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The western Murray Basin obscures the interpreted transition between Proterozoic and Phanerozoic rocks of Australia in the upper crust, often referred to as the Tasman Line. The South Australian part of this continental margin has been interpreted, based on sparse extrapolated constraints, to have sat in various geodynamic settings associated with a Cambrian subduction system. We use newly acquired multi-disciplinary datasets and the results of the MinEx CRC Delamerian National Drilling Initiative program to elucidate the architecture of this hidden Cambrian margin, revealing unrecognised potential for a spectrum of mineral systems. Whilst it has been accepted for a number of years that the Stavely Zone in western Victoria represents a volcanic arc in the mid-Cambrian, continent-ward belts to the west (beneath the Murray Basin), have had uncertain affinities. With the results of recent drilling, we show that both regional, and highly partitioned back-arc extension were present in the period 515-500 Ma, and speculate that inherited structure in pre-Cambrian basement rocks are responsible for the variation in deformation styles present in drill core., Open-Access Online Publication: May 29, 2023

Australian sediment-hosted mineral systems are important sources of base metals and critical minerals that are vital to delivering Australia’s low-carbon economy. In Australia, sediment-hosted resources account for ~82% and ~86% of the total zinc (Zn) and lead (Pb) resources respectively. Given their significance to the Australian economy, four national-scale mineral potential models for sediment-hosted Zn-Pb mineral systems have been developed: clastic-dominated siliciclastic carbonate, clastic-dominated siliciclastic mafic, Mississippi Valley-type and Irish-type. In addition to the potential for Zn-Pb mineralisation, the uncertainty related to data availability has been examined. The mineral potential models were created using a mineral systems-based approach where mappable criteria have been used to assess the prospectivity of each system. Each model has been derived from a large volume of precompetitive geoscience data. The clastic-dominated siliciclastic carbonate mineral potential model predicts 92% of known deposits and occurrences within 15.5% of the area, the clastic-dominated siliciclastic mafic mineral potential model predicts 85% of deposits and occurrences within 27% of the area, and the Mississippi Valley-type mineral potential model predicts 66% of known deposits and occurrences within 31% of the area. Each model successfully predict the location of major sediment-hosted Zn-Pb deposits while highlighting new areas of elevated prospectivity in under-explored regions of Australia, reducing the exploration search space by up to 85% for sediment-hosted Zn-Pb mineral systems.

The application of deep learning algorithms in mineral prospectivity mapping (MPM) is a hot topic in mineral exploration. However, few studies have focused on recurrent neural networks (RNNs) in terms of integrating different evidential layers to map mineral potential. In this study, a gated recurrent unit (GRU) model was employed for MPM using a case study on the Baguio District of Philippines. To generate sufficient training samples for GRU, data augmentation with geological constraints was employed. To explore the influence of different orders of evidence layers, as inputs of RNN, a total permutation of the evidence layers was built. Meanwhile, a nonlinear controlling function was used to capture the spatial relationships between known mineral deposits and geological controlling factors and assign the value for each pixel of evidence layers. The obtained results demonstrated the excellent performance of GRU in MPM. The delineated high-anomaly areas show close spatial relationships with known mineral deposits and therefore can provide significant clues for the next round of mineral exploration in the study area.

As a part of National Geochemical Mapping (NGCM) programme of GSI, regional geochemical mapping was carried out for an area of 705 sq km in parts of Katni, Panna and Satna districts of Madhya Pradesh covering toposheet number 64A/05 bounded by latitudes N23°45′00″ to N24°00′00″ and longitudes E80°15′00″ to E80°30′00″. Chemical analyses of 182 composite stream/slope sediments samples were carried out and baseline geochemical maps of oxides and elements were prepared. Data analyses has led to significant conclusions on environment hazard due to metal contamination and possible mineral potential due to REE enrichment. Study of the spatial distribution of individual variables showed Cr and Co have values higher than the permissible level in dry soils in some parts of the area which requires investigation by concerned agencies. Some samples over the laterites show higher than threshold values of REEs which are much higher than their crustal abundance. Factor analyses on the geochemical data with 46 oxides and elements has led to the identification of five factors accounting for 84% of the total variance of the data set and describing five physico-chemical processes controlling the spatial geochemical variation. The analyses points to the enrichment of the REEs in the lateritisation process. The laterites covering 171 sq km of the area need to be considered for investigation of REE potential.

