This paper demonstrates a novel approach that uses wavelet tessellation in rapid analysis of raw geochemical data produced by laser-induced breakdown spectroscopy (LIBS) to produce pseudologs that are representative of stratigraphy. Single-line LIBS spectral data for seven major rock-forming elements (Al, Ca, Fe, Mg, Si, Na and K) were collected from a synthetic 22-sample rock-block comprising two distinct lithological groups based on mineralogy, chemistry and texture: plutonic rocks and marble. Seven sublithologies are identified within the rock-block from traditional laboratory whole-rock geochemical analysis: marble, Mg-marble, granite, quartz monzonite, foidolite, granodiorite and gabbroic diorite. Two-domain clustering (k = 2) on raw spectral LIBS data combined with wavelet tessellation was applied to generate a simplified lithological stratigraphy of marble and plutonic rocks and generate a pseudolog identical to the rock-block stratigraphy. A pseudolog generated from seven-domain clustering (k = 7) and wavelet tessellation successfully discriminated most sublithologies within the rock-block slabs, especially marble slabs. Small-scale units were identified within the more mineralogically and geochemically complex plutonic slabs. The spatial resolution of the LIBS analysis, with a measurement spacing of ~0.35 mm, allowed for assessment of individual mineral compositions and rock textures, and small-scale units within the plutonic rocks can be correlated to specific coarse-grained minerals or mineralogical associations. The application of the wavelet tessellation method to raw LIBS geochemical data offers the possibility of rapid and objective lithogeochemical analysis and interpretations which can predate further analysis (quantitative) and supplement geological logging.
This study examines how LIBS data collected using a downhole deployable LIBS prototype for geochemical analysis in a fashion that imitates downhole deployment may be used for mineralogical investigations. Two chemically and mineralogically practically identical felsic rocks, namely granite and microgranite are used to assess the effects of rock texture on mineral classification and high-resolution SEM-TIMA mineral maps are used to reveal mineralogical composition of each LIBS ablation crater. Additionally, in order to extend the LIBS application for fast mineralogical studies to a greenfield scenario (i.e., no previous knowledge) a clustering methodology is presented for mineralogical classification from LIBS data. Results indicate that most LIBS spot analyses sample mineral mixtures, 91.2% and 100% for granite and microgranite, respectively, which challenges mineralogical classification, particularly for fine-grained rocks. Positive identification and classification of minerals of slightly different compositions relative to the bulk rock (i.e., fluorite and biotite in granitic rocks) demonstrates how minerals or minerals groups of distinct and interesting chemical compositions (e.g., sulphides or oxides in silicate dominated rocks) can be rapidly recognised in a mineral exploration scenario. Strategies for overcoming mineral mixture issues are presented and recommendations are given for effective workflows for mineralogical analysis using LIBS data in different mineral exploration stages. Supplementary material: https://doi.org/10.6084/m9.figshare.c.6444482
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