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Abstract:
The efforts of today’s society to switch to greener technology and fossil-free energy requires mineral resources. The economical depth of new deposits grows hence deep exploration methods are needed. Magnetotellurics is non-invasive passive electromagnetic method allowing to survey from the surface down to a several tens of km and therefore is a choice when deposit scale information is required. In 2018 a magnetotelluric 3-D array dataset was collected around known magnetite-pegmatite-deposits in Kiruna, Sweden. The survey area is affected by industrial electromagnetic noise from the mine and Kiruna town, which is often a challenge for the magnetotelluric method. Nevertheless, we utilized robust multi-remote reference processing techniques to derive magnetotellurics transfer functions which are in general of a good quality, except a few sites. Many sites exhibit an unusual behavior with phase of main components of the impedance tensor going out of quadrant. This behavior can be indication of noisy data or possibly strong 3D effects. Therefore, we rely on data re-weighting scheme to conclude about the data quality. The final 3-D model was obtained after a few re-weighted least square iterations using diffusion smoothness constrains as model covariance matrix (Second order Tikhonov regularization). Finally, we have obtained a model with stable anomalies at all depths which matches known geology but brings new details and insights into the general understanding of the area.
