ORCID Profile
0000-0001-6484-3291
Current Organisations
University of Oviedo
,
CSIRO Australian Resources Research Centre
,
University of Western Australia
,
Universidad de Oviedo
,
CSIRO
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Resource geoscience | Mineralogy and crystallography | Exploration geochemistry | Geology
Publisher: Elsevier BV
Date: 2022
Publisher: Elsevier BV
Date: 05-2019
Publisher: CSIRO
Date: 2018
A Chelate-Free Nano-Platform for Incorporation of Diagnostic and Therapeutic Isotopes
Publisher: Informa UK Limited
Date: 2020
DOI: 10.2147/IJN.S227931
Publisher: SPIE
Date: 05-05-2016
DOI: 10.1117/12.2223626
Publisher: Elsevier BV
Date: 11-0010
Publisher: Elsevier BV
Date: 06-2021
Publisher: Elsevier BV
Date: 08-2014
Publisher: Elsevier BV
Date: 07-2013
Publisher: Elsevier BV
Date: 04-0001
Publisher: Elsevier BV
Date: 04-2011
Publisher: Elsevier BV
Date: 02-2019
Publisher: Elsevier BV
Date: 08-2013
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-6682
Abstract: & & The Gawler Craton hosts significant economic mineralization within South Australia. Due to limited outcrops, deeply weathered profiles, and the absence of a clear variety of landscape surface features, mineral exploration is particularly challenging in this part of Australia. Here we present a workflow of data processing and interpretation to understand the neotectonics and landscape characterization of this region. We explore the potential to delineate surface lineaments and features from newly acquired high-resolution datasets. We aim to automatically identify landform domains based on the analysed data and investigate whether deep seated tectonic lineaments manifest in recognizable surface expressions.& & & & The data we analyse in this study comprises digital elevation, radiometric, magnetic, and gravity data. We assume that elevation and radiometric data relate to surficial landscape features, whereas gravity and magnetic data represent subsurface basement features. Linking the analysis of both surface and subsurface datasets can potentially yield information on the neotectonic activity, and the association between landforms and basement structures as potential zones of fluid migration. We will show how processed digital elevation data can be used for automatic classification of different landform domains.& & & & In order to assess mineral potential zones in the area, we compare the generated lineament data in terms of their geometric and topological properties to examine whether there is consistency in the subsurface and surface layers. We postulate that through a line density map, we may be able to quantify a potential relationship between lineaments that are representative in both the surface and subsurface, indicating potential faults or large-scale lineament trends that may link mineral systems in the basement with the landscape surface features. Areas that exhibit large numbers of surface and subsurface lineaments might be areas of enhanced mineral potential. This study contributes to enhance the efficiency of mineral exploration protocols in areas under cover.& &
Publisher: Society of Exploration Geophysicists
Date: 17-08-2017
Publisher: Elsevier BV
Date: 02-2000
Publisher: Elsevier BV
Date: 11-2010
Publisher: Elsevier BV
Date: 11-2020
Publisher: Elsevier BV
Date: 02-2019
Publisher: CSIRO
Date: 2018
Publisher: Elsevier BV
Date: 07-2012
Publisher: Society of Economic Geologists
Date: 15-02-2012
Publisher: MDPI AG
Date: 06-07-2021
DOI: 10.3390/IJGI10070459
Abstract: Landscapes evolve due to climatic conditions, tectonic activity, geological features, biological activity, and sedimentary dynamics. Geological processes at depth ultimately control and are linked to the resulting surface features. Large regions in Australia, West Africa, India, and China are blanketed by cover (intensely weathered surface material and/or later sediment deposition, both up to hundreds of metres thick). Mineral exploration through cover poses a significant technological challenge worldwide. Classifying and understanding landscape types and their variability is of key importance for mineral exploration in covered regions. Landscape variability expresses how near-surface geochemistry is linked to underlying lithologies. Therefore, landscape variability mapping should inform surface geochemical s ling strategies for mineral exploration. Advances in satellite imaging and computing power have enabled the creation of large geospatial data sets, the sheer size of which necessitates automated processing. In this study, we describe a methodology to enable the automated mapping of landscape pattern domains using machine learning (ML) algorithms. From a freely available digital elevation model, derived data, and s le landclass boundaries provided by domain experts, our algorithm produces a dense map of the model region in Western Australia. Both random forest and support vector machine classification achieve approximately 98% classification accuracy with a reasonable runtime of 48 minutes on a single Intel® Core™ i7-8550U CPU core. We discuss computational resources and study the effect of grid resolution. Larger tiles result in a more contiguous map, whereas smaller tiles result in a more detailed and, at some point, noisy map. Diversity and distribution of landscapes mapped in this study support previous results. In addition, our results are consistent with the geological trends and main basement features in the region. Mapping landscape variability at a large scale can be used globally as a fundamental tool for guiding more efficient mineral exploration programs in regions under cover.
