Exploration
V.S.S.A Naidu Badireddi; Vije durga raju Mullagiri; MVS sekhar Bezawada; Ambili V; K S N Reddy
Abstract
The Bavanapadu-Nuvvalarevu coastal sector in Andhra Pradesh, India, hosts substantial subsurface heavy mineral (HM) resources, presenting significant economic potential. This study employs ArcGIS raster techniques to estimate Total Heavy Mineral (THM) and Total Economic Heavy Mineral (TEHM) resources ...
Read More
The Bavanapadu-Nuvvalarevu coastal sector in Andhra Pradesh, India, hosts substantial subsurface heavy mineral (HM) resources, presenting significant economic potential. This study employs ArcGIS raster techniques to estimate Total Heavy Mineral (THM) and Total Economic Heavy Mineral (TEHM) resources in a 39 square kilometers area, integrating geospatial analysis with field data from core sediment samples. The findings reveal a total of 2.681953 million tons of THM, including 2.434422 million tons of TEHM, with the highest concentration observed in the top 1-meter sea bed sediment layer (1.605286 million tons). Ilmenite, garnet, and sillimanite dominate the mineral assemblage, accompanied by smaller quantities of zircon, monazite, and rutile, offering an estimated revenue potential of $634 to $851 million USD. The application of ArcGIS methodologies, particularly inverse distance weighting (IDW) interpolation, enabled precise mapping of HM distribution, despite challenges such as wide sample spacing and shallow core penetration. While the study highlights the economic and industrial significance of the Bavanapadu sector, it also underscores environmental concerns, including habitat disruption and sediment degradation, associated with mining. Sustainable practices, such as advanced separation technologies, site rehabilitation, and comprehensive environmental impact assessments (EIAs), are essential to mitigate ecological impacts. This research demonstrates the efficacy of GIS-based techniques in resource estimation and sustainable mining, offering a replicable framework for coastal and offshore mineral resource management globally. The findings provide critical insights into balancing economic growth with environmental preservation, setting a benchmark for responsible heavy mineral extraction in dynamic coastal environments.
Mohammad Rezaei; Milad Ghasemi
Abstract
Resource estimation and determining the grade distribution is one of the most important stages in planning and designing the open-pit and underground mines. In this work, a new mythology is used for resource estimation of the Angouran underground mine based on the optimized integration of the indicator ...
Read More
Resource estimation and determining the grade distribution is one of the most important stages in planning and designing the open-pit and underground mines. In this work, a new mythology is used for resource estimation of the Angouran underground mine based on the optimized integration of the indicator kriging (IK), simple kriging (SK), and inverse distance weighted (IDW) methods. For this purpose, waste blocks are first removed from the block model using the IK method. Then the amount of mineral resource is estimated using the SK and IDW methods. Indeed, variograms are developed to estimate the grade of zinc minerals in the three used methods. Variograms analysis in three directions prove that the studied resource is anisotropic. Also the validation results confirm that the correlation coefficients between the measured and estimated zinc values by the SK and IDW methods equal to 0.76 and 0.75, respectively. Knowing this satisfactory result, a 3D model of the resource is prepared using the IK method, in which the ore and waste sections of the Angouran underground mine are separated definitely. According to the above methodology, the calculated resource of the Angouran underground mine using the SK method is achieved 1373962.5 tons with an average grade of 30.11%, whereas the estimated amount of this resource is attained 1349325 tons with an average grade of 31.88% using the IDW approach. The verification results show that the suggested methodology based on the optimized integration of the IK, SK, and IDW methods can be successfully applied for resource modeling and grade estimating of the Angouran underground mine.
Exploitation
H. Moini; F. Mohammad Torab
Abstract
Kriging is an advanced geostatistical procedure that generates an estimated surface or 3D model from a scattered set of points. This method can be used for estimating resources using a grid of sampled boreholes. However, conventional ordinary kriging (OK) is unable to take locally varying anisotropy ...
