Preprints
https://doi.org/10.5194/se-2021-124
https://doi.org/10.5194/se-2021-124

  03 Nov 2021

03 Nov 2021

Review status: this preprint is currently under review for the journal SE.

Utilisation of probabilistic MT inversions to constrain magnetic data inversion: proof-of-concept and field application

Jeremie Giraud1,2,3,a, Hoël Seillé4, Mark D. Lindsay1,5,6, Gerhard Visser4, Vitaliy Ogarko1,2, and Mark W. Jessell1,2 Jeremie Giraud et al.
  • 1Centre for Exploration Targeting (School of Earth Sciences), University of Western Australia, 35 Stirling Highway, Crawley, Australia
  • 2Mineral Exploration Cooperative Research Centre, School of Earth Sciences, University of Western Australia, 35 Stirling Highway, WA Crawley 6009 Australia
  • 3GeoRessources, Université de Lorraine, Rue du doyen Marcel Roubault, Vandoeuvre-lès-Nancy, France
  • 4Commonwealth Scientific and Industrial Research Organisation, Deep Earth Imaging Future Science Platform, Australian Resources Research Centre, Kensington, Australia
  • 5Commonwealth Scientific and Industrial Research Organisation, Mineral Resources, Australian Resources Research Centre, Kensington, Australia
  • 6ARC Industrial Transformation Training Centre in Data Analytics for Resources and Environment (DARE)
  • anow at: GeoRessources, Université de Lorraine, Rue du doyen Marcel Roubault, Vandoeuvre-lès-Nancy, France

Abstract. We propose, test and apply a methodology integrating 1D magnetotelluric (MT) and magnetic data inversion, with a focus on the characterization of the cover-basement interface. It consists of a cooperative inversion workflow relying on standalone inversion codes. Probabilistic information about the presence of rock units is derived from MT and passed on to magnetic inversion through constraints combining such structural constraints with petrophysical prior information. First, we perform the 1D probabilistic inversion of MT data for all sites and recover the respective probabilities of observing the cover-basement interface, which we interpolate to the rest of the study area. We then calculate the probabilities of observing the different rock units and partition the model into domains defined by combinations of rock units with non-zero probabilities. Third, we combine such domains with petrophysical information to apply spatially-varying, disjoint interval bound constraints to least-squares magnetic data inversion. We demonstrate the proof-of-concept using a realistic synthetic model reproducing features from the Mansfield area (Victoria, Australia) using a series of uncertainty indicators. We then apply the workflow to field data from the prospective mining region of Cloncurry (Queensland, Australia). Results indicate that our integration methodology efficiently leverages the complementarity between separate MT and magnetic data modelling approaches and can improve our capability to image the cover-basement interface. In the field application case, our findings also suggest that the proposed workflow may be useful to refine existing geological interpretations and to infer lateral variations within the basement.

Jeremie Giraud et al.

Status: open (until 15 Dec 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on se-2021-124', Max Moorkamp, 26 Nov 2021 reply
  • RC2: 'Comment on se-2021-124', Anonymous Referee #2, 01 Dec 2021 reply

Jeremie Giraud et al.

Jeremie Giraud et al.

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Short summary
We propose and apply a workflow to combine the modelling and interpretation of magnetic anomalies and resistivity anomalies to better image the basement. We test the method on a synthetic case study and apply it to real world data from the Cloncurry area (Queensland, Australia), which is prospective for economic minerals. Results suggest new interpretation about the composition and structure towards to east of the profile that we modelled.