Publisher: Elsevier BV
Date: 03-2010
Publisher: CSIRO
Date: 2022
DOI: 10.25919/8T3J-PP81
Publisher: CSIRO
Date: 2017
Publisher: Copernicus GmbH
Date: 20-06-2022
DOI: 10.5194/ICG2022-31
Abstract: & & Detection of mineral system footprints in regions under thick cover is challenging. The difficulties are enhanced in regions with low-relief landscapes that are deeply weathered. This is widely the case in Australia where & % of the surface and subsurface is characterised by transported cover and/or deeply and intensely weathered profiles.& & & & In a variety of geological-cover contexts, geochemical dispersion/concentration processes within cover units can be particularly efficient. These processes can produce near surface geochemical anomalies in the landscape, which may be expressions of mineral systems within basement units at depth& #8217 .& & & & Basement structures in Earth& #8217 s crust are a well-recognised conduit for fluid flow, which can result in the formation of a large variety of mineral deposits (e.g., IOCG, hydrothermal Ni, SEDEX, etc). Therefore, identifying basement structures that may be associated with mineral deposit formation has become an important part of exploration protocols and prospectivity assessments.& & & & The possible link between neotectonics and geochemical dispersion processes should be carefully considered when studying landscape geochemistry in areas with thick overburden.& & & & Surface structures linked to principal basement structures which are intermittently reactivated may maintain a direct geochemical link between the basement and the surface. To efficiently resolve basement-derived geochemical signals, soil or surface landscape units should be selectively s led in relation to these structures.& & & & This study discusses how in areas of deep cover, neotectonic and/or reactivation surface landscape features have the highest probability to detect deep basement geochemical signatures at surface. This approach may have a critical impact in mineral exploration under cover in similar landscape contexts around the world, such as regions in Australia, West Africa, India, China and Brazil.& &
Publisher: CSIRO
Date: 2020
DOI: 10.25919/5DQE-6X48
Publisher: Elsevier BV
Date: 03-2016
Publisher: Elsevier BV
Date: 03-2016
Publisher: Elsevier BV
Date: 05-2008
Publisher: Elsevier BV
Date: 09-2011
Publisher: Elsevier BV
Date: 07-2023
Publisher: Society of Exploration Geophysicists
Date: 09-2021
Publisher: AMPCo
Date: 08-2013
DOI: 10.5694/MJA13.10161
Abstract: To investigate whether General Practice Management Plans (GPMPs), Team Care Arrangements (TCAs) and reviews of these improve the management and outcomes of patients with diabetes when supported by cdmNet, a web-based chronic disease management system and to investigate adherence to the annual cycle of care (ACOC), as recommended in diabetes guidelines. A before-and-after study to analyse prospectively collected data on 577 patients with type 1 or 2 diabetes mellitus who were managed with a GPMP created using cdmNet between June 2008 and November 2012. Completion of the clinical tests in the ACOC (process outcome) and values of six of these clinical measurements (clinical outcomes). Significant improvements were seen after creation of a GPMP in the proportion of ACOC clinical tests completed (57.9% v 74.8%, P < 0.001), total cholesterol level (P < 0.01), low-density lipoprotein (LDL) cholesterol level (P < 0.001) and body mass index (BMI) (P < 0.01). Patients using GPMPs and TCAs also improved their glycated haemoglobin (HbA1c) level (P < 0.05). Patients followed up with irregular reviews had significant improvements in the proportion of ACOC clinical tests completed (59.2% v 77.6%, P < 0.001), total cholesterol level (P < 0.05), and BMI (P < 0.01), but patients with regular reviews had greater improvements in the proportion of ACOC clinical tests completed (58.9% v 85.0%, P < 0.001), HbA(1c) level (57.7 v 53.0 mmol/mol, P < 0.05), total cholesterol level (4.8 v 4.5 mmol/L, P < 0.05), LDL cholesterol level (2.8 v 2.4 mmol/L, P < 0.01) and diastolic blood pressure (76.0 v 74.0 mmHg, P < 0.05). There were significant improvements in process and clinical outcomes for patients on a GPMP or a GPMP and TCA, particularly when these were followed up by regular reviews. Patients using cdmNet were four times more likely to have their GPMP or TCA followed up through regular reviews than the national average.
