A new approach for the geological risk evaluation of coal resources through a geostatistical simulation

Estimations of mineral resources and ore reserves have been recently widely used by mining engineers and investors. The classification framework based on the prepared code by the Joint Ore Reserves Committee of The Australasian Institute of Mining and Metallurgy, Australian Institute of Geoscientists and Minerals Council of Australia (JORC code), which is one of the international standards for mineral resource and ore reserve reporting, provides a template system that conforms to international society requirements. Recent research has shown that an existing fault risk can affect the mineral resource and ore reserve estimation. According to this research, the faulted area that is involved in the effect on the estimated region is so extensive that it is not distinguishable. In this research, a new method called FGT (F for fault, G for grade and T for thickness) is introduced and presented for the estimation of mineral resources. The proposed method can provide an error map of a particular aspect of the combination of coal accumulation (G), fault risk (F) and thickness (T), and its output would categorise the mineral resources. This method was implemented in the Parvadeh Ш coal deposit, which is located in the eastern portion of Central Iran. The deposit contains five seams named B1, B2, C1, C2 and D; of these, C1 was selected as the most important seam in the exploratory grid analysis. Thus, C1 alone can reflect the properties of the Parvadeh Ш deposit. In this study, we compared the conventional method and the FGT method. This comparison indicated that the areas that should be rejected from the region in the FGT method are less and more distinguishable than those determined with the conventional method. Therefore, the inferred resources can be completely differentiated from the indicated and measured resources with a high resolution. The conventional method cannot distinguish between these three categories at this level of resolution. Therefore, the FGT approach has high precision in classifying the coal resource compared to the conventional method.     

A neural network approach to geostatistical simulation

Neural networks offer a non-algorithmic approach to geostatistical simulation with the possibility of automatic recognition of correlation structure. The paper gives a brief overview of neural networks and describes a feedforward, back-propagation network for geostatistical simulation. The operation of the network is illustrated with two simple one-dimensional examples which can be followed through with hand calculations to give an insight into the operation of the network. The convergence of the network is described in terms of the variogram calculated from the values at each of the output nodes at each iteration.     

A geostatistical approach to predicting the washability characteristics of coal in situ

The washability characteristics of coal are dependent on two basic relations: the ash assay vs. relative density curve, and the distribution by weight of the relative densities of coal particles. Armstrong and Whitmore (1980) demonstrated that the ash content and the yield of coal floating at a particular density can be predicted with reasonable accuracy using a simple inverse proportionality relation for the ash assay vs. density curve and a lognormal model for the distribution. In this paper, geostatistical techniques are used in conjunction with the two models to predict the washability characteristics of coal in situ.     

大同市矿山地质环境风险评价

文章从矿业开发影响和地质环境脆弱性相互作用的角度出发,提出了矿山地质环境风险评价的定义及方法。将大同市作为评价对象,建立了矿业开发影响力和地质环境脆弱性评价指标体系,利用层次分析法进行指标权重分析,进而通过模糊综合评判数学模型进行计算和对比;最终将大同市划分为矿山地质环境高风险区、中风险区和低风险区。并根据评价分区结果,提出了风险防控建议。     

A new approach to the determination of methane content of coal seams

Summary An approach to the determination of methane content of coal seams is proposed. The method utilizes the transformed Airey's empirical equation on desorption of methane from coals. The methane content values estimated by this method correspond well with actual values from laboratory experiments. In the case of Indian coals, the applicability of the relationship for the calculation of the gas lost from coal lumps during long periods of time loss appears to be limited due to poor agreement with the experimental values.     

A proposed new approach for groundwater resources assessment in India

Assessment of groundwater resources in India is guided by National Water Policy (1987, 2002) which states that groundwater resources can be exploited only up to its recharge limit. The methodology for groundwater resources assessment in India is broadly based on Ground Water Resources Estimation Methodology, 1997 and it involves assessment of annual replenishable groundwater resources (recharge), annual groundwater draft (utilization) and the percentage of utilization with respect to recharge (stage of development). The assessment units (blocks/watersheds) are categorized based on stage of groundwater development (utilization) and the long term water level trend. The present methodology though useful in identification and prioritization of areas for groundwater management, falls short of addressing several critical issues like spatial and temporal variation of groundwater availability within the aquifer, accessibility of groundwater resources and quality of groundwater. This paper introduces a new categorisation scheme considering the above issues. The proposed scheme takes into account four criteria, viz. (i) stage of exploitation, (ii) extractability factor, (iii) temporal availability factor and (iv) quality factor. In comparison to the existing method used for categorisation, the proposed approach is more inclusive. The methodology is also equally suitable for both alluvial and hard rock terrain since it takes into consideration the variable characteristics of different types of aquifers and convergence of quantitative and qualitative assessment. The categorisation proposed here involves GIS based integration of different parameters/ themes. This allows better representation of spatial variability. The proposed methodology is demonstrated in this paper taking a case study from a hard rock terrain in central India.     

