Engineering topics which span a range of length and time scales present a unique challenge to researchers. Hydraulic fracturing (fracking) of oil shales is one of these challenges and provides an opportunity to use multiple research tools to thoroughly investigate a topic. Currently, the extraction efficiency from the shale is low but can be improved by carefully studying the processes at the micro- and nano-scale. Fracking fluid induces chemical changes in the shale which can have significant effects on the microstructure morphology, permeability, and chemical composition. These phenomena occur at different length and time scales which require different instrumentation to properly study. Using synchrotron-based techniques such as fluorescence tomography provide high sensitivity elemental mapping and an in situ micro-tomography system records morphological changes with time. In addition, the transmission X-ray microscope (TXM) at the Stanford Synchrotron Radiation Lightsource (SSRL) beamline 6-2 is utilized to collect a nano-scale three-dimensional representation of the sample morphology with elemental and chemical sensitivity. We present the study of a simplified model system, in which pyrite and quartz particles are mixed and exposed to oxidizing solution, to establish the basic understanding of the more complex geology-relevant oxidation reaction. The spatial distribution of the production of the oxidation reaction, ferrihydrite, is retrieved via full-field XANES tomography showing the reaction pathway. Further correlation between the high resolution TXM data and the high sensitivity micro-probe data provides insight into potential morphology changes which can decrease permeability and limit hydrocarbon recovery.
Combining the energy tunability provided by synchrotron X-ray sources with transmission X-ray microscopy, the
morphology of materials can be resolved in 3D at spatial resolution down to 30 nm with elemental/chemical
specification. In order to study the energy dependence of the absorption coefficient over the investigated volume, the
tomographic reconstruction and image registration (before and/or after the tomographic reconstruction) are critical. We
show in this paper the comparison of two different data processing strategies and conclude that the signal to noise ratio
(S/N) in the final result can be improved via performing tomographic reconstruction prior to the evaluation of energy
dependence. Our result echoes the dose fractionation theorem, and is particularly helpful when the element of interest
has low concentration.