Publisher: CSIRO
Date: 2021
DOI: 10.25919/V837-CZ33
Publisher: Elsevier BV
Date: 2003
Publisher: No publisher found
Date: 2022
DOI: 10.25919%2F8T3J-PP81
Publisher: CSIRO
Date: 2019
Publisher: Elsevier BV
Date: 06-2006
Publisher: CSIRO
Date: 2022
DOI: 10.25919/0XJN-WQ15
Publisher: Informa UK Limited
Date: 11-11-2019
Publisher: Wiley
Date: 08-12-2021
Publisher: Elsevier BV
Date: 03-2016
Publisher: Informa UK Limited
Date: 12-2018
Publisher: Elsevier BV
Date: 2022
Publisher: CSIRO
Date: 2013
Publisher: CSIRO
Date: 2013
Publisher: Department for Energy and Mining, South Australia / CSIRO
Date: 2018
Publisher: CSIRO
Date: 2013
Publisher: Elsevier BV
Date: 11-2019
Publisher: Elsevier BV
Date: 11-2018
Publisher: Geological Society of America
Date: 2016
Publisher: Elsevier BV
Date: 12-2015
Publisher: Elsevier BV
Date: 09-2022
Publisher: Copernicus GmbH
Date: 24-09-2021
DOI: 10.5194/SE-2021-108
Abstract: Abstract. A two-stage fuzzy inference system (FIS) is applied to prospectivity modelling and exploration-target delineation for REE deposits associated with carbonatite-alkaline complexes in 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-complexes-related REE mineral systems. In the first stage, three FISs are constructed to map the fertility and favourable geodynamic settings, favourable lithospheric architecture, and favourable shallow crustal (near-surface) 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 identification of prospective targets in the Kamthai-Sarnu-Dandeli and Mundwara regions, where project-scale detailed ground exploration is recommended. Low-confidence targets were identified in the south of the Siwana ring complex, north and northeast of Sarnu-Dandeli, south of Barmer, and south of Mundwara. Detailed geochemical s ling and 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 delineation of exploration targets in geodynamically similar regions globally such as Afar province (East Africa), Paraná-Etendeka (South America and Africa), Siberian (Russia), East European Craton-Kola (Eastern Europe), Central Iapetus (North America, Greenland and the Baltic region), and the Pan-superior province (North America).
Publisher: Geological Society of America
Date: 2016
Publisher: CSIRO
Date: 2020
Publisher: Informa UK Limited
Date: 12-2016
Publisher: Elsevier BV
Date: 11-2010
Publisher: Elsevier BV
Date: 2019
Publisher: CSIRO
Date: 2015
Publisher: CSIRO
Date: 2014
Publisher: Copernicus GmbH
Date: 23-03-2020
DOI: 10.5194/EGUSPHERE-EGU2020-19269
Abstract: & & The rare earth elements (REEs) are a group of seventeen metals including 15 lanthanides, scandium and yttrium. & These metals have been projected to be critical for future industrial development. However, India currently does not have any economic grade primary deposit of REEs all of India& #8217 s production comes from monazite-bearing beach sands along the eastern and western coasts that have been derived from REEs-enriched continental rocks such as pegmatites or carbonatites. This contribution documents a GIS-based prospectivity model for exploration targeting of REE associated with carbonatites and alkaline-complexes in the geologically permissive tracts of NW India comprising parts of western Rajasthan and northern Gujarat. A mineral systems approach is applied to model the key ingredients of an REE system including geodynamic setting fertile mantle/crustal sources of REEs deep to shallow crustal architecture and REE deposition. & This conceptual genetic model of REE mineral systems is, in turn, used to identify the key regional-scale REE-deposit targeting criteria in NW India. Regional-scale multi-parametric exploration datasets are processed to represent the targeting criteria in form of predictor GIS layers. Finally, an expert-driven fuzzy inference system is designed for delineating and raking prospective REE targets. Simultaneously, the stochastic and systemic uncertainties in the prospectivity modeling are modelled to delineated (a) high priority REE exploration targets areas with low uncertainty and high prospectivity for immediate ground follow up and (b) areas with high uncertainty and high prospectivity for further data acquisition in order to reduce uncertainty.& &
Publisher: Copernicus GmbH
Date: 14-03-2022
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 s ling 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).
Publisher: Society of Economic Geologists, Inc.
