Sub-Micron Digital Image Analysis (BIBSEM-DIA), Pore Geometries and Electrical Resistivity in Carbonate Rocks
Norbisrath, Jan H.; Eberli, Gregor; Weger, Ralf J.; Verwer, Klaas; Urai, Janos; Desbois, Guillaume; Laurich, Ben
Assessment of electrical flow properties in heterogeneous carbonate rocks with pore sizes spanning several orders of magnitude requires a multi-scale investigation of the pore system. A new technique using Digital Image Analysis (DIA), ranging from millimeter to nanometer scale, allows for imaging and quantification of the sub-micron pore space in unprecedented detail. To capture the nanometer-scale pores, a new method of Broad-Ion-Beam (BIB) milling is used that produces true 2-D cross-sections for subsequent SEM image mosaic acquisition (BIBSEM).
Four samples were chosen from different depositional and diagenetic environments to compare their distinct microstructures. All samples have similar porosity (16%) for the sake of comparability. Electrical resistivity was measured on all samples; pore size distribution was analyzed with MICP methods, and samples were investigated for their macropore structure with DIA from Optical Light Microscopy (OLM) on epoxy impregnated thin sections. For imaging micropores, the sample surfaces were milled down to nanometer-precision flatness with a JEOL SM-09010 BIB cross-section polisher. The large BIB surfaces (up to 2 square mm) are investigated at 5000x and 15000x magnification (resolution: 58.6 nm/pixel and 18.5 nm/pixel, respectively), and acquired BIBSEM mosaics are composed of up to 570 images each. Combining results from BIBSEM-DIA with OLM-DIA yields a multi-scale analysis.
The ultra-high-resolution BIBSEM image mosaics reveal the diverse microarchitectures of the different rock types, allowing for qualitative estimation of flow properties. The most interesting finding from quantitative DIA is that Pore Size Density Distribution (PSDD) follows a power law when pore sizes are normalized to bin width and area and plotted on log-log scale. This implies that pore densities at all scales as well as the Total Pore Density (TPD) can be modeled from DIA at a single resolution. Furthermore, combining conventional image analysis with spatial analysis using GIS software quantifies pore network connectivity (Nearest Neighbor Connectivity Factor; NNCF). The hypothesis is that the closer the next pore, the more likely a connection exists. The results of the multi-scale DIA display a good correlation between calculated values for TPD and NNCF and electrical flow properties of the rock, corroborating earlier studies that electrical flow properties are strongly influenced by pore density and connectivity.
AAPG Search and Discovery Article #90163©2013AAPG 2013 Annual Convention and Exhibition, Pittsburgh, Pennsylvania, May 19-22, 2013