|3D subsurface characterisation of the Belgian Continental Shelf: a new voxel modelling approach|Hademenos, V.; Stafleu, J.; Missiaen, T.; Kint, L.; Van Lancker, V.R.M. (2019). 3D subsurface characterisation of the Belgian Continental Shelf: a new voxel modelling approach. Geol. Mijnb. 98(e1). https://hdl.handle.net/10.1017/njg.2018.18
In: Netherlands Journal of Geosciences. Kluwer/Cambridge University Press: Den Haag, Cambridge. ISSN 0016-7746; e-ISSN 1573-9708, meer
3D stochastic modelling; aggregate resource estimation; information entropy; North Sea; Quaternary
|Auteurs|| || Top |
- Hademenos, V.
- Stafleu, J.
- Missiaen, T.
- Kint, L.
- Van Lancker, V.R.M.
Modelling of surface and shallow subsurface data is getting more and more advanced and is demonstrated mostly for onshore (hydro)geological applications. Three-dimensional (3D) modelling techniques are used increasingly, and now include voxel modelling that often employs stochastic or probabilistic methods to assess model uncertainty. This paper presents an adapted method ologicalwork flow for the 3Dmodelling of offshore sand deposits and aims at demonstrating the improvement of the estimations of lithological properties after incorporation of more geological layers in the modelling process. Importantly, this process is driven by new geological insight from the combined interpretation of seismic and borehole data. Applying 3D modelling techniques is challenging given that offshore environments may be heavily reworked through time, often leading to thin and discontinuous deposits. Since voxel and stochastic modelling allow in-depth analyses of a multitude of properties (and their associated uncertainties) that define a lithological layer, they are ideal for use in an aggregate resource exploitation context. The voxel model is now the backbone of a decision support system for long-term sand extraction on the Belgian Continental Shelf.