Fine-scale heterogeneity of pyrite and organics within mudrocks: Scanning electron microscopy and image analysis at the large scale

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Abstract

Mudrocks are highly heterogeneous in terms of both composition and fabric, with heterogeneities occurring at the submicron to centimetre plus scale. Such heterogeneities are relatively easy to visualise at the micron-scale through the use of modern scanning electron microscopy (SEM) techniques, but due to their inherent fine grain size, can be difficult to place within the greater context of the mudrock as a whole, or to visualise variation when viewed at a centimetre scale. The utilisation of SEM to collect automated high-resolution backscattered (BSE) images (tiles) over whole, polished thin-sections presents a potential large data bank on compositional and fabric changes that can be further processed using simple image analysis techniques to extract data on compositional variation. This can then be plotted graphically in 2D as colour contoured distribution maps to illustrate any observed variability. This method enables the easy visualisation of micron-scale heterogeneity present in mudrock, which are here illustrated and discussed for pyrite and organic content at the larger (thin-section) centimetre scale. This does not require the use of other techniques such as energy dispersive x-ray (EDX) mapping to identify phases present, but instead utilizes BSE images that may already have been collected for textural fabric studies. The technique can also be applied to other phases in mudrocks, such as carbonates and silicates, as well as porosity. Data can also be extracted and used in a similar fashion to bulk compositional analytical techniques such as inductively coupled plasma-atomic emission microscopy (ICP-AES) and carbon, nitrogen and sulphur (CNS) analysis, for average organic carbon and percentage pyrite.

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Buckman, J., Aboussou, A., Esegbue, O., Wagner, T., & Gambacorta, G. (2020). Fine-scale heterogeneity of pyrite and organics within mudrocks: Scanning electron microscopy and image analysis at the large scale. Minerals, 10(4). https://doi.org/10.3390/min10040354

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