Subjects -> MINES AND MINING INDUSTRY (Total: 81 journals)
Showing 1 - 42 of 42 Journals sorted alphabetically
American Mineralogist     Hybrid Journal   (Followers: 16)
Applied Earth Science : Transactions of the Institutions of Mining and Metallurgy     Hybrid Journal   (Followers: 4)
Archives of Mining Sciences     Open Access   (Followers: 3)
AusiMM Bulletin     Full-text available via subscription   (Followers: 1)
BHM Berg- und Hüttenmännische Monatshefte     Hybrid Journal   (Followers: 2)
Canadian Mineralogist     Full-text available via subscription   (Followers: 7)
Clay Minerals     Hybrid Journal   (Followers: 9)
Clays and Clay Minerals     Hybrid Journal   (Followers: 5)
Coal Science and Technology     Full-text available via subscription   (Followers: 3)
Contributions to Mineralogy and Petrology     Hybrid Journal   (Followers: 14)
Environmental Geochemistry and Health     Hybrid Journal   (Followers: 2)
European Journal of Mineralogy     Hybrid Journal   (Followers: 14)
Exploration and Mining Geology     Full-text available via subscription   (Followers: 3)
Extractive Industries and Society     Hybrid Journal   (Followers: 2)
Gems & Gemology     Full-text available via subscription   (Followers: 2)
Geology of Ore Deposits     Hybrid Journal   (Followers: 5)
Geomaterials     Open Access   (Followers: 3)
Geotechnical and Geological Engineering     Hybrid Journal   (Followers: 9)
Ghana Mining Journal     Full-text available via subscription   (Followers: 3)
Gold Bulletin     Hybrid Journal   (Followers: 2)
Inside Mining     Full-text available via subscription  
International Journal of Coal Geology     Hybrid Journal   (Followers: 4)
International Journal of Coal Preparation and Utilization     Hybrid Journal   (Followers: 2)
International Journal of Coal Science & Technology     Open Access   (Followers: 1)
International Journal of Hospitality & Tourism Administration     Hybrid Journal   (Followers: 15)
International Journal of Mineral Processing     Hybrid Journal   (Followers: 8)
International Journal of Minerals, Metallurgy, and Materials     Hybrid Journal   (Followers: 11)
International Journal of Mining and Geo-Engineering     Open Access   (Followers: 4)
International Journal of Mining and Mineral Engineering     Hybrid Journal   (Followers: 8)
International Journal of Mining Engineering and Mineral Processing     Open Access   (Followers: 6)
International Journal of Mining Science and Technology     Open Access   (Followers: 4)
International Journal of Mining, Reclamation and Environment     Hybrid Journal   (Followers: 6)
International Journal of Rock Mechanics and Mining Sciences     Hybrid Journal   (Followers: 9)
Journal of Analytical and Numerical Methods in Mining Engineering     Open Access  
Journal of Applied Geophysics     Hybrid Journal   (Followers: 17)
Journal of Central South University     Hybrid Journal   (Followers: 1)
Journal of China Coal Society     Open Access  
Journal of China University of Mining and Technology     Full-text available via subscription   (Followers: 1)
Journal of Convention & Event Tourism     Hybrid Journal   (Followers: 6)
Journal of Geology and Mining Research     Open Access   (Followers: 10)
Journal of Human Resources in Hospitality & Tourism     Hybrid Journal   (Followers: 9)
Journal of Materials Research and Technology     Open Access   (Followers: 2)
Journal of Metamorphic Geology     Hybrid Journal   (Followers: 17)
Journal of Mining Institute     Open Access  
Journal of Mining Science     Hybrid Journal   (Followers: 5)
Journal of Quality Assurance in Hospitality & Tourism     Hybrid Journal   (Followers: 6)
Journal of Sustainable Mining     Open Access   (Followers: 3)
Journal of the Southern African Institute of Mining and Metallurgy     Open Access   (Followers: 6)
Lithology and Mineral Resources     Hybrid Journal   (Followers: 4)
Lithos     Hybrid Journal   (Followers: 12)
Mine Water and the Environment     Hybrid Journal   (Followers: 5)
Mineral Economics     Hybrid Journal   (Followers: 2)
Mineral Processing and Extractive Metallurgy : Transactions of the Institutions of Mining and Metallurgy     Hybrid Journal   (Followers: 14)
Mineral Processing and Extractive Metallurgy Review     Hybrid Journal   (Followers: 5)
Mineralium Deposita     Hybrid Journal   (Followers: 5)
Mineralogia     Open Access   (Followers: 2)
Mineralogical Magazine     Hybrid Journal   (Followers: 1)
Mineralogy and Petrology     Hybrid Journal   (Followers: 5)
Minerals     Open Access   (Followers: 2)
Minerals & Energy - Raw Materials Report     Hybrid Journal   (Followers: 1)
Minerals Engineering     Hybrid Journal   (Followers: 14)
Mining Engineering     Full-text available via subscription   (Followers: 7)
Mining Journal     Full-text available via subscription   (Followers: 4)
Mining Report     Hybrid Journal   (Followers: 3)