Read More
Kriging is an advanced geostatistical procedure that generates an estimated surface or 3D model from a scattered set of points. This method can be used for estimating resources using a grid of sampled boreholes. However, conventional ordinary kriging (OK) is unable to take locally varying anisotropy (LVA) into account. A numerical approach has been presented that generates an LVA field by calculating the anisotropy parameters (direction and magnitude) in each cell of the estimation grid. After converting the shortest anisotropic distances to Euclidean distances in the grid, they can be used in variography and kriging equations (LVAOK). The ant colony optimization (ACO) algorithm is a nature-inspired metaheuristic method that is applied to extract image features. A program has been developed based on the application of ACO algorithm, in which the ants choose their paths based on the LVA parameters and act as a moving average window on a primary interpolated grid. If the initial parameters of the ACO algorithm are properly set, the ants would be able to simulate the mineralization paths along continuities. In this research work, Choghart iron ore deposit with 2,447 composite borehole samples was studied with LVA-kriging and ACO algorithm. The outputs were cross-validated with the 111,131 blast hole samples and the Jenson-Shannon (JS) criterion. The obtained results show that the ACO algorithm outperforms both LVAOK and OK (with a correlation coefficient value of 0.65 and a JS value of 0.025). Setting the parameters by trial-and-error is the main problem of the ACO algorithm.
B. A. Mert
Abstract
This paper presents the procedures used for determining and defining the tonnage and grade of the coalfields of Kangal basin from the developed GIS-aided block model. In this work, firstly, all the lithological logs of drill holes and chemical analysis data of core in the basin were analyzed with the ...
Read More
This paper presents the procedures used for determining and defining the tonnage and grade of the coalfields of Kangal basin from the developed GIS-aided block model. In this work, firstly, all the lithological logs of drill holes and chemical analysis data of core in the basin were analyzed with the help of geostatistics, and then the digital raster maps of each one of the attributes such as the thickness, calorific value (LCV), ash content (AC%), moisture content (MC%), and surface maps of lignite seams were mapped in GIS environment. In the second stage, quantities of the overburden and resources with different categories were calculated on the basis of field-based quality and volume queries with the help of the digital maps on GIS platform. As a result, it was estimated that the Kalburçayırı field had a tonnage of 116 Mt of lignite with an LCV of 1308 kcal/kg, the Hamal field had a tonnage of 30 Mt of lignite with an LCV of 987 kcal/kg, and the Etyemez field had a tonnage of 48 Mt of lignite with an LCV of 1282 kcal/kg. Also it was estimated that almost 24,278,151 tons of lignite in the Hamal and Etyemez fields had a quality of less than 950 kcal/kg that could be directly fired without the blending process in the power plant. As a consequence, the Hamal and Etyemez fields should go into production as soon as possible and be fired in the power plant after being mixed with the lignite in the Kalburcayırı field so that they can be redounded to economy.
Exploitation
B. Unver
Abstract
The prerequisite of maintaining an efficient and safe mining operation is the proper design of a mine by considering all aspects. The first step in a coal mine design is a realistic geometrical modelling of the coal seam(s). The structural features such as faults and folding must be reliably implemented ...
Read More
The prerequisite of maintaining an efficient and safe mining operation is the proper design of a mine by considering all aspects. The first step in a coal mine design is a realistic geometrical modelling of the coal seam(s). The structural features such as faults and folding must be reliably implemented in 3D seam models. Upon having a consistent seam model, the attributes such as calorific value, ash and moisture contents, volatile matter, and sulfur must be estimated in the block model. Considering the geotechnical and hydrogeological conditions, the most appropriate mine design strategy can be selected and implemented. Application of the above steps to three coal basins in Turkey are presented in this paper. The Soma-Eynez and Tunçbilek-Ömerler basins are the two most important lignite resources having an on-going production and prospect for future underground mining. Comprehensive 3D coal seam modelling is carried out at both basins. As both are extensively faulted due to tectonism, it is a challenging task to realistically model their structures. On the other hand, the Karapınar basin has a considerably different geological, structural, and coal measure rock conditions in comparison to the Eynez-Ömerler basin. The Karapınar basin is a relatively recently explored brown field site suitable mainly for surface mining. Coal seam(s) geometry and quality-related attributes certainly play the most important role for production planning and mining activities. The influence of the inherent characteristics of each site on the modelling and mine design strategy are also briefly discussed. This paper presents the fundamentals of coal seam modelling at various geological and structural conditions. It is believed that the methodology presented in this paper can be considered as a guiding example for a comprehensive 3D modelling and resource estimation of coal seams around the world.
