A new methodology to train fracture network simulation using multiple-point statistics

Bruna, Pierre-Olivier; Straubhaar, Julien; Prabhakaran, Rahul; Bertotti, Giovanni; Bisdom, Kevin; Mariethoz, Grégoire; Meda, Marco

doi:https://doi.org/10.5194/se-10-537-2019

Articles | Volume 10, issue 2

https://doi.org/10.5194/se-10-537-2019

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

https://doi.org/10.5194/se-10-537-2019

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

Articles | Volume 10, issue 2

Research article

|

17 Apr 2019

Research article |

| 17 Apr 2019

A new methodology to train fracture network simulation using multiple-point statistics

Pierre-Olivier Bruna, Julien Straubhaar, Rahul Prabhakaran, Giovanni Bertotti, Kevin Bisdom, Grégoire Mariethoz, and Marco Meda

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Final revised paper (published on 17 Apr 2019)
Preprint (discussion started on 11 Oct 2018)

Interactive discussion

Status: closed

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

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- Supplement

RC1: 'report', Anonymous Referee #1, 22 Oct 2018
- AC1: 'Reply to Anonymous Reviewer 1', Pierre-Olivier Bruna, 28 Dec 2018
RC2: 'Review of A new methodology to train fracture network simulation using Multiple Point Statistic', Anonymous Referee #2, 19 Nov 2018
- AC2: 'Reply to Anonymous Reviewer 2', Pierre-Olivier Bruna, 28 Dec 2018
SC1: 'review comments', Stephen Laubach, 29 Nov 2018
- AC3: 'Reply to S. Laubach', Pierre-Olivier Bruna, 28 Dec 2018

Peer-review completion

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

AR by Pierre-Olivier Bruna on behalf of the Authors (05 Feb 2019) Author's response Manuscript

ED: Referee Nomination & Report Request started (06 Feb 2019) by Federico Rossetti

RR by John Hooker (12 Mar 2019)

RR by William Dershowitz (25 Mar 2019)

ED: Publish subject to minor revisions (review by editor) (26 Mar 2019) by Federico Rossetti

AR by Pierre-Olivier Bruna on behalf of the Authors (27 Mar 2019) Manuscript

ED: Publish as is (28 Mar 2019) by Federico Rossetti

ED: Publish as is (28 Mar 2019) by Federico Rossetti (Executive editor)

AR by Pierre-Olivier Bruna on behalf of the Authors (01 Apr 2019)

Short summary

Natural fractures influence fluid flow in subsurface reservoirs. Our research presents a new methodology to predict the arrangement of these fractures in rocks. Contrary to the commonly used statistical models, our approach integrates more geology into the simulation process. The method is simply based on the drawing of images, can be applied to any type of rocks in various geological contexts, and is suited for fracture network prediction in water, geothermal, or hydrocarbon reservoirs.