3
D
study of pore space morphology of the shales
Authors: Mikhutkin Alexey , Pichkur Evgeniy , Karateev Igor , Spasennykh Mikhail , Vasiliev Alexander 
Published: December 2016

One of the goals of gas and oil shales study is the analysis of multiscale porosity. Pores are located in the areas, containing organic compounds, particularly kerogen, and in the mineral matrix. The analysis of porosity is required for the characterization of geological cores and development of hydrocarbon extraction methods. The parameters, which have to be determined, are pore size distribution, total pores volume and their connectivity. Different methods are used for these investigations and the most popular are the mercury intrusion porosimetry and the X‐ray tomography. However, these methods are limited in space resolution and do not reveal completely the pore space at the micro‐ and nanoscale. Nowadays one of the frequently used methods of the porous material characterization is the scanning electron microscopy (SEM) combined with the focused ion beam (FIB), so‐called “slice‐and‐view” method: it allows to reconstruct the three‐dimensional (3D) microstructure of a sample, in particular its porous space, by successive imaging (by SEM) and slicing (by FIB) the object. An important step of 3D reconstruction is the SEM images segmentation, which allows identifying pores (images binarization). Often this task is complicated due to peculiarities of SEM images contrast formation and specific appearance of pores in SEM images. The solution of these problems and completion of all processing steps results in generation of pores surface model and that allows to get quantitative characteristics of pore space, including the connectivity of pores by skeletonization of the internal pore space.

The study of pore space was performed on a number of shales from different areas of Bazhenov formation and these samples were in various katagenesis stages. Bazhenov formation is one of the largest Russian shale formation (Western Siberia) with unconventional hydrocarbon reserves, formed by sediments of the seabed in the late Jurassic and early Cretaceous period. The composition of the Bazhenov formation rocks is characterized by a large volume fraction of organic matter, in which the kerogen dominates. Other shales components, determined by X‐ray diffraction (XRD), SEM and energy‐dispersive X‐ray spectroscopy, were silica minerals series (e.g., quartz), carbonates, clay minerals and pyrite. Moreover, the components of the shales, namely mineral component and organic compounds, contain pores of different types, which sizes vary over a wide range (nano‐ and micrometer ranges), and their distribution is nonuniform.

Helios (FEI, USA), Scios (FEI, USA) and Versa 3D (FEI, USA) DualBeam (FIB/SEM) systems with the registration of secondary electrons (SE) and back‐scattered electrons (BSE) were used in this study. Avizo and Amira software (FEI, USA) was used for image processing, 3D reconstruction and analysis.

3D reconstruction of one of the shale samples is shown in Fig. 1. The overall microstructure consists of three main components: mineral matrix, pore‐kerogen space and pyrite inclusions. This sample has a high concentration of the kerogen at a high katagenesis stage (MK
3
) and, therefore, high density of pores of different sizes. The pores sizes in the kerogen were in the range of 0.01 µm to 0.5 µm and in cross‐sections they looked mostly roundish. More irregular pores were in mineral matrix and typically they were larger in size. The automatic segmentation by threshold level in this case was not always possible. The automatic segmentation of pores was challenging and, therefore, an advanced image processing, including image filtering, combined with more complicated segmentation methods were used. The result of 3D reconstruction of the pore space in the kerogen is presented in Fig. 2. Pores volume distribution was calculated on the basis of the 3D binarized image dataset. Next procedure was the skeletonization of pore space and the estimation of pores connectivity. After 3D reconstruction it was easy to estimate the volume fractions of the kerogen, pyrite and mineral matrix in the sample.