In the Simulation Extension, GeoScene3D utilizes and extends a new implementation of MPS algorithms developed in cooperation between I•GIS and researchers at the Niels-Bohr Institute, University of Copenhagen and the Danish Geological Survey (GEUS), as part of the Danish geological modeling research project, ERGO.

MPS provides a statistical approach to modeling the geological heterogeneity observed within rock type variations. It is an alternative to Gaussian-based geostatistics with semi-variograms, and instead relies on geological knowledge captured in user-defined Training Images. For a theoretical overview of the MPS version implemented in GeoScene3D and the theoretical innovations made on this field through the ERGO project see:  Hansen et al. 2016 og Hansen et al. 2018. Høyer et al. 2017 provides a study showing the methods applied tolarge part of southern Denmark.  

The Simulation Extension adds extra functionality to the Voxel Builder Module in GeoScene3D, giving access to Multiple Point Statistics for property simulation in voxel models. These tools provide you with the functionality for working with the latest advancements in geological modeling, all wrapped up in a sequence of user friendly software Wizards, guiding you through the modeling workflow

SI is a clever implicit modeling approach based on machine learning  allowing the computer to learn what the geologist do when (s)he interprets geological layers based on airborne electromagnetic (AEM) data. Based on what the machine has learned from the geologist's interpretations the tool will predict how the geologist would interpret throughout the rest of the survey. This way, the SI algorithm will help speeding up the interpretation process and at the same time include all available data and the expert knowledge from the geologist training the system. For a theoretical summary of the method see Gulbrandsen et al. 2015, 2017a.

The Smart Interpretation tool is included in the AEM extension and has proven to be very successful thorough a number of applications. See e.g. Gulbrandsen et al. 2016, Anschuetz et al. 2016,  Gulbrandsen et al. 2017b, Munday et al. 2018, Gulbrandsen et al. 2018