共查询到20条相似文献，搜索用时 312 毫秒
1.
C.
zgen Karacan 《International Journal of Coal Geology》2007,72(3-4):221-239
In longwall development mining of coal seams, planning, optimizing and providing adequate ventilation are very important steps to eliminate the accumulation of explosive methane–air mixtures in the working environment. Mine operators usually try to supply maximum ventilation air based on the capacity of the system and the predicted need underground. This approach is neither economical nor safer as ventilation capacity may decrease in time depending on various mining and coalbed parameters. Thus, it is important to develop better engineered approaches to optimize mine ventilation effectiveness and, therefore, to ensure a safer work environment.This study presents an approach using coalbed methane reservoir modeling and an artificial neural network (ANN) design for prediction and optimization of methane inflows and ventilation air requirements to maintain methane concentrations below statutory limits. A coalbed reservoir model of a three-entry development section, which is typical of Pittsburgh Coalbed mines in the Southwestern Pennsylvania section of Northern Appalachian Basin, was developed taking into account the presence and absence of shielding boreholes around the entries against methane inflow. In the model, grids were dynamically controlled to simulate the advance of mining for parametric simulations.Development and application of artificial neural networks as an optimization tool for ventilation requirements are introduced. Model predictions are used to develop, train, and test artificial neural networks to optimize ventilation requirements. The sensitivity and applications of proposed networks for predicting simulator data are presented and discussed. Results show that reservoir simulations and integrated ANN models can be practical and powerful tools for predicting methane emissions and optimization of ventilation air requirements. 相似文献
2.
C.
zgen Karacan 《International Journal of Coal Geology》2009,79(4):131-144
Gob gas ventholes (GGV) are used to control methane inflows into a longwall operation by capturing it within the overlying fractured strata before it enters the work environment. Thus, it is important to understand the effects of various factors, such as drilling parameters, location of borehole, applied vacuum by exhausters and mining/panel parameters in order to be able to evaluate the performance of GGVs and to predict their effectiveness in controlling methane emissions. However, a practical model for this purpose currently does not exist.In this paper, we analyzed the total gas flow rates and methane percentages from 10 GGVs located on three adjacent panels operated in Pittsburgh coalbed in Southwestern Pennsylvania section of Northern Appalachian basin. The ventholes were drilled from different surface elevations and were located at varying distances from the start-up ends of the panels and from the tailgate entries. Exhauster pressures, casing diameters, location of longwall face and mining rates and production data were also recorded. These data were incorporated into a multilayer-perceptron (MLP) type artificial neural network (ANN) to model venthole production. The results showed that the two-hidden layer model predicted total production and the methane content of the GGVs with more than 90% accuracy. The ANN model was further used to conduct sensitivity analyses about the mean of the input variables to determine the effect of each input variable on the predicted production performance of GGVs. 相似文献
3.
目前,在波兰41对主要生产矿井中,有23对高瓦斯矿井进行了瓦斯抽放。2004年瓦斯平均抽放率为30%,平均利用率为39%。根据瓦斯地质条件、瓦斯涌出特点和采区通风方式,着重介绍了波兰煤矿强化煤层、围岩和采空区瓦斯抽放,提高矿井瓦斯抽放效率的工艺技术特点。在工作面的瓦斯排放中,注重开采、通风与瓦斯抽放一体化,通过优化抽放钻孔布置,取得钻孔瓦斯抽放的最佳效果,是波兰煤矿瓦斯治理的一项成功经验,成为煤矿持续安全高效生产的重要技术保障。 相似文献
4.
Gas emission prediction and recovery in underground coal mines 总被引：2，自引：0，他引：2
Strata gas can be released and captured from non-active and active gas resources either from virgin or relaxed strata, both prior to and when mining activities take place. The high and irregular gas emissions associated with high production longwall mining have provided a need to optimise the methods used to predict these gas levels and the ventilation requirements for gas dilution. A forecast of gas emissions during development drivage and longwall mining indicated possible gas and ventilation problems requiring the introduction of various gas drainage techniques and in maintaining the necessary air quantities in ventilation systems to satisfy the statutory gas limitations for various coal production rates. Although there are sound principles used in world-recognised methods of gas emission prediction, a new approach developed from long-term practical experience in underground gassy coal mine practices and gas-rock mechanics studies appear most suitable for local conditions and mining systems in use. The Lunagas ‘Floorgas' and ‘Roofgas' geomechanical and gas emission models offer an effective solution to these problems. Both programs are the most advanced engineering, numerical tools available to calculate gas source contributions to total gassiness and improve the accuracy and quality of gas control, gas capture technologies and ventilation system design. 相似文献
5.