In this study, ASTER imagery, geochemical, lithological, and structural data are exploited for Mineral Potential Mapping (MPM) of the Astaneh granitic pluton and its surrounding area. The independe...

This paper reports an application of uncertainty visualisation of a regional scale (1:50 000) 3D geological geometry model to be involved in GIS-based 3D mineral potential assessment of the Xiangxibei lead-zinc mineral concentration area in northwestern Hunan District, China. Three-dimensional (3D) geological modelling is a process of interpretation that combines a set of input measurements in geometry. Today, technology has become a necessary part of GIS-based deep prospecting. However, issues of sparse data and imperfect understanding exist in the process so that there are several uncertainties in 3D geological modelling. And these uncertainties are inevitably transmitted into the post-processing applications, such as model-based mineral resource assessment. Thus, in this paper, first, a big-data-based method was used to estimate the uncertainty of a 3D geological model; second, a group of expectations of geological geometry uncertainty were calculated and integrated into ore-bearing stratoisohypse modelling, which is one of the major favourable parameters of assessment for Lead-Zinc (Pb-Zn) deep prospectivity mapping in northwestern Hunan; and finally, prospecting targets were improved.

The purpose of this contribution is to highlight four topics of regional and worldwide mineral resource prediction: (1) use of the jackknife for bias elimination in regional mineral potential assessments; (2) estimating total amounts of metal from mineral potential maps; (3) fractal/multifractal modeling of mineral deposit density data in permissive areas; and (4) worldwide and large-areas metal size-frequency distribution modeling. The techniques described in this paper remain tentative because they have not been widely researched and applied in mineral potential studies. Although most of the content of this paper has previously been published, several perspectives for further research are suggested.

The data-driven index overlay technique is an amended version of the conventional index overlay method, which has been utilized for mineral potential modeling (MPM) in brown-fields exploration, whereby a data-driven way is utilized to determine the relative significance of both individual evidence maps and evidential values. Although this method evades exploration bias in the conventional index overlay MPM resulting from categorization of evidential maps into some optional classes, it still possesses two major issues: (i) since this technique utilizes the plots of prediction-area (P-A) for defining the importance degree of every evidential map, it carries exploration bias resulting from the use of known mineral occurrences (KMOs) and (ii) it is not applicable in green-fields areas where there may be no KMOs. In this study, we propound an improved index overlay MPM to overcome the deficiencies described above, whereby every individual evidential map is rendered a weight without expert opinion and without the use of KMOs through a modified Shannon’s entropy method. To illustrate this procedure, we applied it to the brown-fields Dolatabad district of southern Iran as a MPM case study for podiform chromite deposits. The results indicated that the improved index overlay approach outperformed the data-driven index overlay method for modeling the potential of the podiform chromite deposits. After successful testing of the improved index overlay technique, we applied it to the green-fields Birjand district of eastern Iran in order to ascertain promising zones for further detailed exploration of the targeted deposit.

The South African gold mining sector remains a significant contributor to the country’s economy. Facing several challenges that hinder the realisation of South Africa’s full mineral potential, the sector’s sustainability and profitability can be enhanced through implementing operational improvement measures. Mobile cooling units (MCUs) were identified as a potential focus area for operational improvement. MCUs are used as tertiary or in-stope cooling in hot underground workings. In this paper, a method was presented to characterise the performance of existing MCUs based on three key performance indicators (KPIs), namely, the wet-bulb temperature ratio (WTR), efficiency and position. Optimisation strategies were then elected and implemented based on these KPIs. The implementation of this method in a South African gold mine attained a reduction in pumped water volumes, reduced operating costs through electricity cost savings and improvements in underground ventilation air temperatures.

This paper introduces the concept of geodata science-based mineral prospectivity mapping (GSMPM), which is based on analyzing the spatial associations between geological prospecting big data (GPBD) and locations of known mineralization. Geodata science reveals the inter-correlations between GPBD and mineralization, converts GPBD into mappable criteria, and combines multiple mappable criteria into a mineral potential map. A workflow of the GSMPM is proposed and compared with the traditional workflow of mineral prospectivity mapping. More specifically, each component in such a workflow is explained in detail to demonstrate how geodata science serves mineral prospectivity mapping by deriving geoinformation from geoscience data, generating geo-knowledge from geoinformation, and allowing spatial decision-making by integrating geoinformation and geo-knowledge on the formation of mineral deposits. This review also presents several research directions for GSMPM in the future.

