Blind Source Separation of Spectrally Filtered Geochemical Signals to Recognize Multi-depth Ore-Related Enrichment Patterns

This contribution conceptualizes a blind source separation (BSS) model to recover sources of geochemical signals such that multi-depth ore-related enrichment patterns in complex metallogenic systems can be recognized. The proposed BSS framework consists of two consecutive modules. The first module is for the spectral decomposition of elemental mixtures to obtain different frequency-related components of signals induced by various geological sources. The second module serves to recover the sources of spectrally filtered geochemical signals according to the statistical assumptions made for the transmission of the latter from the former. In a real case experiment on a multiphase mineralization system, the proposed model was applied to the surface geochemical signals of ore-forming elements to gauge the relevance of source-related signals in depicting subsurface ore-related enrichment patterns. Multifractal filtering according to the generalized scale invariance characteristics of the power spectral density plane was adopted to derive elemental images enhanced in different spectral bands. Assuming linear instantaneous transmission, the FastICA technique was employed to encode spectrally filtered representations of elemental mixtures and recover source-related geochemical signals corresponding to different geo-processes. Support vector machines were used to train classifiers to establish statistical links between the surface geochemical signals and the shallow/deep ore-related enrichment patterns within the study area. The classification accuracies demonstrated that shallow/deep ore-related enrichment patterns can be recognized and distinguished more effectively using recovered source-related signals than using elemental mixtures or spectrally filtered representations. The results indicated that the proposed BSS model can provide efficient source-related geochemical signals to identify robust ore-related enrichment patterns with integrated grade and depth resolution to guide further metal exploration.