甲烷是最主要的非二氧化碳温室气体,受到越来越多的重视。煤炭甲烷是我国最主要的甲烷排放源类型,我国也是世界煤炭甲烷排放量最大的国家,煤炭甲烷的有效排放管控与高效开发利用兼具温室气体减排、能源气体开发利用和灾害气体防治三重意义。基于系统调研和研究工作积累,概述了煤炭甲烷排放管控背景,总结了全球与代表性国家煤炭甲烷排放及其管控现状,阐释了我国煤炭甲烷开发利用与排放管控历程及发展趋势,讨论和前瞻了我国煤炭甲烷减排路径与减排潜力。已有研究工作表明:我国煤炭甲烷排放主要来自煤炭地下开采风排瓦斯,且较长时期内仍是我国煤炭甲烷的主要来源;随着我国关闭矿井增多,由此产生的关闭矿井甲烷排放量呈增长趋势,是我国煤炭甲烷不容忽视的来源。随着碳中和目标的提出,温室气体减排的政策导向逐渐成为我国煤炭甲烷排放管控的重点,明确了煤炭甲烷减排方向。我国煤炭甲烷排放管控形成了以煤层气勘探开发利用、煤矿瓦斯抽采利用、关闭/废弃矿井瓦斯抽采利用、乏风瓦斯利用等全浓度利用,煤炭采前、采中和采后全周期利用为特征的关键技术路径。我国煤炭甲烷排放管控面临巨大压力和严峻挑战,诸多政策、机制、技术问题亟待破解。突破复杂地质条件适配性煤层... 相似文献
6.
Ground subsidence induced by extraction of coal seam belowground brings about changes in territorial environment. This occurs in two forms, namely, trough and pot-hole subsidence. Pot-hole subsidence is extremely hazardous as it does not give any prior indication before its occurrence. Several pot-holes have occurred in the recent past in the coal mines of South Eastern Coalfields Limited and called for a specific study to develop an in-depth understanding of various parameters influencing the pot-hole occurrence for formulating the basis of different predictive models. These critical parameters have been compiled and analysed for seven mines located in different areas of SECL, a subsidiary of Coal India Limited. Multiple regression and artificial neural network (ANN) techniques were used for the preparation of the predictive models to calculate pot-hole depth under different conditions. Different conditions considered in the study are development and depillaring, presence and absence of faults and water bodies. This paper presents the results of the studies carried out in Indian mines representing different geo-mining conditions along with the pot-hole depth prediction models developed. The developed models were validated for a few new cases with the model results matching (within 10 % error in the case of ANN model) with the actual pot-hole depth measured. More varied data sets can fine tune the developed models further. 相似文献
7.
Natural wetlands are thought to be one of the largest natural sources of atmospheric methane concentrations. Although numerous studies referred to the rate of methane fluxes in different geophysical regions, only a few had estimates of the overall geographical methane emissions in China. This study estimated the spatial variations of annual methane emissions with the pixel size of 1 km × 1 km from natural wetlands, excluding water surface, in China. The natural wetland areas were extracted from the database of the 2000 land covers, and geophysical divisions were used to represent different climate conditions. Methane emission in every geophysical region was calculated based on methane release factors obtained from an extensive overview of published literature and the data of elevation and vegetation proportion. The estimated annual methane emissions ranged from 0 to 5,702.8 kg per pixel within the area of 1 km2, and the spatial variation in methane emissions was strongly correlated with proportion of wetlands in the area. The total methane emission from natural wetland in China ranged from 3.48 to 7.16 Tg (terrogram, unit of weight) per year, with the mean value of 4.94 Tg per year, based on the area 133,000 km2 of natural wetlands. Specifically, the wetland in Northeast China had the highest contribution in China (39 %). Inner Mongolia and Qinghai-Tibet highland represented for about 25 and 21 %, respectively. The other 15 % of the measured methane was released in Northwest, North, Central, and South China. 相似文献
8.
9.
