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Natural Resources Research

, Volume 24, Issue 3, pp 275–290 | Cite as

Curvature Attribute from Surface-Restoration as Predictor Variable in Kupferschiefer Copper Potentials

An Example from the Fore-Sudetic Region
  • Pablo Mejía-Herrera
  • Jean-Jacques Royer
  • Guillaume Caumon
  • Alain Cheilletz
Article

Abstract

This work explains a procedure to predict Cu potentials in the ore-Kupferschiefer using structural surface-restoration and logistic regression (LR) analysis. The predictor in the assessments are established from the restored horizon that contains the ore-series. Applying flexural-slip to unfold/unfault the 3D model of the Fore-Sudetic Monocline, we obtained curvature for each restored time. We found that curvature represents one of the main structural features related to the Cu mineralization. Maximum curvature corresponds to high internal deformation in the restored layers, evidencing faulting and damaged areas in the 3D model. Thus, curvature may highlight fault systems that drove fluid circulation from the basement and host the early mineralization stages. In the Cu potential modeling, curvature, distance to the Fore-Sudetic Block and depth of restored Zechstein at Cretaceous time are used as predictors and proven Cu-potential areas as targets. Then, we applied LR analysis establishing the separating function between mineralized and non-mineralized locations. The LR models show positive correspondence between predicted probabilities of Cu-potentials and curvature estimated on the surface depicting the mineralized layer. Nevertheless, predicted probabilities are particularly higher using curvatures obtained from Late Paleozoic and Late Triassic restorations.

Keywords

Structural restoration Fault system Fault activity Logistic regression Predictive modeling 

Notes

Acknowledgments

This works has been performed in the frame of the Gocad research project. We thank the industry and academic members of the Gocad Research Consortium (http://www.gocad.org/w4/index.php/consortium/members) for supporting this research. We thank Paradigm for the Gocad software. We appreciate the collaboration of Clementine Fourrier (Université de Lorraine). We thank Piotr Krzemiński (Mozów Copper SP z o.o.) for his comments and remarks which helped improve this paper. Finally, our special thanks go to Laurent Ailleres (Monash University) and Tobias Bauer (Luleå University of Technology) for very helpful observations and discussions. Part of this research received funding from the European Union’s Seventh Framework Program under grant agreement \(\hbox {n}^{\circ } 228559\) (ProMine Project), and was performed in the framework of the of Investissements d’avenir Labex RESSOURCES21 (ANR-10-LABX-21).

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Copyright information

© International Association for Mathematical Geosciences 2014

Authors and Affiliations

  • Pablo Mejía-Herrera
    • 1
  • Jean-Jacques Royer
    • 1
  • Guillaume Caumon
    • 1
  • Alain Cheilletz
    • 1
  1. 1.Université de Lorraine-ENSG, CNRS-CREGU, Géoressources, UMR 7359Vandoeuvre-lès-Nancy CedexFrance

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