Risk analysis for remediation of contaminated sites: the geostatistical approach

The assessment of the risks associated with contamination by elevated levels of pollutants is a major issue in most parts of the world. The risk arises from the presence of a pollutant and from the uncertainty associated with estimating its concentration, extent and trajectory. The uncertainty in the assessment comes from the difficulty of measuring the pollutant concentration values accurately at any given location and the impossibility of measuring it at all locations within a study zone. Estimations tend to give smoothed versions of reality, with the smoothing effect being inversely proportional to the amount of data. If risk is a measure of the probability of pollutant concentrations exceeding specified thresholds, then the variability is the key feature in risk assessment and risk analysis. For this reason, geostatistical simulations provide an appropriate way of quantifying risk by simulating possible “realities” and determining how many of these realities exceed the contamination thresholds, and, finally, provides a means of visualizing risk and the geological causes of risk. This study concerns multivariate simulations of organic and inorganic pollutants measured in terrain samples to assess the uncertainty for the risk analysis of a contaminated site, an industrial site in northern Italy that has to be remediated. The main geostatistical tools are used to model the local uncertainty of pollutant concentrations, which prevail at any unsampled site, in particular by means of stochastic simulation. These models of uncertainty have been used in the decision-making processes to identify the areas targeted for remediation.     

Vulnerability assessment in a volcanic risk evaluation in Central Mexico through a multi-criteria-GIS approach

The Valley of Toluca is a major industrial and agricultural area in Central Mexico, especially the City of Toluca, the capital of The State of Mexico. The Nevado de Toluca volcano is located to the southwest of The Toluca Basin. Results obtained from the vulnerability assessment phase of the study area (5,040 km² and 42 municipalities) are presented here as a part of a comprehensive volcanic risk assessment of The Toluca Basin. Information has been gathered and processed at a municipal level including thematic maps at 1:250,000 scale. A database has been built, classified and analyzed within a GIS environment; additionally, a Multi-Criteria Evaluation (MCE) approach was applied as an aid for the decision-making process. Cartographic results were five vulnerability maps: (1) Total Population, (2) Land Use/Cover, (3) Infrastructure, (4) Economic Units and (5) Total Vulnerability. Our main results suggest that the Toluca and Tianguistenco urban and industrial areas, to the north and northeast of The Valley of Toluca, are the most vulnerable areas, for their high concentration of population, infrastructure, economic activity, and exposure to volcanic events.     

A quantitative approach for the evaluation of rockfall risk on buildings

Natural Hazards - A quantitative rockfall risk analysis at local scale is a complex and difficult task because it should consider both the randomness in the natural phenomenon and the variability...     

Comparison of three geostatistical methods for hydrofacies simulation: a test on alluvial sediments

The hydrodispersive properties of porous sediments are strongly influenced by the heterogeneity at fine scales, which can be modeled by geostatistical simulations. In order to improve the assessment of the properties of three different geostatistical simulation methods (Sequential indicator simulation, SISIM; Transition probability geostatistical simulation, T-PROGS; Multiple point simulation, MPS) a comparison test at different scales was performed for a well-exposed aquifer analogue. In the analysed volume (approximately 30,000?m³) four operative hydrofacies have been recognised: very fine sand and silt, sand, gravelly sand and open framework gravel. Several equiprobable realizations were computed with SISIM, MPS and T-PROGS for a test volume of approximately 400?m³ and for the entire volume, and the different outcomes were compared with visual inspection and connectivity analysis of the very or poorly permeable structures. The comparison of the different simulations shows that the geological model is best reproduced when the simulations are realised separately for each highest rank depositional element and subsequently merged. Moreover, the three methods yield different images of the volume; in particular MPS is efficient in mapping the geometries of the most represented hydrofacies, whereas SISIM and T-PROGS can account for the distribution of the less represented facies.     

Potentially harmful metals,and health risk evaluation in groundwater of Mardan,Pakistan: Application of geostatistical approach and geographic information system