Mining Technology : Transactions of the Institutions of Mining and Metallurgy     Hybrid Journal   (Followers: 4)
Mining, Metallurgy & Exploration     Hybrid Journal  
Natural Resources & Engineering     Hybrid Journal  
Natural Resources Research     Hybrid Journal   (Followers: 4)
Neues Jahrbuch für Mineralogie - Abhandlungen     Full-text available via subscription   (Followers: 1)
Physics and Chemistry of Minerals     Hybrid Journal   (Followers: 4)
Podzemni Radovi     Open Access  
Rangeland Journal     Hybrid Journal   (Followers: 4)
Réalités industrielles     Full-text available via subscription  
Rem : Revista Escola de Minas     Open Access  
Resources Policy     Hybrid Journal   (Followers: 4)
Reviews in Mineralogy and Geochemistry     Hybrid Journal   (Followers: 5)
Revista del Instituto de Investigación de la Facultad de Ingeniería Geológica, Minera, Metalurgica y Geográfica     Open Access  
Rock Mechanics and Rock Engineering     Hybrid Journal   (Followers: 9)
Rocks & Minerals     Hybrid Journal   (Followers: 5)
Rudarsko-geološko-naftni Zbornik     Open Access  
Transactions of Nonferrous Metals Society of China     Hybrid Journal   (Followers: 9)
Similar Journals
Journal Cover
Natural Resources Research
Journal Prestige (SJR): 0.8
Citation Impact (citeScore): 3
Number of Followers: 4  
  Hybrid Journal Hybrid journal (It can contain Open Access articles)
ISSN (Print) 1573-8981 - ISSN (Online) 1520-7439
Published by Springer-Verlag Homepage  [2626 journals]
  • Correction to: Calibration of Genetic Algorithm Parameters for
           Mining-Related Optimization Problems
    • Abstract: The original version of this article unfortunately contained a mistake in figures. The source file for figures was submitted and published incorrectly; hence, the figures should be swapped as given below.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9400-9
  • Natural Resources Research: Acknowledgement of Reviewers in 2018
    • PubDate: 2019-04-01
      DOI: 10.1007/s11053-019-09453-0
  • Expanded S-Curve Model of a Relationship Between Crude Steel Consumption
           and Economic Development: Empiricism from Case Studies of Developed
    • Abstract: Abstract Different economic development stages are associated with distinctive patterns of steel consumption, and the forecast of future steel consumption has been an intriguing subject. This article takes a pragmatic approach to the examination of intrinsic relations between crude steel consumption and economic development using historical data of the past 100 years from 11 developed economies. The relations between crude steel consumption and GDP can be described by an expanded S-curve model: with the growth in GDP per capita and per capita steel consumption showing an expanded S-curve of “slow growth–rapid growth–zero growth, or even negative growth.” The patterns of crude steel consumption in different economic development stages are characterized by different transitional thresholds, which are referred to as the takeoff point, turning point, and zero-growth point of the per capita crude steel consumption. Using a mathematical model and the critical thresholds, the expanded S-curve can be divided into four transitional sections: slow growth, accelerated growth, decelerated growth, and zero/negative growth. The expanded S-curve model is expected to be a foundation for forecasting crude steel demand in different economies or in the same economy at different economic development stages.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9406-3
  • Real Option Identification Framework for Mine Operational Decision-Making
    • Abstract: Abstract Identification of opportunities for applying real options (RO) in mining operations is a major challenge to decision-makers. In order to make optimal decisions in uncertain times, managers require a full understanding of the relationships between risk, uncertainty and flexibility. RO analysis, which captures the value of any managerial flexibility that may exist in a project, provides a proactive management of uncertainty. Thus, it enhances optimal decision-making. However, it is important that a structured framework is created to identify project uncertainties and areas available to cultivate flexibility. In this paper, uncertainty identification framework in a mining operation is proposed, and areas for managerial flexibility and their application domains within the mining cycle are mapped as well. To avoid complex mathematical models, which hinder the adoption of RO analysis in mining operations, a relationship between risk measure (beta) and flexibility (flexibility index) is derived and applied. This implies that if a project beta is known, then the expected option values and volatility of future cash flows can be precisely estimated. Once the option value is calculated using the derived equation, a modified smooth pasting condition with the mean value theorem is subsequently applied to estimate the optimal value. This combination of beta, flexibility index and mean value theorem can be used as a decision criterion for screening various options within a mining project.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9393-4
