bazhenov, and Woodford shale. Textural heterogeneity was quantified by the statistical coefficient of variation. Textural anisotropy was quantified using spatial autocorrelation functions. Radial profiles of the autocorrelation function along azimuths ranging from 0o to 180o were computed, and the correlation length estimated at each azimuth. The texture anisotropy was quantified by the anisotropy ratio (AR) defined as the ratio between the maximum and minimum correlation lengths over all azimuths. Our analysis showed a small positive correlation between the degree of heterogeneity and the mean spatial correlation length of the microstructure. The textural anisotropy ranges from 10% to 80%. A singular value decomposition (SVD) spectral analysis showed that the shale microstructures have characteristics in common with fractal stochastic images. We also obtain a correlation between maturity and textural heterogeneity. The textural heterogeneity increases with increasing maturity (decreasing kerogen content), while there seems to be a general decrease in textural anisotropy with maturity.
AAPG Search and Discovery Article #90026©2004 AAPG Annual Meeting, Dallas, Texas, April 18-21, 2004.