Abstract
Abstract. A two-stage fuzzy inference system (FIS) is applied to prospectivity modelling and exploration-target delineation for rare earth element (REE) deposits associated with carbonatite–alkaline complexes in the western part of the state of Rajasthan in India. The design of the FIS and selection of the input predictor map are guided by a generalised conceptual model of carbonatite–alkaline-complex-related REE mineral systems. In the first stage, three FISs are constructed to map the fertility and favourable geodynamic settings, favourable lithospheric architecture for fluid transportation and favourable shallow crustal (near-surface) emplacement architecture, respectively, for REE deposits in the study area. In the second stage, the outputs of the above FISs are integrated to map the prospectivity of REE deposits in the study area. Stochastic and systemic uncertainties in the output prospectivity maps are estimated to facilitate decision-making regarding the selection of exploration targets. The study led to the identification of prospective targets in the Kamthai–Sarnu-Dandeli and Mundwara regions, where detailed project-scale ground exploration is recommended. Low-confidence targets were identified in the Siwana ring complex region, north and northeast of Sarnu-Dandeli, south of Barmer, and south of Mundwara. Detailed geological mapping and geochemical sampling together with high-resolution magnetic and radiometric surveys are recommended in these areas to increase the level of confidence in the prospectivity of these targets before undertaking project-scale ground exploration. The prospectivity-analysis workflow presented in this paper can be applied to the delineation of exploration targets in geodynamically similar regions globally, such as Afar province (East Africa), Paraná–Etendeka (South America and Africa), Siberia (Russia), East European Craton–Kola (eastern Europe), Central Iapetus (North America, Greenland and the Baltic region) and the pan-superior province (North America).
Highlights
According to the International Union of Pure and Applied Chemistry (IUPAC), the term rare earth elements (REEs) includes yttrium (Y), scandium (Sc) and the lanthanides
Aranha et al.: REEs associated with carbonatite–alkaline complexes in western Rajasthan, India
The second fuzzy inference system (FIS) maps favourable lithospheric architecture for the transportation of REE-enriched carbonatite–alkaline magma (Fig. 4b and Table A3) and narrows down the target areas identified by the first FIS to areas that are proximal to trans-lithospheric structures
Summary
According to the International Union of Pure and Applied Chemistry (IUPAC), the term rare earth elements (REEs) includes yttrium (Y), scandium (Sc) and the lanthanides (lanthanum, La; cerium, Ce; praseodymium, Pr; neodymium, Nd; promethium, Pm; samarium, Sm; europium, Eu; gadolinium, Gd; terbium, Tb; dysprosium, Dy; holmium, Ho; erbium, Er; thulium, Tm; ytterbium, Yb; and lutetium, Lu). These approaches have evolved from the Prospector (Duda et al, 1978, 1979, 1980), which was the earliest knowledge-based expert system that utilised fuzzy operators in a Bayesian network (Porwal et al, 2015) The outputs of both data-driven and knowledge-driven prospectivity models are subject to two types of uncertainties (Porwal et al, 2003; Lisitsin et al, 2014), namely, systemic (or epistemic) and stochastic (or aleatory). Morgenstern et al (2018) analysed the potential of REEs in New Zealand using a multi-stage fuzzy inference system (FIS) This contribution describes the first systematic and comprehensive prospectivity modelling exercise aimed at identifying exploration targets for REE associated with carbonatite–alkaline complexes in western Rajasthan, India (Fig. 1). Continental extensional settings) globally for exploration targeting, e.g. in eastern Africa, South and North America, Russia, eastern Europe, Greenland and the Baltic region
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