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Discussion papers | Copyright
https://doi.org/10.5194/se-2018-79
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

Research article 24 Aug 2018

Research article | 24 Aug 2018

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

Integration of geological uncertainty into geophysical inversion by means of local gradient regularization

Jeremie Giraud1, Mark Lindsay1, Vitaliy Ogarko2, Mark Jessell1, Roland Martin3, and Evren Pakyuz-Charrier1 Jeremie Giraud et al.
  • 1Centre for Exploration Targeting, School of Earth Sciences (University of Western Australia), 35 Stirling Highway WA Crawley 6009, Australia
  • 2The International Centre for Radio Astronomy Research, 7 Fairway, Ken and Julie Michael Building, The University of Western, Australia, WA Crawley 6009, Australia
  • 3Géoscience Environnement Toulouse, Observatoire Midi-Pyrénées, 14 Avenue Edouard Belin, 31400 Toulouse, France

Abstract. We introduce a workflow integrating geological uncertainty information in order to constrain gravity inversions. We test and apply this approach to data from the Yerrida Basin (Western Australia), where we focus on prospective greenstone belts beneath sedimentary cover. Geological uncertainty information is extracted from the results of a probabilistic geological modelling process using geological field data and their uncertainty as input. It is utilized to locally adjust the weights of a minimum-structure gradient-based regularization function constraining geophysical inversion. Our results demonstrate that this technique allows geophysical inversion to update the model preferentially in geologically less certain areas. It also indicates that inverted models are consistent with both the probabilistic geological model and geophysical data of the area, reducing interpretation uncertainty. The interpretation of inverted models finally reveals that the recovered greenstone belts may be shallower and thinner than previously thought.

Jeremie Giraud et al.
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Data sets

Yerrida Basin Geophysical Modeling J. Giraud, M. Lindsay, and V. Ogarko. https://doi.org/10.5281/zenodo.1238216

Synthetic dataset for the testing of local conditioning of regularization function using geological uncertainty J. Giraud, V. Ogarko, and E. Pakyuz-Charrier https://doi.org/10.5281/zenodo.1238529

Jeremie Giraud et al.
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Short summary
We propose the quantitative integration of geology and geophysics in an algorithm integrating the probability of observation of rocks with gravity data to improve subsurface imaging. This allows geophysical modelling to adjust models preferentially in the least certain areas while honouring geological information and geophysical data. We validate our algorithm using an idealised case and apply it to the Yerrida Basin (Australia), where we can recover the geometry of buried greenstone belts.
We propose the quantitative integration of geology and geophysics in an algorithm integrating...
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