The Gilan-e-Gharb block is known as a prospective area for hydrocarbon resources in the form of oil, gas in deep potential and natural bitumen (Gilsonite) on the surface. Natural bitumen is not clearly detectable by geochemical or geophysical methods. Hereupon, identifying high potential areas for further exploration, attempted with the help of AHP-Fuzzy and TOPSIS methods. The comprehensive database of geological and geostructural records, satellite imagery analysis by remote sensing and mine indexes counted as the inputs for this method. First, the lithological unit as the main mineralization hosts determined with respect to the dominant geological structures as a factor of controlling natural bitumen placement (fold, fracture and faults) in the Gilan-e-Gharb block. The Gachsaran, Asmari, Pabdeh and Gurpi Formations identified as the most important lithological units for mineralization. Placement and distribution of natural bitumen mineralization in the form of mine indexes are added to the geology database. Finally, we assigned appropriate weights to applied information layers using Analytical Hierarchy Processing (AHP) based on knowledgeable information and field studies to synthesize exploratory data. Then, we used the FTOPSIS method to define the Positive Ideal Solution (FPIS, A+) that allows maximizing the beneficial characteristics and minimizing the impediment characteristics and the Negative Ideal Solution (FNIS, A-) that minimizes the beneficial characteristics and maximizes the impediment characteristics. This method, as a new approach in the exploration of minerals with a shortage of data, is applicable to other mineral deposits.

Magnetotelluric (MT) data allow geoscientists to investigate the link between mineralisation and lithospheric-scale features and processes. In particular, the highly conductive structures imaged by MT data appear to map the pathways of large-scale palaeo-fluid migration, which is an important element of several mineral systems. New data were collected as part of the Australian Lithospheric Architecture Magnetotelluric Project (AusLAMP) under Geoscience Australia Exploring for the Future (EFTF) program in northern Australian. We use this dataset to demonstrate that the MT method is a valuable tool for mapping lithospheric-scale features and for selecting prospective areas for mineral exploration. Our results image a number of major conductive structures at depths up to ~200 km or deeper in the survey region, for example, the Carpentaria Conductivity Anomaly in east of Mount Isa; and the Tanami Conductive Anomaly along the Willowra Suture Zone. These significant anomalies are lithospheric- scale highly conductive structures, and show spatial correlations with major suture zones and known mineral deposits. These results provide important first-order information for lithospheric architecture and possible large footprint of mineral systems. Large-scale crustal/mantle conductivity anomalies mapping fluid pathways associated with major sutures/faults may have implications for mineral potential. These results provide evidence that some mineralisation occurs at the gradient of or over highly conductive structures at lower crustal and lithospheric mantle depths. These observations provide a powerful means of highlighting greenfields for mineral exploration in under-explored and covered regions.

Geologically, the province of Central Sulawesi is composed of various types of rocks, both in the form of igneous, sedimentary and metamorphic rocks. Regarding Central Sulawesi Province, mineral resources both metal and non-metal are quite varied. Increasing demand and demand for minerals, both metals, and non-metals. Research conducted to study the mineral potential in one of the regencies in Central Sulawesi Province. This research was conducted in Galang Sub-district, Tolitoli Regency, and Central Sulawesi Province by using the resistivity method and the Induced Polarization (IP) method with the Wenner-Schlumberger arrangement consisting of eight lines. The IP method is very accurate to discuss the potential of minerals that are below the surface. The inversion process does data processing in order to obtain the actual form of resistivity and chargeability modeling. Based on the modeling, the mineral potential in Galang Sub-district, Tolitoli Regency, Central Sulawesi Province is mostly found in all trajectories namely lane 01; 02; 04; 05; 05; 06; 07. Which is marked by a very high chargeability value between 300 msec - 500 msec. The research area also discusses granite and andesite, which have high resistivity values, between 2000 Ωm – 400000 Ωm.

