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European Microscopy Congress 2020 Abstract Database

Quality assurance and quality control (QA/QC) procedures for mineralogy, porosity, and texture analyses of fine-grained carbonate rocks using automated quantitative mineralogy combined with scanning electron microscopy (AQM-SEM)

Quality assurance and quality control (QA/QC) procedures for mineralogy, porosity, and texture analyses of fine-grained carbonate rocks using automated quantitative mineralogy combined with scanning electron microscopy (AQM-SEM)

Session

PSA.6 - Geological Materials & Bio-mineral systems

Authors

Stefanie Lode (1), Sebastian Næsby Malkki (1), Nynke Keulen (1), Bodil Lauridsen Wesenberg (1), Peter Frykman (1)

Affiliations

1. Geological Survey of Denmark and Greenland (GEUS)

Keywords

1: Automated mineralogy, 2: fine-grained carbonate rocks, 3: quality assurance and quality control

Abstract text

Advanced micro-analytical methodologies, such as AQM-SEM (Zeiss Mineralogic software), originated from and is most commonly used in mineral processing applications in the mineral resource industry but is also used for reservoir geological and other geoscientific applications [1,2,3,4,5]. Automated mineralogy acquires high resolution digital maps of the mineral phases present in the scanned samples and produces detailed quantitative data concerning modal mineralogy, grain composition and shape, and mineral/ element associations [1,2]. Additionally, porosity can be characterised in respect to area, size, and textures. Hence, this method allows to evaluate the provenance and composition of a rock, including diagenetic features, i.e., dissolution/ precipitation reactions and textures.

Fine-grained rocks, such as chalk and marly chalk, represent challenges for AQM-SEM, as they are more difficult to analyze due the primary electron beam diameter versus small grain size and the resulting interaction volume [4]. Furthermore, the chalks are analyzed under, for conventional AQM-SEM analyses, high magnification of 8000x. Accordingly, it is of great importance to implement QA/QC procedures to ensure that the data are reliable. As part of this ongoing research project two ‘endmembers’ of the chalk to marly chalk range were chosen: an Upper Cretaceous ‘clean’ chalk and a Lower Cretaceous marly chalk and investigated regarding their mineralogy, porosity, and textural features, including the quantification of organic matter in the marly chalk. For QA/QC purposes, additional to the main large mineral map (map a), a small map area (map b) was selected for duplicate analyses. The smaller ‘map b’ was run prior to the main mineral map (map a) and again afterwards (map b-duplicate). The same sequence of map analyses (i.e., map b, map a, map b-duplicate) was also acquired for the porosity analyses. Preliminary results indicate that both, the mineralogical and porosity data, have a very good reproducibility.

The advantage of applying these non-destructive AQM-SEM methodologies on chalk and marly chalk is that it provides an excellent opportunity to quantify the mineralogy and porosity, as well as produces information regarding the textures present in the same analysed sample areas. Thus, the used procedures in this study are of significance not only for fine-grained carbonate rocks, but also are of significance for and can be applied to other geoscientific, environmental, or material science research areas [6].

 

References

[1] F Gu, Automated scanning electron microscope based mineral liberation analysis—An introduction to JKMRC/FEI Mineral Liberation Analyser (2003) Journal of Minerals and Materials Characterization & Engineering, Vol. 2, No. 1, pp. 33-41.

[2] SD Graham, Automated mineralogy—the past, present and future, conference paper (2017)

[3] S Lode and L Beranek, Reservoir quality and porosity evolution of Cambrian and Ordovician rift-drift foreland basin sandstones, western Newfoundland (2017) Petroleum Exploration and Enhancement Program (PEEP), Project 2016-2017 Report

[4] SD Graham and N Keulen, Nanoscale automated quantitative mineralogy: A 200-nm quantitative mineralogy assessment of fault gouge using Mineralogic (2019) Minerals, 9, 665, doi:10.3390/min9110665.

[5] N Keulen, S Næsby Malkki, and SD Graham, Automated quantitative mineralogy applied to metamorphic rocks (2020) Minerals, 10, 47, doi: 10.3390/min10010047.

[6] The authors greatly appreciate the financial support by DHRTC. Kind advise was also provided by Mojgan Alaei, Carsten Guvad, Høgni Vesturklett, Christian Knudsen, Stefan Bernstein, and others from the PetroMalm crew, their help was and is greatly appreciated.