Articles | Volume 10, issue 1
https://doi.org/10.5194/se-10-193-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/se-10-193-2019
© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Jan 2019
Research article |
| 25 Jan 2019
| 25 Jan 2019
Integration of geoscientific uncertainty into geophysical inversion by means of local gradient regularization
Centre for Exploration Targeting, School of Earth Sciences, University of Western Australia, 35 Stirling Highway, WA Crawley 6009, Australia
Mark Lindsay
Centre for Exploration Targeting, School of Earth Sciences, University of Western Australia, 35 Stirling Highway, WA Crawley 6009, Australia
Vitaliy Ogarko
The International Centre for Radio Astronomy Research, 7 Fairway, Ken and Julie Michael Building, The University of Western, Australia, WA Crawley 6009, Australia
Mark Jessell
Centre for Exploration Targeting, School of Earth Sciences, University of Western Australia, 35 Stirling Highway, WA Crawley 6009, Australia
Roland Martin
Géoscience Environnement Toulouse, UMR CNRS 5563, Université Paul Sabatier, Observatoire Midi-Pyrénées, 14 Avenue Edouard Belin, 31400 Toulouse, France
Evren Pakyuz-Charrier
Centre for Exploration Targeting, School of Earth Sciences, University of Western Australia, 35 Stirling Highway, WA Crawley 6009, Australia
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Preprint withdrawn
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Related subject area
Subject area: Crustal structure and composition | Editorial team: Geodesy, gravity, and geomagnetism | Discipline: Geodesy
Sequential inversion of GOCE satellite gravity gradient data and terrestrial gravity data for the lithospheric density structure in the North China Craton
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Topological analysis in Monte Carlo simulation for uncertainty propagation
Joint analysis of the magnetic field and total gradient intensity in central Europe
Yu Tian and Yong Wang
Solid Earth, 11, 1121–1144, https://doi.org/10.5194/se-11-1121-2020, https://doi.org/10.5194/se-11-1121-2020, 2020
Short summary
Short summary
Given the inconsistency of the plane height and also the effects of the initial density model on the inversion results, the sequential inversion of on-orbit GOCE satellite gravity gradient and terrestrial gravity are divided into two integrated processes. Some new findings are discovered through the reliable and effective inversion results in the North China Craton.
Jérémie Giraud, Mark Lindsay, Mark Jessell, and Vitaliy Ogarko
Solid Earth, 11, 419–436, https://doi.org/10.5194/se-11-419-2020, https://doi.org/10.5194/se-11-419-2020, 2020
Short summary
Short summary
We propose a methodology for the identification of rock types using geophysical and geological information. It relies on an algorithm used in machine learning called
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Evren Pakyuz-Charrier, Mark Jessell, Jérémie Giraud, Mark Lindsay, and Vitaliy Ogarko
Solid Earth, 10, 1663–1684, https://doi.org/10.5194/se-10-1663-2019, https://doi.org/10.5194/se-10-1663-2019, 2019
Short summary
Short summary
This paper improves the Monte Carlo simulation for uncertainty propagation (MCUP) method for 3-D geological modeling. Topological heterogeneity is observed in the model suite. The study demonstrates that such heterogeneity arises from piecewise nonlinearity inherent to 3-D geological models and contraindicates use of global uncertainty estimation methods. Topological-clustering-driven uncertainty estimation is proposed as a demonstrated alternative to address plausible model heterogeneity.
Maurizio Milano, Maurizio Fedi, and J. Derek Fairhead
Solid Earth, 10, 697–712, https://doi.org/10.5194/se-10-697-2019, https://doi.org/10.5194/se-10-697-2019, 2019
Short summary
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In this work we aim to interpret the extended magnetic low visible at satellite altitudes above central Europe by performing a joint analysis of magnetic field and total gradient intensity maps at low and high altitudes. Here we demonstrate that such a magnetic anomaly is mainly a result of the contrast between two crustal platforms differing strongly in geological and magnetic properties. Synthetic model tests have been created to support our modeling.
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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 idealized 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...