This study investigates the values of pH, total dissolved solids (TDS), elevation, oxidative reduction potential (ORP), temperature, and depth, while the concentrations of Br, and potentially harmful metals (PHMs) such as Cr, Ni, Cd, Mn, Cu, Pb, Co, Zn, and Fe in the groundwater samples. Moreover, geographic information system (GIS), XLSTAT, and IBM SPSS Statistics 20 software were used for spatial distribution modeling, principal component analysis (PCA), cluster analysis (CA), and Quantile-Quantile (Q-Q) plotting to determine groundwater pollution sources, similarity index, and normal distribution reference line for the selected parameters. The mean values of pH, TDS, elevation, ORP, temperature, depth, and Br were 7.2, 322 mg/L, 364 m, 188 mV, 29.6 °C, 70 m, 0.20 mg/L, and PHMs like Cr, Ni, Cd, Mn, Cu, Pb, Co, Zn, and Fe were 0.38, 0.26, 0.08, 0.27, 0.36, 0.22, 0.04, 0.43 and 0.86 mg/L, respectively. PHMs including Cr (89%), Cd (43%), Mn (23%), Pb (79%), Co (20%), and Fe (91%) exceeded the guideline values set by the world health organization (WHO). The significant R² values of PCA for selected parameters were also determined (0.62, 0.67, 0.78, 0.73, 0.60, 0.87, ?0.50, 0.69, 0.70, 0.74, ?0.50, 0.70, 0.67, 0.79, 0.59, and ?0.55, respectively). PCA revealed three geochemical processes such as geogenic, anthropogenic, and reducing conditions. The mineral phases of Cd(OH)_2, Fe(OH)_3, FeOOH, Mn₃O_4, Fe₂O_3, MnOOH, Pb(OH)_2, Mn(OH)_2, MnO_2, and Zn(OH)₂ (?3.7, 3.75, 9.7, ?5.8, 8.9, ?3.6, 2.2, ?4.6, ?7.7, ?0.9, and 0.003, respectively) showed super-saturation and under-saturation conditions. Health risk assessment (HRA) values for PHMs were also calculated and the values of hazard quotient (HQ), and hazard indices (HI) for the entire study area were increased in the following order: Cd>Ni>Cu>Pb>Mn>Zn>Cr. Relatively higher HQ and HI values of Ni, Cd, Pb, and Cu were greater than one showing unsuitability of groundwater for domestic, agriculture, and drinking purposes. The long-term ingestion of groundwater could also cause severe health concerns such as kidney, brain dysfunction, liver, stomach problems, and even cancer.     

城市地下空间资源地质环境适宜性评价方法对比分析

为了选择最优的地下空间资源地质适宜性评价模型,对地下空间进行资源科学、合理的评价,给地下空间开发提供合理的规划支持,笔者等选取了3种不同的模型,对其进行对比分析,总结其优缺点及适用条件,并以深圳市南山区为例进行地下空间资源地质适宜性评价,利用 ArcGIS生成了南山区地下空间资源地质适宜性评价分区图。评价结果表明,最不利等级判别法评价模型较为适用于南山区的地质适宜性评价,突出了敏感因子对于南山区地下空间开发的制约性作用。笔者等的研究对未来地下空间资源地质适宜性评价的模型选择具有一定借鉴意义,为深圳市南山区的地下空间规划提供一定的参考。     

城市地下空间资源地质环境适宜性评价方法对比分析

为了选择最优的地下空间资源地质适宜性评价模型,对地下空间进行资源科学、合理的评价,给地下空间开发提供合理的规划支持,笔者等选取了3种不同的模型,对其进行对比分析,总结其优缺点及适用条件,并以深圳市南山区为例进行地下空间资源地质适宜性评价,利用 ArcGIS生成了南山区地下空间资源地质适宜性评价分区图。评价结果表明,最不利等级判别法评价模型较为适用于南山区的地质适宜性评价,突出了敏感因子对于南山区地下空间开发的制约性作用。笔者等的研究对未来地下空间资源地质适宜性评价的模型选择具有一定借鉴意义,为深圳市南山区的地下空间规划提供一定的参考。     

A probabilistic approach to the assessment of uranium resources

This paper presents a probabilistic approach to the estimation of uranium resources that allows for the integration of geologic observations with the experience and judgment of geologists. The paper focuses on estimating roll-front type deposits. The approach is based on a quantitative material balance model of ore formation that describes the quantity of uranium resources in terms of several key parameters constituting the quantity of uranium entering a host, and the fraction of the entering uranium that has been precipitated. The parameters cannot necessarily be measured in the field, but they can be inferred from available information and interpretation of field observations. The key to this approach is eliciting these inferences from geologists, representing the uncertainties inherent in drawing the geologic inferences as probability distributions, and combining the distributions to arrive at a probability distribution for uranium resources in a region. This paper presents the model, procedures for eliciting subjective probabilities and updating the distribution over resources within a Bayesian framework, and a demonstration of the procedure by obtaining estimates for three roll-front type deposits in Wyoming.     

A new rating system approach for risk analysis of rock slopes

In this paper, an approach is presented to analyze the stability risk of rock slopes based on a new rating system. Three factors are used to estimate the risk level of rock slopes: (1) failure probability, (2) element at risk rating, and (3) vulnerability rating. Element at risk and vulnerability ratings are both given a range from 0 to 10, and the probability of failure is varied between 0 and 1, so the risk rating ranges between 0 and 100. This risk rating can be used to determine both the quantitative and qualitative risk levels of slopes at the same time. The method is tested on the western sector of the slopes facing Songun copper plant phase III, Iran, to clarify its procedures and assess its validity. Deterministic kinematic analyses showed that the slope has a potential for circular failure. Risk assessments revealed that the risk levels of the slope in both static and pseudo-static conditions are “very low” and “high,” respectively.