On the visualization of uncertainty in geoscience 3D models

@inproceedings{ZEHNER_RM2020,
 abstract = { The workflow for the generation of a 3D geological model involves several steps that each involve uncertainty starting with the acquisition of primary data", such as borehole measurements or seismic data. Subsequently there is often conceptual uncertainty involved when interpreting the acquired data especially in regions where data are sparse or have a low quality. Several workflows have been proposed to assess the uncertainty of the input data on the uncertainty of the final structural model, mostly using Monte Carlo techniques. It is important to find ways to visualize these uncertainties and to make the user aware of where the model is uncertain and to what degree, as the currently common visualization and the geometrical description of the models mostly pretend that we know the subsurface to within a precision of a centimetre. To show the uncertainty would not only be a question of fairness with regard to information autonomy but also helps the users to make better decisions. When they are, for example, planning some operation they could decide themselves if they prefer to avoid regions of high uncertainty or if they prefer to perform additional investigations in order to reduce this uncertainty. As part of a work package within the EU-GeoERA project 3DGEO-EU, options and workflows to visualize this uncertainty are evaluated, and example data sets and workflows explaining the use of the suggested methods for 3D geological models are generated. We will discuss the different types of uncertain data and how they could be visualized. Further," we will outline the requirements a geoscience data infrastructure must meet to efficiently manage and visualize these uncertain data and models. },
 author = { Zehner, Björn },
 booktitle = { 2020 RING Meeting },
 publisher = { ASGA },
 title = { On the visualization of uncertainty in geoscience 3D models },
 year = { 2020 }
}