Data mining of petrophysical and lithogeochemical borehole data to elucidate the origin of seismic reflectivity within the Kevitsa Ni–Cu–PGE bearing intrusion, northern Finland

N Junno,I Kukkonen,E Koivisto,M Montonen,C Wijns,A Malehmir

doi:10.1111/1365-2478.12907

Abstract

ABSTRACTThe Kevitsa mafic‐ultramafic intrusion, located within the Central Lapland Greenstone Belt in northern Finland, hosts a large, disseminated Ni–Cu–PGE sulphide deposit. A three‐dimensional seismic reflection survey was conducted over the Kevitsa intrusion in 2010 primarily for open‐pit mine planning and for deep mineral exploration purposes. In the Kevitsa three‐dimensional seismic data, laterally continuous reflections are observed within a constrained region within the intrusion. In earlier studies, it has been suggested that this internal reflectivity mainly originates from contacts between the tops and more sulphide‐rich bottoms of smaller scale, internally differentiated magma layers that represent a spectrum of olivine pyroxenites. However, this interpretation is not unequivocally supported by the borehole data. In this study, data mining, namely the Self‐Organizing Map analysis, of extensive Kevitsa borehole data is used to investigate the possible causes for the observed internal reflectivity within the Kevitsa intrusion. Modelling of the effect of mineralization and alteration on the reflectivity properties of Kevitsa rock types, based on average modal compositions of the rock types, is presented to support the results of the Self‐Organizing Map analysis. Based on the results, we suggest that the seismic reflectivity observed within the Kevitsa intrusion can possibly be attributed to alteration, and may also be linked to the presence of sulphide minerals.

Highlights

In the past decades, seismic reflection methods have increasingly been used for mining and mineral exploration applications in hard rock environments (Milkereit et al 1996; Eaton, Milkereit and Salisbury 2003; Heinonen et al 2012; review by Malehmir et al 2012a; Buske, Bellefleur and Malehmir 2015 and references therein)
Interpretation of seismic reflection data from hard rock mining and exploration environments is often challenging because of the geological complexity emanating from multiple phases of deformation and alteration that the rocks have experienced during their history (e.g. L’Heureux, Milkereit and Vasudevan 2009)
A Davies–Bouldin analysis suggested a local minimum at 13 clusters, which was chosen for further interpretation

Summary

Introduction

Seismic reflection methods have increasingly been used for mining and mineral exploration applications in hard rock environments (Milkereit et al 1996; Eaton, Milkereit and Salisbury 2003; Heinonen et al 2012; review by Malehmir et al 2012a; Buske, Bellefleur and Malehmir 2015 and references therein). Data mining approaches have been used in growing numbers for data-driven analyses of the complex geophysical and geological data sets typical for mining and exploration camps (e.g. Klose 2006; Bierlein et al 2008; Steel 2011; Cracknell, Reading and McNeill 2014; Kieu, Kepic and Kitzig 2018; Horrocks 2019), but examples on the use of data mining techniques for the interpretation of seismic data in hard rock settings are still lacking

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Conclusion