  • Artificial Fracture Stimulation of Rock Subjected to Large Isotropic
           Confining Stresses in Saline Environments: Application in Deep-Sea Gas
           Hydrate Recovery
    • Abstract: Abstract The low permeability of gas hydrate deposits leads to poor extraction rates. Artificial fracture stimulation could significantly improve the recovery rate of an estimated 300 trillion m3 of this untapped future energy source, which form in seabed sedimentary deposits. Because conventional methods of rock fragmentation are inapplicable in such deposits due to sudden release of energy that may impose the risk of methane release to the atmosphere, alternative rock fragmentation technologies are necessary for artificial fracture stimulation of gas hydrate deposits. We checked the effectiveness of a new hydrophobic non-explosive demolition agent as a rock fracturing technique, which could potentially be used as a third-generation disruptive technology for mining (3G-DTM). Laboratory experiments performed by mimicking deep-sea environments suggest that the density of the gradually generated rock mass fractures increases with confining pressure and pore fluid salinity. Importantly, due to the fracturing nature of 3G-DTM, the fracture density can be significantly improved (by 116%) with increasing the confining pressure (from 70 kPa to 20 MPa). Increased salinity of the rock pore fluid also improved the fracture density by 38% at 20 MPa confining pressure when the salinity increased from 0% to 20%. Furthermore, the rock is subjected to a gradual fracturing process in the 3G-DTM fracturing (10–15 h in the laboratory experiments) allowing for a safer, more controlled fracture propagation, making 3G-DTM a substitute for conventional rock fragmentation in marine environments.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9409-0
  • Evaluation of Impact of Potential Extreme Rainfall Events on Mining in
    • Abstract: Abstract The impact that climate change may play in the future sustainability of mining projects has become increasingly important for the mining industry and its stakeholders. The most significant areas of concern are mine infrastructure, supply chains, health and safety conditions, environmental management, community relations and exploration. This is particularly relevant to mining in a country as climatically vulnerable as Peru. This study focuses on the identification of mining regions and main commodities in Peru that are potentially vulnerable to future extreme rainfall events associated with climate change. From a mine design and planning perspective, this study is a first step to illustrate the importance of considering the impacts of different climatic scenarios on mining in Peru. Based on HadGEM2-ES global climate model projections, mining regions across Peru were clustered into “super-regions” with differing potentials of extreme rainfall events during the next three decades. Five indices for precipitation extremes were used, and their variations between 1971–2000 and 2015–2034 were computed. Current and future metallic mining projects expected to take place across Peru in the next 30 years were retrieved from a mining database and subsequently exported into a geographical information systems software to represent their location and interpolate the variation for each precipitation extreme index. The results of this study point out at a decreasing trend in rainfall extremes intensity and frequency in regions of southern Peru. For copper projects located in these regions, a decrease in rainfall events could also imply an eventual decrease in total precipitation and consequently a deficit in water availability during the next three decades. Mining regions in central Peru, with significant number of zinc projects, are likely to experience a marked increase in overall annual precipitation, average daily precipitation intensity, consecutive days of precipitation and number of heavy precipitation days. At a lesser extent than in central Peru, gold projects in northern Peru are also likely to experience an overall increase in precipitation extremes. The approach used for this research could be extended to other mining regions around the world with extreme weather events.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9396-1
  • Groundwater Potential Mapping in a Rural River Basin by Union (OR) and
           Intersection (AND) of Four Multi-criteria Decision-Making Models
