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Discussion papers
https://doi.org/10.5194/se-2019-164
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-2019-164
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Submitted as: research article 11 Nov 2019

Submitted as: research article | 11 Nov 2019

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This discussion paper is a preprint. It is a manuscript under review for the journal Solid Earth (SE).

Towards geologically reasonable lithological classification from integrated geophysical inverse modelling: methodology and application case

Jérémie Giraud1, Mark Lindsay1, Mark Jessell1, and Vitaliy Ogarko2 Jérémie Giraud et al.
  • 1Centre for Exploration Targeting (Schoolof Earth Sciences), University of Western Australia, 35 Stirling Highway, 6009 Crawley, Australia
  • 2The International Centre for Radio Astronomy Research, The University of Western Australia, 7 Fairway, 6009 Crawley, Australia

Abstract. We propose a methodology for the recovery of lithologies from geological and geophysical modelling results and apply it field data. Our technique relies on classification using self-organizing maps (SOM) paired with geoscientific consistency checks and uncertainty analysis. In the procedure we develop, the SOM is trained using prior geological information in the form of geological uncertainty, the expected spatial distribution of petrophysical properties, and constrained geophysical inversion results. We ensure local geological plausibility in the lithological model recovered from classification by enforcing basic topological rules through a process called post-regularisation. This prevents the three-dimensional lithological model from violating elementary geological principles while maintaining geophysical consistency. Interpretation of the resulting lithologies is complemented by the estimation of the uncertainty associated to the different nodes of the trained SOM. The application case we investigate uses data and models from the Yerrida Basin (Western Australia). Our results generally corroborate previous models of the region but they also suggest that the structural setting in some areas need to be updated. In particular, our results suggest the thinning of one of the greenstone belts in the area may be related to a deep structure not sampled by surface geological measurements and which was absent in previous geological models.

Jérémie Giraud et al.
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Synthetic geophysical survey using geological modelling from the Yerrida Basin (Western Australia) J. Giraud https://doi.org/10.5281/zenodo.3522841

Jérémie Giraud et al.
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Short summary
We propose a methodology for the identification of rock types using geophysical and geological information. It relies on an algoritm used in machine learning called Self-organizing maps, to which we add plausibilty filtes to ensure that the results respect base geological rules and geophysical measurements. Application in the Yerrida Basin (Western Australia) reveals that the thinning of prospective greenstone belts at depth could be due to deep structures not seen from surface.
We propose a methodology for the identification of rock types using geophysical and geological...
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