Integration of Nano CT and SEM in the Characterization of Marcellus Shale

Shale has proven to be a major unconventional natural gas play. However, due to its complex bedding orientations, comparatively high clay content and its complex heterogeneity, producing and optimising production is often hindered by its challenging complexities. It is now imperative to critically understand the complexities surrounding the geology of Shale reservoirs and its characterization. The overall aim of this study is to understand and characterise the Marcellus shale with the view of enhancing our knowledge of the geometry and topology of the tight shale rock. This study presents a simplified workflow in the study of the heterogeneity of shale rock sample by the combination of Nano CT imaging and Scanning Electron Microscopy imaging methodologies. The key components involve the uses of an appropriate sample preparation technique and application of complex imaging algorithm in digitising the shale sample and 3dimension image analysis for improved gas recovery. Full networks with parameterised topology have been generated on the scanned images. In this study the measured porosity is 4.73% and calculated porosity is 4.92%. Therefore the average porosity of the Marcellus shale derived in is study is 4.83% .The network predicted absolute permeability at cross points of the correlations; both correlation combinations gave a similar water saturation value of 0.533 while the relative permeability using the Corey/Skjaeveland was 0.044 and Sigmund Mccaffery/Benstine Anli was 0.047. The Nano CT scans were used for both determination of the static petro physical properties-porosity and visualisation of the sample. The SEM was used to discretise the morphology. The integration of Nano CT reconstruction and SEM imaging modalities presented in this study is a new technique in the characterisation of tight formations at a core scale. This technique carried out in the discretization of unconventional/shale reservoirs will not only help in providing understanding onto the complex geometry of tight reservoirs but also provide intricate insight into understanding adaptable optimum production techniques through flow behavioural analysis and characterisation