    • Abstract: Abstract Targeting groundwater in the river basin like Chandrabhaga with seasonal drought is a very urgent task especially for mitigating irrigation demand during the non-monsoon period. This paper delineated suitable groundwater potential zones based on the analytical hierarchy process (AHP), modified AHP, PCA-based weight and knowledge-based weight of multiple input parameters. For providing more certainty of the target zones in the derived models, union and intersection of all models were performed. A GIS-based multi-criteria approach using 13 relevant parameters has been adopted in this work. From the first four models, it is found that very suitable areas vary from 7.5 to 11% of the total basin area. The union and intersection models of the four individual models, respectively, delineated 13.91% and 3.69% suitable areas. Among the six models, the average yield of groundwater (5.96 L/s) is maximum in case of the intersection model, which is, therefore, more reliable than others. In case of the union model, the suitable area has 0.2 L/s less average yield than the intersection model. Therefore, for the harvesting more water, very good potential area delineated in the intersection model can be targeted. All these models will nevertheless help decision-makers to judge whether the existing groundwater harvesting structures are located properly or whether reorientation is needed.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9404-5
  • Geohydrodynamic Parameters and Their Implications on the Coastal
           Conservation: A Case Study of Abak Local Government Area (LGA), Akwa Ibom
           State, Southern Nigeria
    • Abstract: Abstract A total of 14 vertical electrical soundings using Schlumberger electrode configuration and the complementary laboratory analysis of aquifer samples were carried out in the Abak Local Government Area of Akwa Ibom State, the coastal region of Nigeria. The study focused on the estimation of geohydrodynamic parameters of the frequently exploited aquifers and the implication of hydrodynamic parameters on the lithostratigraphy and the anticipated exposure of the assessed geologic formation at the shorelines. These parameters were porosity (ϕ), tortuosity (τ), formation factor (F), aquifer water formation resistivity (Rw) and coefficient of permeability/hydraulic conductivity (K). Computation of the effective porosities from the aquifer cuttings was carried out using wet weight–dry weight technique and petrophysical techniques. The F values were computed using the aquifer formation bulk resistivity measured from field 1-D resistivity data analysis, whose interpretation was constrained by nearby borehole information. The formation pore water resistivities were estimated from the laboratory using electrical resistivity metre. The Win RESIST software program was used in interpreting the field data electronically. The results of interpretation gave the primary parameters of saturated and unsaturated units of the coastal regions used in this work. The area generally shows seemingly high porosity with high coefficient of permeability. The primary and secondary parameters have been contoured to model their distributions. Besides, some functional relations have been realized through regression analyses. The contour distribution of the geohydrodynamic parameters indicates the vulnerability of the water repositories to contaminations as well as the vulnerability of the shoreline to waterborne erosion. The seemingly high effective porosity in the compliant laboratory and calculated values indicate that the coastal region is neither lithified nor compacted/consolidated. This signals the possibility of the formation to be easily eroded, weathered or flooded where these units are exposed to water current. With these revelations, the shorelines could be properly managed and conserved by geotechnically reinforcing with hard and water-resistant concrete that can protect the vulnerable and erosion-prone porous sediments.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9391-6
  • Three-Dimensional Petrophysical Modelling and Volumetric Analysis to Model
           the Reservoir Potential of the Kupe Field, Taranaki Basin, New Zealand
    • Abstract: Abstract This study addresses the three-dimensional (3D) petrophysical modelling and volumetric analysis of the Farewell Reservoir in the Kupe Field in the southern Taranaki Basin, New Zealand. The qualitative petrophysical analysis of the Kupe South-1, Kupe South-3, Kupe South-4 and Kupe-6 wells helped to model the lithological and mineralogical composition of the reservoir, while the quantitative interpretation was used to identify the shale volume, porosity type and distribution, and water and hydrocarbon saturations. A 3D petrophysical model was developed on the basis of the petrophysical analysis, and it showed the spatial distribution and propagation of the petrophysical properties within the reservoir formation of the