3D subsurface characterisation of the Belgian Continental Shelf: a new voxel modelling approach. (27th March 2019)

• Record Type: Journal Article
• Authors: Hademenos, Vasileios; Stafleu, Jan; Missiaen, Tine; Kint, Lars; Van Lancker, Vera R.M.
• Is Part Of: Geologie en mijnbouw. Volume 98(2019)
• Publication Date: 2019-03-27
• Subjects: 3D stochastic modelling, -- aggregate resource estimation, -- information entropy, -- North Sea, -- Quaternary; Geology -- Periodicals; Geology -- Netherlands -- Periodicals; Mines and mineral resources -- Periodicals; 551.05
• DOI: 10.1017/njg.2018.18
• Languages: English
• ISSNs: 0016-7746

Abstract

Abstract: 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 methodological workflow for the 3D modelling 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.