2/12/2023 0 Comments Ternary diagram co2 wolfcamp shaleThe data were obtained using an x-ray microprobe at beamline 13-ID-E at the Advanced Photon Sources. Here, the SMART classifier was applied to μXRF scans of various sedimentary rock samples including consolidated shales from the Eagle Ford (EFS1), Green River (GRS1), Haynesville (HS1), and New Albany (NAS1) formations and a syntaxial vein from the Upper Wolfcamp formation. The SMART mineral classifier is trained on coupled μXRF and micro-x-ray diffraction (μXRD) data, which is what distinguishes it from existing mapping tools. The approach is called Synchrotron-based Machine learning Approach for RasTer (SMART) mapping, which reads μXRF scans and provides mineral maps of the same size and resolution. In this work, millimeter-scale mineral maps are generated using a neural network approach for 2D mineral mapping based on synchrotron micro x-ray fluorescence (μXRF) data. Reactive transport models require such information at the grain-scale to accurately simulate coupled processes of mineral reactions, aqueous solution speciation, and mass transport. Accurate characterizations of mineral reactivity require mapping of spatial heterogeneity, and quantifications of mineral abundances, elemental content, and mineral accessibility.
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