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News Article | May 4, 2017
Site: www.mining-journal.com

Troy Resources (AU:TRY) managing director Martin Purvis has resigned from his position after agreeing to take on the MD and CEO roles at mineral sands producer MZI Resources (AU:MZI). Purvis, who will step down from the precious metal miner at the end of May, is replaced on an interim basis by chairman Fred Grimwade. He had been at Troy since September 2014. At MZI, he comes in for Steve Ward, who has been interim MD and CEO since November 2016. After Purvis’ appointment on July 1, Ward will revert to his non-executive director role. Under Ward’s leadership, the company has completed significant plant upgrades and associated optimisation activities at its Keysbrook mine in Western Australia.


Ford A.,University of Western Australia | Ford A.,James Cook University | Hagemann S.G.,University of Western Australia | Fogliata A.S.,National University of Tucuman | And 3 more authors.
Ore Geology Reviews | Year: 2015

This paper presents a review of the available information on the significant porphyry, epithermal, and orogenic gold districts in Argentina, including the tectonic, geological, and structural settings of large deposits or deposits that have been exploited in the past. Based on this review of the geology and mineralization, targeting models are developed for epithermal and orogenic gold systems, in order to produce GIS-based prospectivity models. Using publically available digital geoscience data, weights of evidence and fuzzy logic prospectivity maps were generated for epithermal and orogenic gold mineralization in Argentina. The results of the prospectivity mapping highlight existing gold deposits within known mineralized districts throughout Argentina, as well as other highly prospective areas with no known deposits within these districts. Additionally, areas within Argentina that have no known gold mineralization (based on publically available information) were highlighted as being highly prospective based on the models used. © 2015 Elsevier B.V.


Costa E Silva E.,Reinarda Mineracao Ltda. Troy Brazil | Silva A.M.,University of Brasilia | Bemfica Toledo C.L.,University of Brasilia | Mol A.G.,Troy Resources Ltd | And 2 more authors.
Economic Geology | Year: 2012

The Rio Maria granite-greenstone terrain is characterized by extensive surficial cover and a lack of outcrop. Therefore, airborne geophysical measurements play a major role in mineral exploration in this region. A highresolution airborne survey was used to build a prospectivity model for gold targeting employing a fuzzy logic technique. Within the Rio Maria granite-greenstone terrain, a total of 57 new potential orogenic gold targets were identified. The ability of this processing technique to identify favorable targets with potential for economic gold mineralization was verified by comparing the new predicted targets with known gold occurrences (e.g., Mamão Mine and Lagoa Seca deposits). Geographic Information System (GIS)-based automated processing methods employing fuzzy logic techniques were used to derive spatial models for generating orogenic gold exploration targets. Two metallogenic approaches were used. The first approach considers orogenic gold deposits hosted at the contact between mafic and felsic rocks. The second approach considers shear zone-hosted veins associated with mafic rocks and iron formations in the greenstone terrain. Detailed models were constructed for different blocks of the study area. A subset of these targets, i.e., Marcinho, Resende, and Votuporanga, were subsequently assessed using field evaluations that consisted of geological mapping and geochemical sampling. A follow-up drilling program is currently in progress and will be used to assess the main target areas where grid soil and rock sampling have indicated anomalous trends. The remaining predicted targets warrant further investigation. Data integration using GIS modeling and interpretation resulted in the following main conclusions with respect to the orogenic gold exploration potential of the Rio Maria Province: (1) as shown using GIS-based prospectivity analysis, there is considerable potential for orogenic gold deposits along the Andorinhas greenstone belt, and several prospective areas are associated with mafic and iron formation units; (2) several deposits within the Rio Maria and Identidade greenstone belt are associated with felsic units, as demonstrated by the fuzzy logic models; (3) many of the previously known targets that have been re-identified should be reevaluated to identify those the most promising targets for the discovery of a gold deposit; (4) the final prospectivity model shows that many of the most important gold deposits known are located within areas of high favorability, and several other new potential gold-bearing targets were selected; and (5) the proposed method identifies 57 geologically consistent targets and led to the discovery of the Marcinho deposit. © 2012 by Economic Geology, Inc.


Ford A.,University of Western Australia | Miller J.M.,University of Western Australia | Mol A.G.,Troy Resources Ltd
Natural Resources Research | Year: 2016

Large amounts of digital data must be analyzed and integrated to generate mineral potential maps, which can be used for exploration targeting. The quality of the mineral potential maps is dependent on the quality of the data used as inputs, with higher quality inputs producing higher quality outputs. In mineral exploration, particularly in regions with little to no exploration history, datasets are often incomplete at the scale of investigation with data missing due to incomplete mapping or the unavailability of data over certain areas. It is not always clear that datasets are incomplete, and this study examines how mineral potential mapping results may differ in this context. Different methods of mineral potential mapping provide different ways of dealing with analyzing and integrating incomplete data. This study examines the weights of evidence (WofE), evidential belief function and fuzzy logic methods of mineral potential mapping using incomplete data from the Carajás mineral province, Brazil to target for orogenic gold mineralization. Results demonstrate that WofE is the best one able to predict the location of known mineralization within the study area when either complete or unacknowledged incomplete data are used. It is suggested that this is due to the use of Bayes’ rule, which can account for “missing data.” The results indicate the effectiveness of WofE for mineral potential mapping with incomplete data. © 2015, International Association for Mathematical Geosciences.

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