This project provides 2D synchrotron micro X-ray fluorescence (µXRF) and micro X-ray diffraction (µXRD) data, as well as generated mineral maps for a shale rock from the Eagle Ford formation. The Eagle Ford shale is an organic-rich laminate shale in southern Texas that is actively drilled for unconventional oil and gas operations. The Eagle Ford shale sample in this study is a calcareous mudstone consisting of ultra-fine-grained calcite and silicate minerals arranged in a foliated texture with concentrated layers of larger calcite grains (Spokas et al. 2019). It was originally obtained from an outcrop, purchased from Kokurec Industries. The synchrotron data were obtained at Advanced Photon Source (APS) of Argonne National Laboratory, beamline 13-ID-E (Lanzirotti et al. 2016, Sutton et al. 2017), a beamline that houses a hard X-ray microprobe with diffraction and fluorescence detection capabilities with raster scanning at micron resolutions. Raw synchrotron data can be interpreted and further analyzed using LARCH (Newville 2013). This project includes coupled µXRF-µXRD data from a 2D scan of a thin section of an Eagle Ford shale rock (‘EFS1’) of size 500 µm by 500 µm (resolution: 2 µm). For 8 selected elements, fluorescence intensity map images are included as part of the analysis data. Also included is 2D µXRF data from a 7 mm by 2 mm area (resolution: 4 µm) of the same Eagle Ford shale rock (‘EFS2’). Similarly, element intensity map images for 8 selected elements are provided. Mineral maps of the shale were generated using SMART mineral mapping method, an original method developed by the authors (Kim et al. 2020 in prep – see publications tab). The SMART mineral mapper utilizes an Artificial Neural Network trained on coupled XRF-XRD data. The resulting mineral classifier can reliably map minerals for an input of new µXRF data. A subset of the coupled data for EFS1 served as training data, and the µXRF data for EFS2 were interpreted using the SMART mineral mapper. Scripts to generate mineral distribution maps written in MATLAB® (V. 9.3, The Mathworks Inc.), and all data needed for mineral map generation are included as a part of analysis and origin data, respectively.
Catherine Peters (Princeton University)
Jan. 18, 2020
The downloadable archive contains all project data; the size of the archive file for this project is 8.49 GB.Download