Seismics, 2D and 3D Inversion of Magnetotellurics Jigsaw pieces in understanding the Skellefte Ore District
Abstract: The Skellefte District (SD) is one of the richest metallogenic mining areas in Sweden. The main deposits consist of volcanic-hosted massive sulphides (VHMS) rich in zinc, copper, lead, gold and silver, that have been explored and mined for more than a century. Considering that technological advancements allow deeper mining, and that today new discoveries rarely occur, renewed efforts are now directed at locating targets at greater depths. Thus, current exploration strategies need to be adapted, and a better understanding of regional scale structures is necessary. To address these questions the project VINNOVA 4D modeling of the Skellefte District was launched. Its main purpose is to unravel the regional structures and tectonic setting of the SD. To accomplish this, new geological and geophysical data have been acquired in two key localities.This thesis presents the contribution from 2D and 3D inversion of magnetotelluric (MT) data and seismic reflection data. The main findings include: conductive hydrothermally altered zones within the otherwise resistive rocks of the Skellefte Group, the depth extension of early and postorogenic intrusions, prominent shear zones in the central part of the district, and enhanced reflectivity and conductivity at the base of the Skellefte Group throughout the SD.Even though the application of these methods is challenged by the complex geological setting of the SD, it is shown that after a careful processing and analysis of the data, they are able to provide a robust image of the deep subsurface. Additionally, the combination of reflection seismics and MT has proved to be a powerful tool for hypothesis testing and to develop the general understanding of the configuration and history of the SD.Furthermore, two 3D inversion models of MT data are presented and compared with the results of standard 2D determinant inversions. The 3D procedure shows significant improvements in data fit and is able to constrain better the observed model features. Although 3D inversion of MT data is not yet a run of the mill scheme and issues like model assessment and galvanic distortion effects need to be further addressed, results from complex environments with areal coverage, are already superior to those from 2D inversions.
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