Mineral systems modeling for lithium-bearing pegmatite prospectivity analysis in central Lapland granitoid complex and its surroundings

Abstract

The aim of the thesis is to evaluate existing generic prospectivity modeling tools and data resources for assessing lithium-bearing pegmatite potential in the Central Lapland Granitoid Complex (CLGC), which is potential, but as of today, little-researched area for lithium in northern Finland.

Methodologically, existing scientific mineral systems models for lithium, available from New Zealand and Australia, are applied together with existing Mineral Prospectivity Modeling tool (MPM), and geological data provided by the Geological Survey of Finland. Mineral systems models define mapping criteria for the following: sources (energy, fluid, ligand, ore), pathway (enrichment and focusing mechanism), trap, and preservation (surface expression), and their computational proxy data sets, derived from regional geological and geophysical information. Methodologically MPM tools use prospectivity modeling based on fuzzy logic computation on available geological data as defined by the mineral systems models. The availability and accuracy of geological data are of key importance for the mineral systems approach.

The genesis of lithium-bearing pegmatites is scientifically not fully understood yet, and there are several theories of the set of geological conditions that make possible formation of pegmatites, such as pluton magma fractioning, anatectic partial melting, and multiphase melting. The tectonics history of CLGC is analysed with respect to different genesis theories and compared to known lithium bearing pegmatite rich areas in Finland, such as western side of Central Finland Granitoid Complex (CFGC). Existing mineral systems models for lithium are dependent largely on such types of geological data which are either not available in CLGC area or not computationally adapted for MPM tool evaluated in this research. Especially till data elements needed for geochemical indicators or as pathfinders for lithium minerals, are computationally lacking, most notably Li itself and Al, B, Be, Cl, Cs, F, Mg, Mo, Nb, Rb, REE, Sn, Sr, Ta, W. As prominent source, S- type granites are specifically enriched by Ba, Be, Cs, F, Ga, K, Li, Nb, Rb, Sn, Ta, most of which are also computationally lacking in MPM till data. A major result of the study was that computationally both available and relevant till data elements in MPM are restricted to Ba, Ca, K, La, Mn, P, Th. Gamma (K, Ba) was found useful as proxy for S- type pegmatites. Gamma (P, La, Th, Mn) was found useful as proxy for incompatibles. Another major result was that Gamma (distance to geological structures, geophysical gravity worms) was found computationally useful as structural proxy. With these computational proxies, a fuzzy logic computational model and prospectivity map for lithium were generated with MPM tools for CLGC area and its surroundings. Results are presently inconclusive as regards to lithium potential in CLGC requires further validation. Further research is needed to identify and connect more appropriate geological data e.g. mapped granite-types, fertility indicators, metamorphic and erosion levels, and needed geochemical indicator and pathfinder elements computationally to mineral systems model, and selection of more open and powerful tools for prospectivity modeling. There is also a need to improve the mineral systems models themselves to better match the data sources available for any specified target area in Finland.