High-Resolution Mapping of the Distribution and Connectivity of Organic Matter in Shales

Abstract

Abstract Organic matter is an important component of shale oil and gas resource plays and can have a profound effect on the properties of shale. Porosity in the organic matter provides potential storage for hydrocarbons, and depending on the connectivity of the organic matter, possible connected pathways for hydrocarbon flow. In addition, from a completions and seismic mapping perspective, the distribution of organic matter will affect the elastic properties of shale as well as the elastic anisotropy. Because of the heterogeneity of shales and micron to sub- micron size of the organic matter, mapping changes in organic distribution with sufficient resolution to capture a statistically meaningful sample of the organic matter has proven difficult. Previous work has used a combination of scanning electron microscopy (SEM) with scanning acoustic microscopy (SAM), x-ray computed tomography (XCT), or optical thin sections to map the distribution of organic matter. All these techniques have limitations in the sense that they either provide large area mapping at low resolution or small area mapping at high resolution but not large areas with high resolution. With the advent of large area ion beam milling and automated high-resolution SEM imaging and stitching, a seven order of magnitude size range can now be spanned allowing the distribution of organic matter over centimeter square areas to be mapped with nanometer resolution. Utilizing this technique, the distribution and connectivity of organic matter over extended contiguous sections of core from the Barnett and Wolfcamp Shales were mapped at one inch intervals. Variations in total organic content between cores and within the same core were measured in the lab, and these variations are compared to the SEM results. In addition, the shape and orientation of the organic matter was analyzed. These measurements aid in placing limits on the scale of variation in organic matter distribution in shale and represent the first crucial step in attempting to upscale SEM data to core petrophysical measurements and potentially to log-scale measurements.