Magnetotelluric (MT) data allow geoscientists to investigate the link between mineralisation and lithospheric-scale features and processes. In particular, the highly conductive structures imaged by MT data appear to map the pathways of large-scale palaeo-fluid migration, which is an important element of several mineral systems. New data were collected as part of the Australian Lithospheric Architecture Magnetotelluric Project (AusLAMP) under Geoscience Australia (GA)'s Exploring for the Future (EFTF) program in northern Australia. We use this dataset to demonstrate that the MT method is a valuable tool for mapping lithospheric-scale features and for selecting prospective areas for mineral exploration. Given the importance of MT data, Geoscience Australia, state and territory geological surveys, and research organisations have united under the Australian Lithospheric Architecture Magnetotelluric Project (AusLAMP) to collect long-period MT data across the continent on a ~55 km-spaced grid (Figure 1). Our results image a number of major conductive structures at depths up to ~200 km or deeper in the survey region, for example, the Carpentaria Conductivity Anomaly east of Mount Isa and the Tanami Conductivity Anomaly along the Willowra Suture Zone. These significant anomalies are highly conductive lithospheric-scale structures, and show spatial correlations with major suture zones and known mineral deposits. These results provide important first-order information for lithospheric architecture and identifying the broad footprint of mineral systems. Large-scale crust/mantle conductivity anomalies that map fluid pathways associated with major sutures/faults may have implications for mineral potential. These results provide evidence that some mineralisation occur at the gradient of or over highly conductive structures at lower crustal and lithospheric mantle depths. These observations provide a powerful means of highlighting greenfields for mineral exploration in under-explored and covered regions., Open-Access Online Publication: March 03, 2023

The accuracy of data-driven predictive mineral prospectivity models relies heavily on the training datasets used. These models are usually trained using data for “known” deposit locations as well as “non-deposit” locations that are based on randomly generated point patterns. In this study, data related to the Seabridge Gold Inc Iskut project, an epithermal Au deposit in northwestern British Columbia (BC), Canada, are used to test the utility of data-driven mineral prospectivity modeling. The input spatial dataset is comprised mostly of publicly available data. Data for 18 vein and epithermal Au known mineral occurrences (KMO) are obtained from the BC Geological Survey’s MINFILE repository and selected as training deposit locations. A total of eleven sets of non-deposit locations (NDL) were also created, including one set of selected non-prospective KMO for Au deposits from the MINFILE and ten sets of random point patterns. Given the scale of this study, most of the KMO recorded on the property are of the epithermal deposit type. Hence, they could not be used as a selection criterion. Data-driven mineral potential models are generated using the random forest (RF) algorithm and trained on multiple data sets. The comparison of RF models demonstrated that using non-prospective KMO generates more accurate predictions than the random point pattern. The produced mineral prospectivity maps delineated multiple areas with higher discovery potential, which matched viable targets for the Au-Cu epithermal-porphyry system identified through previous Seabridge Gold Inc. (Toronto, ON, Canada) field reconnaissance and drilling programs.

With the increasing use of machine learning for big data analytics, several methods have been implemented for the purpose of exploration targeting using mineral potential mapping in a GIS environment. Random forests (RF) have been successfully applied to data-driven mineral potential mapping using relatively small numbers of input maps that have typically been pre-classified by a geologist familiar with the mineral system being targeted. However, it is useful to understand how well RF perform for mineral potential mapping when a large number of multi-class categorical or non-thresholded numeric input maps are used in the classification or when weighted or ranked training data are used. Four different implementations of RF are presented to examine how the results vary depending on the degree of intervention from an expert in the modeling process. A case study has been devised using data from the eastern Lachlan Orogen in New South Wales (Australia) for the purposes of targeting porphyry Cu–Au mineralization related to the Macquarie Arc. The results demonstrate that the use of a large number of multi-class categorical or non-thresholded numeric predictive input maps results in a poor mineral potential map outcome. An expert review to determine reclassifications or thresholds that produce geologically meaningful maps as proxies for the mineral system being targeted results in more effective RF-based mineral potential maps being produced. Weighting or ranking the deposits used as training data produces more narrowly defined prospective areas that may assist with targeting tier-one economic deposits. Comparison of the RF results to a standard weights of evidence analysis highlighted some significant differences in which predictive maps should be considered important for modeling, and in the extent of prospective area delineated from each output mineral potential map.

