Design of backfilled thin-seam coal pillars using earth pressure theory

In underground coal mining any increase in coal recovery rate is dependent on a decrease in pillar size. Backfilling is one way of reducing the required size of pillars and hence the volume of coal left underground. Therefore any comparisons made between a self-supported mine layout and backfill supported mine layout are based directly on pillar design. The most effective way to examine the effect of backfill on pillar support, and subsequently the rate of recovery, would be to incorporate the mechanisms of backfill support directly into the current design procedure for coal pillars. This paper presents a review of the mechanics of backfill support, a method of estimating the magnitude of that support based on earth pressure theory, and an example that incorporates backfill support into current coal pillar design.     

Effective resource estimates for primary diamond deposits from the EKATI Diamond Mine™, Canada

Primary economic diamond deposit modelling has rarely been documented in the public domain. This paper presents information collected from significantly diamondiferous kimberlite pipes located near Lac de Gras in the Arctic region of Canada's Northwest Territories. The resource estimation process is widely accepted as a cyclical iteration of data collection and evaluation processes. A resource database is typically assembled from a large inventory of exploration data. These data must be methodically quality checked before accepting the information for interpretive analysis. The foundation of a mineral resource model is based on clear understanding of the geology model along with subsidiary grade, volume, and density models. Defining these models is an iterative process of statistical analyses and interpretation. As a deposit progresses along a path towards development, reducing risk to acceptable levels is critical for identifying and realizing its maximum value.     

Mapping the Bonanza: Geographies of Mining Investment in an Era of Neoliberal Reform*

Geographic analyses of how national policies of economic liberalization influence global patterns of economic activity often draw their conclusions from studies of the paradigmatic sectors of manufacturing and, to a lesser extent, services. There is, by contrast, relatively little work examining how neoliberal policy reforms in the developing world may be driving changes in the geography of primary sector (i.e., extractive) activities at the global scale. This article presents and analyzes new data on direct investment in the international mining industry. It reports methods and results from a research project to systematically map and evaluate changes in the commodity mix and geographical spread of mining‐related investment in the world economy since 1990. It confirms and quantifies what was hitherto anecdotal evidence of a geographic shift in investment during the 1990s away from mature targets toward a small number of “rising stars” in the developing world, following the adoption in many countries of neoliberal economic policies from the mid‐1980s onward. However, the findings challenge conventional interpretations of this shift as an investment “bonanza” in the periphery and highlight how recent investment trends are highly specific in geographical scope, concentrated within a few commodities, and how the allocation of investment between established and emerging targets is variable over both time and space.     

Primary component analysis method and reduction of seismicity parameters

Introduction Data mining (SHAO and YU, 2003) is a new kind of technique developed with database and artificial intelligence in recent years, which processes the data in the database to abstract the im- plied and pre-unknown, but potentially useful information and knowledge from large amounts of incomplete, noisy, blurring and stochastic data. For data mining, data purging is an important link beforehand that includes eliminating noise, making up lost domain, and deleting ineffective data, as…     

东北地区矿业开发态势与矿山环境地质问题综合研究

在论述东北地区矿业开发态势的同时,阐述了区内能源矿产、金属矿产及非金属矿产开采引发的主要环境地质问题,针对区内复杂的矿山环境地质问题现状,提出了开展东北地区矿山环境地质综合研究问题的工作思路.     

Water pollution in gold mining industry: a case study in Roşia Montană district, Romania

The preliminary study of streams and rivers from the Roşia Montană area revealed that the concntration of heavy metals— Cd, Mn, Cu, Pb, and Zn—are above accepted limits. The gold extraction method is based on flotation. The most important pollution sources are mine tailings. The determinations were performed for samples collected in: April 2004, July 2004, September 2004, November 2004, February 2005 and May 2005. The highest concentrations were found for cadmium in September 2004: 0.17 mg/L; for copper in September 2004: 1.38 mg/L; for manganese in July 2004: 239.4 mg/L; for lead in May 2005: 0.54 mg/L; and for zinc in September 2004: 35.37 mg/L;. This study involved three small rivers (streams) that flow into the Mureş River and finally into the Danube River, having a great impact on human health and environmental stability in the area. In May 2005, a sample of drinking water from the mining district was also collected.     

Localization of mining-induced horizontal fractures along rock layer interfaces in overburden: field measurements and prediction

The locations of mining-induced horizontal fractures along rock interfaces in the overburden of Donetsk Coal Basin were identified using an original experimental device. The device traps methane from horizontal fracture zone (100–fold coal seam thickness) over an active longwall mining excavation. Presence or absence of horizontal fractures along rock layer interfaces is correlated with physical characteristics of the overburden, such as thickness, uniaxial compressive strength of overburden rock layers, location of rock layer interfaces and thickness of extracted coal seams. As a result, a combined criterion based on these physical characteristics is proposed to predict the presence of overburden horizontal fracturing in coal mine operations.     