Kupe Field. Moreover, a volumetric analysis was conducted to estimate the gas reserves and probable reserve growth of the Kupe Field. The results indicated that the gross thickness of the studied reservoir formation ranges from 226.47 to 381 m, while the net reservoir thickness is between 12.95 and 140.2 m. The shale volume lies between 17.3% and 22.4%, while the total and effective porosities are between 17.9% and 27% and between 15.1% and 23%, respectively. The study also shows the presence of net pay zones with an aggregate ranging between 12.95 m and 82.45 m with variable hydrocarbon saturations. The hydrocarbon saturation is between 62.5% and 70.8%, while the water saturation is between 29.2% and 37.5%. The volumetric analysis indicates that the Kupe Gas Field contains 654.6 Bcf (18.5 × 109 m3) of gas, while the recoverable gas is estimated to be 389.87 Bcf (11.03 × 109 m3) at 50% probability. The volumetric estimation also confirms that the possible reserve growth of the Kupe Field is expected to be 60.8 Bcf (1.72 ×  109 m3) of gas in the case of 50% probability estimation. The 3D models not only validate the drilled wells used in the study but also indicate future prospective zones for drilling. The results inferred from the integrated study reveal that the Farewell Formation can be characterized as a good reservoir and has potential for future drilling and further development.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9394-3
  • Extraction of Mineralization-Related Anomalies from Gravity and Magnetic
           Potential Fields for Mineral Exploration Targeting: Tongling Cu(–Au)
           District, China
    • Abstract: Abstract Extraction of mineralization-related anomalies for mineral exploration targeting lies in the interpretation of geological anomalies that indicate favorable ore-forming criteria and major ore-controlling criteria from potential field data, based on the metallogenic model of a study area. The integrated geophysical methods of bi-dimensional empirical mode decomposition and power spectrum analysis were applied to Bouguer gravity and original airborne magnetic data to extract (or decompose) multisource geological anomalies and estimate approximate depths of those anomalies for further interpreting multisource mineralization-related anomalies in the Tongling Cu(–Au) district of China. The results (i.e., decomposed anomaly components for interpretation) can be briefly summarized as follows: (1) high-frequency components (i.e., gravity component BIMFG1 and magnetic component BIMFM1) depict the beaded-cyclic distribution of deposit-scale geological anomalies (~ 3 to 4 km deep), indicating shallow subsurface intrusions including dykes, stocks and apophysis; (2) intermediate-frequency components (i.e., gravity component BIMFG2, BIMFG3 and magnetic component BIMFM2) depict the interaction of magmatism and major NE-trending capping structures at shallow upper-crust (~ 6 to 8 km deep), both of which comprise the tectonic–magmatic–metallogenic system in the Tongling Cu(–Au) district; (3) intermediate-low-frequency components (i.e., gravity component BIMFG4 and magnetic component BIMFM3) further verify the coupling mechanism of major capping structures and magmatism at middle upper-crust (~ 9 km deep), indicating the trend and distribution of magma chambers expanding toward depths; (4) low-frequency components (i.e., gravity component ResG and magnetic component ResM), generally seen as the background information, depict district-scale structures and the distribution of magma chamber at depths. By combining above-mentioned geophysical features and the dataset of Cu(–Au) deposits in the study area, three target zones associated with district-scale structures can be identified. Target zone (I) is distributed along the Tongguanshan anticline, and two other target zones [i.e., zone (II) and zone (III)] are distributed along the Yongcunqiao–Shujiadian anticline. Similar geological and mineralization-related anomalies, represented by above-mentioned target zones, provide exploration targeting criteria for mineral exploration in the study area.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9397-0
  • Particle Swarm Optimization Algorithm for Neuro-Fuzzy Prospectivity
           Analysis Using Continuously Weighted Spatial Exploration Data
    • Abstract: Abstract Classification of spatial exploration data for exploration targeting using neuro-fuzzy models means that the many spatial values have to be simplified and assigned to a few classes. The simplification of complex geological information, which illustrates a high degree of variability, results in overly simplistic models based on the presumption of homogeneous earth. However, such an assumption is not valid. In this paper, we illustrate the superiority of using continuously weighted spatial evidence values compared to discretely weighted evidence data, and how continuously weighted spatial evidence values can increase the efficiency of neuro-fuzzy exploration targeting models. The results of this study demonstrate that neuro-fuzzy targeting model generated with continuously weighted spatial evidence values is superior to that of the neuro-fuzzy model generated with discretely weighted exploration evidence data.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9385-4