Indonesia has an abundant amount of basalt rocks resources, including in East Lampung Regency of Lampung Province. This basalt has not been used optimally and only be used as a foundation. The use of basalt as soil fertilizer also known as the stone meal. This study focused on the effect of using basalt dust on the growth and development of organic fertilizer application for the cassava plant. This study is to support the local government policies that declared Lampung as a national development centre of cassava, with a production rate of 30.8% of the national production of cassava. Basalt powder was characterized using test petrograph and X-ray Fluorescence (XRF) for a description of microscopic and chemical composition. The test results were used to determine the chemical composition of rock classification using the TAS diagram. The experiments of applying fertilizer on cassava crops in the demonstration plots 8 treatment x 3 repetitions were conducted by adding the percentage by weight of the basalt towards organic fertilizer between 0% (control 1), 10%, 20%, 30%, 40%, 50%, 60%, and without treatment (control 2). The results indicated that basalt from East Lampung is classified as olivine Tholeite basalt which is rich in CaO, Mg and Na 2 O + K 2 O. The growth rate of cassava plants which are affected by basalt powder presentation is characterized by a value which is higher than the value of CGR control, and recommended to not exceed 10% of the weight of basalt fertilizer.

Naraul Formation of the Larji Group in Kulu district of Himachal Pradesh contains the major strata bound Copper mineralization at many places as observed through old working near Naraul, Danala and Kanda in Sainj Valley of Kulu district exposing the Proterozoic Northwestern Himalayan belt. The same structural belt is also known for Silver mineralisation around Manikaran. At Naraul, a regional stratigraphic and mineralogical framework of the Naraul Formation for mineralogical resource assessment was viewed. The old workings within 4-5 km long and 200-300m wide along the NW- SE trending structural trend cover the main ore potential zones. The ore mineralisation seems to be alike the copper silver deposit of the Revett Formation of Montana and Idaho, USA. The deposit in Naraul needs further more drilling investigation and exploration for actual reserve assessment.

We collected 38 groundwater and two surface-water samples in the semi-arid Lake Woods region of the Northern Territory to better understand the hydrogeochemistry of this system, which straddles the...

The exploration industry of Ukraine is experiencing a protracted crisis. It is confirmed by the curtailment of funding for the development of country mineral resources by 60% last year which causes the closure of exploration companies. The range of problems traditionally solved by the geography of mineral resources is significantly reduced. These reasons encouraged us to consider the main methodological approaches to the study of mineral potential of specific regions. The studied approaches such as natural-geographical, economic-geographical, ecological-geographical, and complex structural-geographical lie in the domain of geographical science. The article emphasizes the urgency to develop structural and geographical course of research, which is based on the studies of mineral resources and the approaches mentioned above including geological one. The structural and geographical course of research is supposed to create real models of mineral resources of the country regions and to suggest specific measures of their structure optimization alongside prospects of their development following modern world tendencies. The research may result in the creation of a long-term concept of balanced development of the mineral complex of the region, the prevision of the use of mineral resources, the justification of resource-saving technologies. A systematic approach to such a concept will ensure the rational use of resources, the formation of new infrastructure, conditions for environmentally safe function of the economy, sustainable and balanced development of the economic complex of the region.

Structural permeability is a major consideration in assessing mineral potential of a given geological setting. This chapter introduces different geodynamic set ups, supercontinental assemblies, break ups and dispersals, and their possible relationship with formation and preservation of various types of ore deposits. Craton and metallogenic district level structures, and magmatism are discussed with examples and relevant geological maps. The later part of the chapter contains the most illustrated sections that depict and describe classical structural features related to faults and their reactivations, breccia looking structures, shear zones, folds and associated planar and linear structures. The structural assessment is strongly supported by geological maps and over 130 thematic photographs. It is believed that this chapter will enhance the power to comprehend structural features in field.

The aim of this work is to develop a simple and effective approach for surficial iron mineral potential zone identification and mapping using optical remote sensing data. Thus, an iron mineral potential model (IMPM) was developed by combining multiple band ratios for iron mineral detection. The developed method was applied on the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data from Malmberget and nearby area from Gallivare district, Norrbotten county, Sweden. The results from the study area revealed that the developed approach is effective in iron mineral potential zone mapping using ASTER data with more than 90% accuracy.

