Fuzzy clustering constrained magnetelluric inversion - Case study over the Kevitsa ultramafic intusion, Northern Finland

Abstract

Inverse magnetotelluric (MT) problems are non-unique and smoothing criteria are typically added to choose the "best" model. However, the process often produces an unrealistic geological model. In reality the subsurface geology is differentiated by distinct rock units that are often better defined by boundaries rather diffuse or smooth boundaries. We present the application of fuzzy clustering as an added constraint within the inversion process to guide model updates toward earth models that are "blocky", and thus resemble geological units. Fuzzy clustering divides the simulated model into clusters based on the similarity of model features. Moreover, fuzzy clustering naturally enables the inclusion of additional prior information in the inversion process, such as petrophysical information from borehole data. The inclusion of this information produces geo-electrical distributions that are more representative of the true rock units. This is demonstrated through the case study of the Kevitsa Ni-Cu-PGE deposit, northern Finland. The inversion can detect the ore zones and carbonaceous phyllite relating to the conductive zones. The inverted cluster generated model is compare better with borehole data than other approaches.