One of the most significant challenges facing the development of shale oil and gas resources worldwide is an inadequate understanding of complex flow and transport processes within shale reservoirs. For that reason, a proper understanding of the multi-scale transport phenomena within these highly heterogeneous formations is crucial from both scientific and economic perspective.
Because anisotropy of shale rock exists across multiple scales, determining changes in pores distribution has proven to be difficult. Recent studies have indicated that shale rock pores significantly vary in number, size (from nanopores to micropores), and kind (organic pores and nonorganic pores). Thus far, the role of pore network and, more specifically, what pores contribute the most to the hydrocarbons storage or the production process, is not well understood and remains largely unknown. Hence, it is vital to address the need for understanding of how well different pores are connected and how they create possible flow pathways for the hydrocarbons migration.
Here we present a comprehensive image-to-simulation framework for pore network modeling in Woodford Shale rock matrix. First, we performed multi-scale imaging of the sample using correlative X-ray and scanning electron microscopy. The obtained dataset was then digitally segmented and reconstructed into three components of the rock microstructure, specifically organic matter, nonorganic matter, and pore network. Through this process, the mineralogy, porosity, and pore size distribution of the sample were obtained. Furthermore, visualization of the resulting models revealed the full detail of the shale rock geometry, which was later meshed to a tetrahedron volume mesh for any further transport phenomena modeling and simulation studies. This work provides a guidance for reconstruction of realistic geometries, as well as a template for many different simulation studies relevant to unconventional reservoir characterization.