Articles | Volume 10, issue 1
Solid Earth, 10, 193–210, 2019
https://doi.org/10.5194/se-10-193-2019
Solid Earth, 10, 193–210, 2019
https://doi.org/10.5194/se-10-193-2019

Research article 25 Jan 2019

Research article | 25 Jan 2019

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

Jeremie Giraud et al.

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Cited articles

Abtahi, S. M., Pedersen, L. B., Kamm, J., and Kalscheuer, T.: Case History Extracting geoelectrical maps from vintage very-low-frequency airborne data, tipper inversion, and interpretation: A case study from northern Sweden, Geophysics, 81, B135–B147, https://doi.org/10.1190/geo2015-0296.1, 2016. 
Abubakar, A., Gao, G., Habashy, T. M., and Liu, J.: Joint inversion approaches for geophysical electromagnetic and elastic full-waveform data, Inverse Probl., 28, 055016, https://doi.org/10.1088/0266-5611/28/5/055016, 2012. 
Allmendinger, R. W., Siron, C. R., and Scott, C. P.: Structural data collection with mobile devices: Accuracy, redundancy, and best practices, J. Struct. Geol., 102, 98–112, https://doi.org/10.1016/j.jsg.2017.07.011, 2017. 
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Calcagno, P., Chilès, J. P., Courrioux, G., and Guillen, A.: Geological modelling from field data and geological knowledge. Part I. Modelling method coupling 3D potential-field interpolation and geological rules, Phys. Earth Planet. Inter., 171, 147–157, https://doi.org/10.1016/j.pepi.2008.06.013, 2008. 
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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.