  • Groundwater Quality Assessment in a Hyper-arid Region of Rajasthan, India
    • Abstract: Abstract Groundwater is an important source of livelihood in regions where rainfall is scanty, surface water sources are absent, and all domestic and agricultural needs are fulfilled with groundwater. This study deals with groundwater quality assessment in a hyper-arid region using multivariate statistical analysis. A total of 43 samples were collected and analyzed using principal component analysis and hierarchical cluster analysis to model the relationship and interdependence among the various physicochemical variables contributing to groundwater quality in the study area. The results of the statistical techniques showed that the variables are in strong correlation with each other. Cluster analysis proved to be a good tool to ascertain the spatial similarity between the contributing variables. The methodology adopted in the present study has been found to be effective and can be utilized to establish strong water quality monitoring network in similar areas.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9405-4
  • Guidelines for Enhancing the Signature of Multi-element Mineralization
           Using Principal Component Analysis: Part 1—Monte Carlo Simulation
    • Abstract: Abstract Principal component analysis (PCA) is a widely used method in geochemical data processing. The method can be useful to integrate variables associated with mineralization into a single component. In this paper, a Monte Carlo simulation is designed and applied to explore the performance of PCA under conditions controlled by four factors: the number of geo-objects (lithologic units), differences between geo-objects, the relationship between the variables and the number of variables. The results imply that: (1) more significant differences between geo-objects will result in less stable PC results; (2) more geo-objects make the result more robust; (3) variables with similar relationships help to stabilize the result; (4) more input variables do not always lead to a better result. These conclusions provide useful guidelines for using PCA to yield a targeted component like mineralization.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9392-5
  • Calibration of Genetic Algorithm Parameters for Mining-Related
           Optimization Problems
    • Abstract: Abstract Genetic algorithms (GA) are widely used to solve engineering optimization problems. The quality and performance of the solution generated strongly depend on the selection of the GA parameter values (crossover and mutation rates and population size). We propose an approach based on full factorial and response surface methodology experimental designs to calibrate GA parameters such that the objective function is maximized/minimized and the relative importance of the parameters is quantified. The approach was tested by applying it to stope optimization of underground mines, where profit can vary ± 7% based solely on GA parameters. Results showed that: (1) a larger population size did not always increase solution time; (2) solution time was positively related to crossover and mutation rates; and (3) simultaneous analysis of solution time and profit illustrated the trade-off between acceptable computing time and profit desirability through GA parameter selection. This approach can be used to calibrate parameters of other metaheuristics.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9395-2
  • Groundwater Level Prediction/Forecasting and Assessment of Uncertainty
           Using SGS and ARIMA Models: A Case Study in the Bauru Aquifer System
    • Abstract: Abstract Best water management practices should involve the prediction of the availability of groundwater resources. To predict/forecast and consequently manage these water resources, two known methods are discussed: a time series method using the autoregressive integrated moving average (ARIMA) and a geostatistical method using sequential Gaussian simulation (SGS). This study was conducted in the Ecological Station of Santa Barbara (EEcSB), located at the Bauru Aquifer System domain, a substantial water source for the countryside of São Paulo State, Brazil. The relevance of this study lies in the fact that the 2013/2014 hydrological year was one of the driest periods ever recorded in São Paulo State, which was directly reflected in the groundwater table level