The Rare Earth Element (REE) mineralizations are not so &ldquo, rare&rdquo, in Sweden. They normally occur associated and hosted within granitic crystalline bedrock, and in mineral deposits together with other base and trace metals. Major REE-bearing mineral deposit types are the apatite-iron oxide mineralizations in Norrbotten (e.g., Kiruna) and Bergslagen (e.g., Gr&auml, ngesberg) ore regions, the various skarn deposits in Bergslagen (e.g., Riddarhyttan-Norberg belt), hydrothermal deposits (e.g., Olserum, Bastn&auml, s) and alkaline-carbonatite intrusions such as the Norra K&auml, rr complex and Aln&ouml, In this study, analytical data of samples collected from REE mineralizations during the EURARE project are compared with bedrock and till REE geochemistry, both sourced from databases available at the Geological Survey of Sweden. The positive correlation between REE composition in the three geochemical data groups allows better understanding of REE distribution in Sweden, their regional discrimination, and genetic classification. Data provides complementary information about correlation of LREE and HREE in till with REE content in bedrock and mineralization. Application of principal component analysis enables classification of REE mineralizations in relation to their host. These results are useful in the assessment of REE mineral potential in areas where REE mineralizations are poorly explored or even undiscovered.

Post 9/11 USGS research on the prospectivity, or mineral potential mapping, of Afghanistan’s mineral wealth led commentators, governments and the US military to promote the mineral resources of Afghanistan as enough to fundamentally alter the Afghan economy and perhaps the Afghan war itself. Afghanistan’s prospectivity however was of little surprise to economic geologists and is some of the most highly prospective ground in the world.

The distribution patterns of trace elements are a very useful tool for the prediction of mineral deposits occurrence and possible future exploitation. Machine learning techniques were used for the computation of adequate models in trace elements’ prediction. The main subject of this research is to define an adequate model to predict the amounts of Sn and W in the abandoned mine area of Lardosa (Central Portugal). The geochemical composition of 333 stream sediment samples collected in the study area was used. Total concentrations of As, B, Be, Cd, Co, Cr, Cu, Fe, Ni, P, Sn, U, V, W, Y, and Zn were used to define the best prediction model. Different machine learning techniques were tested: decision trees (CART), multilayer perceptron (MLP) and support vector machines (SVM) For regression and clustering, CART, MLP and SVM for the classification problem. These algorithms were used with six different inputs – N1 to N6 - to pick out the best-performing model. The results indicate that CART achieves the best predictions for Sn and W. In the regression process, correlation coefficients of 0.67 for Sn (with Input N1) and 0.70 28 for W (with Input N3) were obtained. Regarding the classification problem, an error rate of 0.10 for both Sn (Input N1) and W (Input N2) was reached. The classification process is the best methodology to use in the prediction of Sn and W using the trace element concentration of stream sediments from Lardosa area., Thanks are due to Prof. M.R. Machado Leite for the use of data on stream sediments from Instituto Geológico e Mineiro, S. Mamede de Infesta (Portugal). C. Iglesias acknowledges the Spanish Ministry of Education, Culture and Sports for FPU 12/02283 grant. This research was carried out under the CERENA/FEUP (Natural resources and Environment Center), Portugal. The author acknowledges the funding provided by the Institute of Earth Sciences (ICT), under contracts UID/ GEO/04683/2013 with FCT (the Portuguese Science and Technology Foundation) and COMPETE POCI-01-0145-FEDER-007690.

Structural equation modeling (SEM) was applied here to modify the ordinary weights-of-evidence (WofE) method for calculating posterior probability to improve conditional independence (CI) in the application of this method mineral potential prediction. The new method attempts to reduce the effect of CI by defining new binary patterns with an optimum combination of cutoff values of patterns. The solution is calculated through SEM, and the goodness of fit between evidence and mineral deposit occurrences is evaluated by a specified target function. The main difference between the new WofE and ordinary WofE is that evidence in the new method maintains a balance between the significance for mineral potential prediction and CI, rather than the significance for mineral prediction only as in ordinary WofE. A case study of prediction of potential for hydrothermal Au mineral deposits in Nova Scotia, Canada, is discussed here. The results indicate that the new method performs better than the ordinary WofE.