Date: 09-2023
DOI: 10.5382/ECONGEO.5009
Abstract: The Ruwai skarn deposit is the largest polymetallic skarn deposit in Borneo and is located in the Schwaner Mountains. The skarns and massive orebodies are hosted in marble of the Jurassic Ketapang Complex, which was intruded by Cretaceous Sukadana granitoids. The prograde-stage garnet and retrograde-stage titanite yielded U-Pb ages of 97.0 ± 1.8 to 94.2 ± 10.3 Ma and 96.0 ± 2.9 to 95.0 ± 2.0 Ma, respectively. These ages are similar to Re-Os ages obtained on sulfides (96.0 ± 2.3 Ma) and magnetite (99.3 ± 3.6 Ma). The U-Pb zircon ages reveal that magmatism at Ruwai occurred in three phases, including the Early Cretaceous (ca. 145.7 and 106.7–105.7 Ma andesite-dacite), Late Cretaceous (ca. 99.7–97.1 Ma diorite-granodiorite), and late Miocene (ca. 10.94–9.51 Ma diorite-dolerite). Based on geochemical and stable isotopic data (C-O-S) the Ruwai skarn ores are interpreted to have formed from oxidized fluids at ca. 160 to 670°C. The ore-forming fluids and metals were mostly magmatic in origin but with significant crustal input. Ruwai skarn mineralization occurred in the Late Cretaceous, associated with Paleo-Pacific subduction beneath Sundaland after the Southwest Borneo accretion. Ruwai is the first occurrence of Cretaceous mineralization recognized in the Central Borneo metallogenic belt.
Publisher: Wiley
Date: 12-2014
Publisher: Elsevier BV
Date: 03-2016
Publisher: CSIRO
Date: 2014
Publisher: Elsevier BV
Date: 08-2013
Publisher: Elsevier BV
Date: 08-2013
Publisher: Informa UK Limited
Date: 11-11-2019
Publisher: Copernicus GmbH
Date: 16-04-2021
DOI: 10.5194/SE-2021-42
Abstract: Abstract. Mineral exploration in areas comprising thick and complex cover represents an intrinsic challenge in Australia. Cost and time efficient methods that help to narrow down exploration areas are therefore of particular interest to the Australian mining industry and for mineral exploration world wide. Based on a case study around the Tarcoola gold mine in the regolith dominated South Australian Central Gawler Craton we suggest an exploration targeting workflow based on the joint analysis of surface and subsurface lineaments. The datasets utilized in this study are a digital elevation model and radiometrics that represent surface signals and total magnetic intensity and gravity attributed to subsurface signals. We compare automatically and manually mapped lineament sets derived from remotely sensed data. In order to establish an integrated concept for exploration through cover based on the best suited lineament data, we will point out the most striking differences between the automatically and manually detected lineaments and compare the datasets that represent surficial in contrast to subsurface structures. After determining which mapping technique is best suited for preliminary exploration in regolith dominated areas, such as the Central Gawler Craton, we will show how merging surface and subsurface lineament data may prove useful for mapping prospective areas. We propose that target areas are represented by areas of high lineament densities that are adjacent to regions comprising high density of intersections.
Publisher: Elsevier BV
Date: 08-2013
Publisher: Copernicus GmbH
Date: 29-04-2022
Abstract: Abstract. Mineral exploration in areas comprising thick and complex cover represents an intrinsic challenge. Cost- and time-efficient methods that help to narrow down exploration areas are therefore of particular interest to the Australian mining industry and for mineral exploration worldwide. Based on a case study around the Tarcoola gold mine in the regolith-dominated South Australian central Gawler Craton, we suggest an exploration targeting workflow based on the joint analysis of surface and subsurface lineaments. The datasets utilised in this study are a digital elevation model and radiometric data that represent surface signals and total magnetic intensity and gravity attributed to subsurface signals. We compare automatically and manually mapped lineament sets derived from remotely sensed data. In order to establish an integrated concept for exploration through cover based on the best-suited lineament data, we will point out the most striking differences between the automatically and manually detected lineaments and compare the datasets that represent surficial in contrast to subsurface structures. We further show how lineaments derived from surface and subsurface datasets can be combined to obtain targeting maps that help to narrow down areas for mineral exploration. We propose that target areas are represented by high lineament densities which are adjacent to regions comprising high density of lineament intersections.
Publisher: CSIRO
Date: 2010
Publisher: European Association of Geoscientists & Engineers
Date: 2019
Publisher: Elsevier BV
Date: 05-2006
Publisher: Elsevier BV
Date: 07-2022
Publisher: CSIRO
Date: 2017
Publisher: CSIRO
Date: 2018
Publisher: Elsevier BV
Date: 03-2016
Location: Australia
Start Date: 2023
End Date: 12-2027
Amount: $5,000,000.00
Funder: Australian Research Council
View Funded Activity