behavior. A hydroclimatological network comprising 49 wells was set up to monitor the groundwater table depths at EEcSB to capture this response. The traditional time series has the advantage that it has been created to forecast and the disadvantage that an interpolation method must also be used to generate a spatially distributed map. On the other hand, a geostatistical approach can generate a map directly. To properly compare the results, both methods were used to predict/forecast the groundwater table levels at the next four measured times at the wells’ locations. The errors show that SGS achieves a slightly higher level of accuracy and considered anomalous events (e.g., severe drought). Meanwhile, the ARIMA models are considered better for monitoring the aquifer because they achieved the same accuracy level as SGS in the 2-month forecast and a higher precision at all periods and can be optimized automatically by using the Akaike information criterion.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9403-6
  • Evaluating Hydrological Responses to Urbanization in a Tropical River
           Basin: A Water Resources Management Perspective
    • Abstract: Abstract The present study investigates the hydrological response of increase in urbanization on water stressed Upper Bhima River basin which lies in a semi-arid climatic zone of Maharashtra state, India. Land Use Land Cover (LULC) changes due to urbanization, industrialization and anthropogenic activities have reconfigured the waterscape of the river basin, which has affected its regional hydrology. Influence of urbanization on key hydrological components is studied using Soil and Water Assessment Tool model. Firstly, Object Based Image Analysis approach was used to prepare time series LULC maps of the years 1992, 2002, 2009 and 2014. Overall classification accuracy of 92.48% and Kappa Coefficient (K) of 0.87 were achieved. Urbanization indicators, e.g. population urbanization level (Up) and spatial urbanization level (Us), were used to quantify the growth patterns in population and urban areas respectively. Mann–Kendall trend test was performed on the average annual rainfall data (year 1985–2014) to study rainfall trends across the region. Further, combination of statistical analyses including correlation analysis and multivariate analysis of variance were performed to comprehend the causative connection and interrelationships between Us and hydrological parameters. The results reveal that during 1992–2014, with increase in Us of 0.05, the average annual surface runoff increased to 10.4 mm [standard deviation (σ) = 4.40; sum of squares (SS) = 58.20], whereas percolation decreased to 14.5 mm [σ = 6.06; SS = 110.10], and base flow decreased to 11.7 mm (σ = 4.90; SS = 72.00). These hydrological parameters are highly influenced by increase in urbanization. This study is relevant for various stakeholders such as water sources planners and policy makers for assessment of water resources to ensure sustainable development in the urbanizing tropical river basins. Remedial measures are suggested to minimize the adverse effect of urbanization on hydrological processes.
      PubDate: 2019-04-01
      DOI: 10.1007/s11053-018-9390-7
  • Experimental Study of Adsorption Effects on Shale Permeability
    • Abstract: Abstract CH4 adsorption plays an important role in the permeability evolution of unconventional gas reservoirs. In this paper, an experimental method for simultaneous measurement of rock adsorption and permeability has been developed. For this experimental method, the CH4 adsorption amounts were obtained using a volumetric method. The permeability was measured by considering gas diffusion from the reference chamber to the core sample, under the pressure difference. A set of adsorption-permeability experiments were conducted on shale samples from lower Silurian Longmaxi Formation in the Sichuan Basin. The experimental results show that both the adsorption and swelling behavior of shale can be well described by the Langmuir equation. The effects of adsorption on permeability are influenced by two factors: (1) adsorption-induced storage, which causes an incremental in apparent porosity, leading to a significant error in permeability measurement if true porosity is used; and (2) adsorption-induced swelling, which potentially closes the existing natural fractures and reduces the intrinsic permeability. The adsorption storage effects are more significant at low pressure and are influenced by the experimental configurations (ratio of chamber volume to pore volume). With the increase in adsorption-induced swelling strain, the permeability declines by a cubic function during the adsorption process. Since swelling strain is linearly proportional to the amount of CH4 adsorbed, the behaviors of permeability and the amount of adsorbing gas follow similar trends.