Soil property variation mapping through data mining of soil category maps

Spatial information on soil properties is an important input to hydrological models. In current hydrological modelling practices, soil property information is often derived from soil category maps by the linking method in which a representative soil property value is linked to each soil polygon. Limited by the area‐class nature of soil category maps, the derived soil property variation is discontinuous and less detailed than high resolution digital terrain or remote sensing data. This research proposed dmSoil, a data‐mining‐based approach to derive continuous and spatially detailed soil property information from soil category maps. First, the soil–environment relationships are extracted through data mining of a soil map. The similarity of the soil at each location to different soil types in the soil map is then estimated using the mined relationships. Prediction of soil property values at each location is made by combining the similarities of the soil at that location to different soil types and the representative soil property values of these soil types. The new approach was applied in the Raffelson Watershed and Pleasant Valley in the Driftless Area of Wisconsin, United States to map soil A horizon texture (in both areas) and depth to soil C horizon (in Pleasant Valley). The property maps from the dmSoil approach capture the spatial gradation and details of soil properties better than those from the linking method. The new approach also shows consistent accuracy improvement at validation points. In addition to the improved performances, the inputs for the dmSoil approach are easy to prepare, and the approach itself is simple to deploy. It provides an effective way to derive better soil property information from soil category maps for hydrological modelling. Copyright © 2014 John Wiley & Sons, Ltd.     

Water mining from the deep critical zone by apple trees growing on loess

There have been significant recent advances in understanding the ecohydrology of deep soil. However, the links between root development and water usage in the deep critical zone remains poorly understood. To clarify the interaction between water use and root development in deep soil, we investigated soil water and root profiles beyond maximum rooting depth in five apple orchards planted on farmland with stand ages of 8, 11, 15, 18, and 22 years in a subhumid region on the Chinese Loess Plateau. Apple trees rooted progressively deeper for water with increasing stand age and reached 23.2 ± 0.8 m for the 22‐year‐old trees. Soil water deficit in deep soil increased with tree age and was 1,530 ± 43 mm for a stand age of 22 years. Measured root deepening rate was far great than the reported pore water velocity, which demonstrated that trees are mining resident old water. The deficits are not replenished during the life‐span of the orchard, showing a one‐way mining of the critical zone water. The one‐way root water mining may have changed the fine root profile from an exponential pattern in the 8‐year‐old orchard to a relative uniform distribution in older orchards. Our findings enhance our understanding of water‐root interaction in deep soil and reveal the unintended consequences of critical zone dewatering during the lifespan of apple trees.     

Erodibility of low‐compaction steep‐sloped reclaimed surface mine lands in the southern Appalachian region,USA

The use of loose spoils on steep slopes for surface coal mining reclamation sites has been promoted by the US Department of Interior, Office of Surface Mining for the establishment of native forest, as prescribed by the Forest Reclamation Approach (FRA). Although low‐compaction spoils improve tree survival and growth, erodibility on steep slopes was suspected to increase. This study quantified a combined K_C factor (combining the effects of the soil erodibility K factor and cover management C) for low compaction, steep‐sloped (>20°) reclaimed mine lands in the Appalachian region, USA. The combined K_C factor was used because standard Unit Plot conditions required to separate these factors, per Revised Universal Soil Loss Equation (RUSLE) experimental protocols, were not followed explicitly. Three active coal mining sites in the Appalachian region of East Tennessee, each containing four replicate field plots, were monitored for rainfall and sediment yields during a 14‐month period beginning June 2009. Average cumulative erosivity for the study sites during the monitoring period was measured as 5248.9 MJ·mm·ha^?1·h^?1. The K_C ranged between 0.001 and 0.05 t·ha·h·ha^?1·MJ^?1·mm^?1, with the highest values occurring immediately following reclamation site construction as rills developed (June – August 2009). The K_C for two study sites with about an 18–20 mm spoil D₈₄ were above 0.01 t·ha·h·ha^?1·MJ^?1·mm^?1 during rill development, and below 0.003 t·ha·h·ha^?1·MJ^?1·mm^?1 after August 2009 for the post‐rill development period. The K_C values for one site with a 40 mm spoil D₈₄ were never above 0.008 t·ha·h·ha^?1·MJ^?1·mm^?1 and also on average were lower, being more similar to the other two sites after the rill development period. Based on an initial K_C factor (K_e) measured during the first few storm events, the average C factor (C_e) was estimated as 0.58 for the rill development period and 0.13 for the post‐rill development period. It appears that larger size fractions of spoils influence K_C and C_e factors on low‐compaction steep slopes reclamation sites. Copyright © 2013 John Wiley & Sons, Ltd.