In this work, a quantifier-guided ordered weighted averaging (OWA) method was employed for mineral potential mapping (MPM) in Nowchun Cu–Mo prospect, SE Iran. The proposed knowledge-driven method has the capability of incorporating the geologists’ preference (weight) and attitude toward risk analysis during MPM. Since quantitative determination of OWA parameters is a tough task, employing linguistic quantifiers aid geologists to simply define their desired strategy for MPM. To implement the method, eight weighted criteria spatially associated with mineralization were derived from geological, geochemical and geophysical datasets. The evidential layer integration was implemented using various OWA operators, which is generated by employing seven linguistic quantifiers. As a result, seven mineral potential maps, which report favorability index from 0 to 1, were produced in a spectrum range of risk from extremely optimistic to extremely pessimistic. According to results, the western and southeastern part of the study area were detected as regions with the lowest and highest mineral favorability. For validation, the results of subsequent geological field works and 106 drilled boreholes were taken into account. The evaluation indicated that the mineral potential map based on the “Some” quantifier has the highest correspondence with underground 3D mineralization zones of Cu and Mo. The mineral potential map based on the “Some” quantifier delineated two main prospective zones in the eastern and central-north parts of the study area. The former zone was recently investigated by drilling, but the latter zone was proposed for new drilling operation. Applying the proposed method in each scale of target delineation (a) generates various continuum favorability maps; (b) reveals mineralization patterns in the study area; and (c) provides an opportunity in exploration to select the optimal mineral potential map for detailed exploration tasks regarding the geologists’ attitudes toward risk and project budget.

Regional scale demarcation of alterations is an important preliminary step in mineral exploration. Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) imageries here have been used for alteration mapping and iron-rich (e.g., Gossans) area demarcation in a highly vegetated and relatively unexplored part of Eastern India, namely, South Purulia Shear Zone (SPSZ). The area is surrounded by mineral-rich Singhbhum Shear Zone (SSZ), but the mineral potentiality of SPSZ has not yet been proven. Alteration mineral assemblages are comprise of iron-rich alteration (gossan), clay alteration with varying amounts of iron content, sericitization, ferruginization and chloritization. In this paper, we discuss a few advantages and limitations of commonly used satellite image processing techniques for mineral mapping. We integrate the outputs of band ratio, Principal Component Analysis (PCA), PCA-loading, and thresholding; termed as Directed PCA (DPCA) for delineating mineral potential areas. Our approach mapped the alteration zones with overall 74% accuracy. Our study leads to demarcation of 28% alteration area within a 10 km wide and 60 km long stretch of SPSZ. Two areas, namely, Lawa (23° 1′ 39.31″ N, 86° 4′ 2.55″ E) and Sindurpur (23° 4′ 38.30″ N, 86° 5′ 3.99″ E) were identified as mineral potential zone. Samples from those areas were studied using XRF, microscope and SEM with the conclusive presence of mineralization. Lawa is potential for hydrothermal polymetallic sulfides along with gold mineralization. Sindurpur is potential for secondary iron and manganese mineralization. The study shows that DPCA is a useful tool for ASTER data processing for narrowing target area in preliminary stages of exploration in vegetated zones.

This paper reviews governance challenges and opportunities in six Central American and Caribbean countries (Belize, Dominican Republic, Guatemala, Honduras, Nicaragua and Panama) as they develop new extractive projects. Despite important differences, governments in these countries share the need to improve their capacity to manage and control growing mining operations and potential revenues. In this paper we argue that mineral extraction faces challenges that go beyond traditional prescriptions to strengthen governance, such as environmental impacts and the cost born by local communities in terms of loss of land, water sources and culture; the right to free, informed and fair consultation; and polarization among the different stakeholders. Yet, we claim that transparency offers a starting point for governments to build trust and to demonstrate that they are prepared to address concerns surrounding mining operations, managing potential mineral windfalls and taking into consideration local community interests.

It presents discussion on scientific and technical problems of rational use of spatial resources steeply dipping deposits in open-pit mine М uruntau. This work discuss basis of following directions for use and functional purpose of the formation of technogenicdeposit in open-pit development: storage rocks, providesecurity works, stabilization of technological processes, formation of structural elements of open-pit mine. Based on analysis of use of technology external and internal dumping in opencast mining in the development of steep deposits installed,that formation of external and internal dumps should occur in a coordinated manner with the development of opencast goaf. The introduction of received results allow to improve efficiency of development of mineral potential with production increase of high liquidity on the world market and improvement of technical and economic parameters of mining operations.