      PubDate: 2019-03-22
      DOI: 10.1007/s11053-019-09476-7
  • Forecasting Copper Prices Using Hybrid Adaptive Neuro-Fuzzy Inference
           System and Genetic Algorithms
    • Abstract: Abstract An accurate forecasting model for the price volatility of minerals plays a vital role in future investments and decisions for mining projects and related companies. In this paper, a hybrid model is proposed to provide an accurate model for forecasting the volatility of copper prices. The proposed model combines the adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA). Genetic algorithms are used for estimating the ANFIS model parameters. The results of the proposed model are compared to other models, including ANFIS, support vector machine (SVM), generalized autoregressive conditional heteroscedasticity (GARCH), and autoregressive integrated moving average (ARIMA) models. The empirical results confirm the superiority of the hybrid GA–ANFIS model over other models. The proposed model also improves the forecasting accuracy obtained from the ANFIS, SVM, GARCH, and ARIMA models by a 62.92%, 36.38%, 91.72%, and 42.19% decrease in mean square error, respectively.
      PubDate: 2019-03-11
      DOI: 10.1007/s11053-019-09473-w
  • Categorization of Mineral Resources Based on Different Geostatistical
           Simulation Algorithms: A Case Study from an Iron Ore Deposit
    • Abstract: Abstract Mineral resource classification plays an important role in the downstream activities of a mining project. Spatial modeling of the grade variability in a deposit directly impacts the evaluation of recovery functions, such as the tonnage, metal quantity and mean grade above cutoffs. The use of geostatistical simulations for this purpose is becoming popular among practitioners because they produce statistical parameters of the sample dataset in cases of global distribution (e.g., histograms) and local distribution (e.g., variograms). Conditional simulations can also be assessed to quantify the uncertainty within the blocks. In this sense, mineral resource classification based on obtained realizations leads to the likely computation of reliable recovery functions, showing the worst and best scenarios. However, applying the proper geostatistical (co)-simulation algorithms is critical in the case of modeling variables with strong cross-correlation structures. In this context, enhanced approaches such as projection pursuit multivariate transforms (PPMTs) are highly desirable. In this paper, the mineral resources in an iron ore deposit are computed and categorized employing the PPMT method, and then, the outputs are compared with conventional (co)-simulation methods for the reproduction of statistical parameters and for the calculation of tonnage at different levels of cutoff grades. The results show that the PPMT outperforms conventional (co)-simulation approaches not only in terms of local and global cross-correlation reproductions between two underlying grades (Fe and Al2O3) in this iron deposit but also in terms of mineral resource categories according to the Joint Ore Reserves Committee standard.
      PubDate: 2019-03-11
      DOI: 10.1007/s11053-019-09474-9
  • Non-stationary Geostatistical Modeling: A Case Study Comparing LVA
           Estimation Frameworks
    • Authors: Ryan Martin; David Machuca-Mory; Oy Leuangthong; Jeff B. Boisvert
      Abstract: Abstract Incorporating locally varying anisotropy (LVA) in geostatistical modeling improves estimates for structurally complex domains where a single set of anisotropic parameters modeled globally do not account for all geological features. In this work, the properties of two LVA-geostatistical modeling frameworks are explored through application to a complexly folded gold deposit in Ghana. The inference of necessary parameters is a significant requirement of geostatistical modeling with LVA; this work focuses on the case where LVA orientations, derived from expert geological interpretation, are used to improve the grade estimates. The different methodologies for inferring the required parameters in this context are explored. The results of considering different estimation frameworks and alternate methods of parameterization are evaluated with a cross-validation study, as well as visual inspection of grade continuity along select cross sections. Results show that stationary methodologies are outperformed by all LVA techniques, even when the LVA framework has minimal guidance on parameterization. Findings also show that additional improvements are gained by considering parameter inference where the LVA orientations and point data are used to infer the local range of anisotropy. Considering LVA for geostatistical modeling of the deposit considered in this work results in better reproduction of curvilinear geological features.
      PubDate: 2018-05-29
      DOI: 10.1007/s11053-018-9384-5
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