Articles | Volume 13, issue 11
https://doi.org/10.5194/se-13-1697-2022
https://doi.org/10.5194/se-13-1697-2022
Method article
 | 
09 Nov 2022
Method article |  | 09 Nov 2022

Clustering has a meaning: optimization of angular similarity to detect 3D geometric anomalies in geological terrains

Michał P. Michalak, Lesław Teper, Florian Wellmann, Jerzy Żaba, Krzysztof Gaidzik, Marcin Kostur, Yuriy P. Maystrenko, and Paulina Leonowicz

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2022-633', Guillaume Duclaux, 24 Aug 2022
    • AC1: 'Reply on RC1', Michal Michalak, 16 Sep 2022
  • RC2: 'Comment on egusphere-2022-633', Thomas Blenkinsop, 30 Aug 2022
    • AC2: 'Reply on RC2', Michal Michalak, 16 Sep 2022

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Michal Michalak on behalf of the Authors (04 Oct 2022)  Author's response   Author's tracked changes   Manuscript 
ED: Publish subject to technical corrections (10 Oct 2022) by David Healy
ED: Publish subject to technical corrections (10 Oct 2022) by Federico Rossetti (Executive editor)
AR by Michal Michalak on behalf of the Authors (12 Oct 2022)  Manuscript 
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Short summary
When characterizing geological/geophysical surfaces, various geometric attributes are calculated, such as dip angle (1D) or dip direction (2D). However, the boundaries between specific values may be subjective and without optimization significance, resulting from using default color palletes. This study proposes minimizing cosine distance among within-cluster observations to detect 3D anomalies. Our results suggest that the method holds promise for identification of megacylinders or megacones.