Common Earth Modelling of the Kiruna Mining District
Three-dimensional geological modelling, at deposit/district scale, has become an essential tool in geosciences, with especially vital applications in the field or ore geology. 3D models in general, and common-earth models integrating various datasets in particular, allow for more accurate geological interpretations from local to regional scale, as well as more reliable prediction and targeting in mine planning and mineral exploration from deposit to district scale. In addition, they provide an intuitive tool to appreciate the complex three-dimensional geometry of geology.
The proposed project aims at combining all available and relevant geological and geophysical data in the Kiruna district into a Common Earth Modelling (CEM) framework. The CEM concept was developed in the oil and gas exploration industry with the objective of providing a GIS-based framework for sharing and visualization of data, models and interpretations. The CEM concept facilitates cooperation and interaction between people with different competences by ensuring that all relevant information is communicated and integrated in a systematic and structured manner. CEM is a multi-disciplinary, interpretive, iterative process and is performed by integration of structural data, geochemistry, geophysics and petrophysics. The technique combines geological, geophysical and petrophysical acceptable models. The common earth model takes all conventional, spatial exploration data as input and provides explicit integration of all components into a single model of the earth consistent with all input data. By doing this we can honor all available data and combine it into a common platform where geological geometries and geological history can be interpreted. The joint and combined modelling shall ensure that all available and relevant data are utilized whereby model parameter uncertainties can be minimized.
In addition to the advantage of having a unified framework for data sharing and modelling, the workflow using the CEM implies that model uncertainties are significantly reduced due to joint interpretation of all data. Research on quantification of model parameter uncertainties is ongoing and progress in this direction has been reported by e.g. Wellmann et al. (2014, 2017). The proposed project will utilize some of these development in order describe uncertainties in the derived models.