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

Giraud, Jeremie; Lindsay, Mark; Ogarko, Vitaliy; Jessell, Mark; Martin, Roland; Pakyuz-Charrier, Evren

doi:https://doi.org/10.5194/se-10-193-2019

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.

https://doi.org/10.5194/se-10-193-2019

© Author(s) 2019. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 10, issue 1

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, Mark Lindsay, Vitaliy Ogarko, Mark Jessell, Roland Martin, and Evren Pakyuz-Charrier

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Final revised paper (published on 25 Jan 2019)
Preprint (discussion started on 24 Aug 2018)

Interactive discussion

Status: closed

AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment

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- Supplement

RC1: 'Review of manuscript se-2018-79', Colin Farquharson, 22 Sep 2018
- AC1: 'Answer to Reviewer', Jeremie Giraud, 05 Nov 2018
- AC2: 'Revised Manuscript.', Jeremie Giraud, 05 Nov 2018
RC2: 'Review of ``Integration of geological uncertainty into geophysical inversion by means of local gradient regularization'' by Giraud et al. submitted to Solid Earth', Anonymous Referee #2, 08 Oct 2018
- AC3: 'Answer to Reviewer', Jeremie Giraud, 05 Nov 2018
- AC4: 'Revised Manuscript.', Jeremie Giraud, 05 Nov 2018

Peer-review completion

AR: Author's response | RR: Referee report | ED: Editor decision

AR by Jeremie Giraud on behalf of the Authors (05 Nov 2018) Author's response Manuscript

ED: Referee Nomination & Report Request started (06 Nov 2018) by Michal Malinowski

RR by Colin Farquharson (25 Nov 2018)

Suggestions for revision or reasons for rejection

Dear Jérémie & Co-Authors,

Thanks very much for considering my comments on the previous version of your manuscript. I'm happy with your responses, and the revised manuscript.

And I can't remember if I explicitly said so before, but I really like the idea of bringing some "other" information, especially "geological", and especially, especially geological information derived from 3D geological modelling, into constrained or guided or whatever geophysical inversions. This is genuinely heading towards a truly integrated *modelling* of geo data.

I do have a couple of remaining comments, which are not important ...

I appreciate the new, revised model with the ghost unit B (and nicely relieved that the geophysics is doing better than I'd thought!). What happens for this example, though, if the new zone of uncertainty that you introduced in this particular example is the only zone of uncertainty, and that the one in the original version of the example weren't there, i.e., not introduce an extra zone (which the inversion can ignore), but have the one zone in the incorrect place? (I'm attaching a pdf file of the page of the supplement with the relevant figures, and I've tried to annotate the image of W_H indicating which two zones I'm talking about.) Will the gravity inversion happily put the density transition where the new, one, incorrectly located zone is??? And if so, how badly distorted is the rest of the model? Maybe it's distorted enough that it's not geologically believable?

Views of the model in Figures 7 & 8: Yes, the addition of the plan views of the regions where the interesting things are definitely helps. The perspective views of the models in these figures are important and useful to see and impressive. Hopefully they can be made as large as possible in the final copy of this paper (and not, e.g., squeezed into a column that is the width of half a page).

Best wishes,
Colin.

Referee Report: PDF

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ED: Publish as is (30 Nov 2018) by Michal Malinowski

ED: Publish as is (05 Dec 2018) by J. Huw Davies (Executive editor)

AR by Jeremie Giraud on behalf of the Authors (07 Dec 2018)

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.