STRUCTURAL, REMOTE SENSING AND MULTIVARIATE CORRELATION METHODS AS AIDS TO MINERAL EXPLORATION, CENTRAL IRELAND
Central Ireland contains some of the largest PB-Zn in Europe. The area is poorly exposed, with thick glacial and post-glacial deposits and extensive agriculture. The known base metal deposits are hosted in Lower Carboniferous carbonates and are stratiform in nature. All the major deposits are adjacent to faults and there is preferential development near to the Courceyan/Chadian boundary. Further deposits are likely to exist beneath a cover of younger Carboniferous rocks and/or beneath thick Quaternary deposits. Such deposits are likely to be blind to conventional exploration methods. The Carboniferous rocks of Central Ireland overlie the zone of the Caledonian collision suture (Iapetus suture). The structure within the Carboniferous cover consists of a series of E-W to ENE-WSW trending dextral shear zones. More stable blocks lie between these transcurrent shear zones. Surface and subsurface mapping at the Silvermines ore deposit showed that the ore bodies were generated in the termination zone of an E-W dextral shear zone. The termination occurs against an inferred granitoid pluton in the basement. The epigenetic Ballyvergin vein deposits lie in a dilation zone at the intersection of major dextral and sinistral shear zones. New methods of analysing the patterns of lineaments interpreted from aerial photographs and enhanced Landsat imagery have defined the known transcurrent shear zones. These methods have also located new shear zones within previously unmapped areas. The zones predicted by this analysis are supported by independent ground structural and geophysical data. Structural models derived from these analyses allow the prediction of possible exploration targets. The geochemical, geophysical, remote sensing and structural data have been statistically combined using computer classification. By introducing geochemical data, this procedure provides, to some extent, an independent test of the previous predictions based on the structural models. Box classification has located new target areas based on the combination of data from known mineral deposits. Discriminant analysis for a set of unmineralized and mineralized 1km**2 sites shows that the ground structural data alone was capable of distinguishing between unmineralized and mineralized sites. With multivariate discriminant analysis (excluding the structural data), the geochemical and derivative aeromagnetic data proved to be best discriminators. The main problems which arose from the discriminant analysis were concerned with the interpolation of data.
Bibliographic Reference: EUR 10334 EN (1986), FS, PP. 1-41, BFR 600, EUROFFICE, LUXEMBOURG, POB 1003
Record Number: 1989124065700 / Last updated on: 1987-01-01
Available languages: en