Application of recurrence plots to orebody exploration data

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A recurring question in mineral exploration is to predict the spatial distribution of ore-bearing minerals, to determine both (i) the economic value of a prospective deposit, and (ii) the optimal locations for mineral discovery (Jébrak M, 1997). In hydrothermal gold deposits such as the Imperial deposit, in the Yilgarn of Western Australia, the gold exhibits a highly variable spatial distribution, causing great difficulties for ore recovery and mine planning; the hypothesis is that such variability results from orebody formation by a non-equilibrium open chemical reactor process with complex chemical-flow-heat-mechanical couplings (Ord et al., 2012, 2016; Lester et al., 2012). With this insight, an important goal is to develop new computational methods to analyse drill-core data to extract key features of the underlying dynamical system, so as to shed light on the orebody formation mechanism(s). In order to discover whether prediction is possible in such systems we need to establish whether the patterns of alteration and mineralisation are intrinsically random or have an underlying deterministic origin.
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