Anthony J. Rietl John A. Nyman Charles W. Lindau Colin R. Jackson 《Estuaries and Coasts》2017,40(3):832-841
Understanding methane emissions from natural sources is becoming increasingly important with future climactic uncertainty. Wetlands are the single largest natural source of methane; however, little attention has been given to how biota and interactions between aboveground and belowground communities may affect methane emission rates in these systems. To investigate the effects of vegetative disturbance and belowground biogeochemical alterations induced by biota on methane emissions in situ, we manipulated densities of Littoraria irrorata (marsh periwinkle snails) and Geukensia granosissima (gulf ribbed mussels) inside fenced enclosures within a Spartina alterniflora salt marsh and measured methane emissions and sediment extracellular enzyme activity (phosphatase, β-glucosidase, cellobiohydrolase, N-acetyl-β-D-glucosaminidase, peroxidase, and phenol oxidase) over the course of a year. Changes in snail density did not have an effect on methane emission; however, increased densities of ribbed mussels significantly increased the emission of methane. Sediment extracellular enzyme activities for phosphatase, cellobiohydrolase, N-acetyl-β-D-glucosaminidase, and phenol oxidase were correlated to methane emission, and none of the enzymes assayed were affected by the snail and mussel density treatments. While methane emissions from salt marsh ecosystems are lower than those from freshwater systems, the high degree of variability in emission rates and the potential for interactions with naturally occurring biota that increase emissions warrant further investigations into salt marsh methane dynamics. 相似文献
10.
A. Saghafi 《Australian Journal of Earth Sciences》2014,61(3):453-462
A new site-specific (Tier 3) method has been developed to determine greenhouse gas emissions from open coal mining. The Tier 3 method presented here is based on extensive measurement of gas emissions from open-cut coal mines and the physics of gas desorption from coal. It was adopted by Australian National Greenhouse and Energy Reporting in 2009 and since 2012 formed the scientific basis for the Australian Government guidelines on calculating greenhouse gas emissions from open cut mines. The main strength of this method is its site-specific nature and accuracy, as well as its ability to be integrated with routine coal exploration programs. New concepts were produced for the model: a coal mine is regarded as a ‘gas reservoir,’ with coal seam gas being emitted from a ‘gas release zone’ that consists of sedimentary geological units (emission layers) above and below the base of the mine. The primary data required for the method are the in situ gas content and gas composition of the coal and carbonaceous rocks contained within the gas-release zone. These data are obtained through direct measurement of gas desorption from bore cores. To reduce gas drilling, a mine lease is compartmentalised into ‘gas zones’ of similar gas content and reservoir properties. The outputs of the method are emission density (the potential volume of gas emitted from mining site per unit area of the ground surface) and emission factor (the gas volume emitted per tonne of raw coal extracted). Owing to spatial variability and errors of measurement, the estimate of emissions is associated with uncertainty. A simple method of calculating uncertainty of emissions is presented in this work. 相似文献
11.
Y. Zee Ma 《Mathematical Geosciences》2011,43(4):401-419
Both statistical methods and artificial neural network (ANN) have been used for lithology or facies clustering. ANN, in particular,
has increasingly gained popularity for clustering of categorical variables as well as for predictions of continuous variables.
In this article, we discuss several counter examples that show deficiencies of these techniques when used for automatic lithofacies
clustering. Our examples show that the lithofacies clustered by ANN alone or ANN in combination with principal component analysis
(PCA), as commonly used, are highly inconsistent with the benchmark charts based on laboratory results. We propose several
techniques to overcome these problems and improve the clustering of lithofacies, including (1) classification of lithofacies
using the minor or intermediate principal component(s), (2) rotation of a principal component before using ANN for clustering,
(3) cascading two or more PCAs and ANNs for clustering lithofacies or electrofacies, and (4) classifying lithofacies with
demarcated stratigraphic reference classes. 相似文献
12.
13.
地质成因的甲烷释放对大气的影响 总被引：2，自引：1，他引：2
地质成因自然源的甲烷释放在整个大气甲烷估算中起着非常重要的作用,它既是不含放射性14C甲烷源(死碳源)缺失部分的重要代表,也是甲烷重碳源的重要部分.概述了国内外关于地质成因甲烷释放对大气甲烷源与汇影响的研究进展,详述了来自地质成因化石燃料泄漏的人为甲烷释放以及来自沉积盆地(含油气盆地)、泥火山、地热区、海洋和甲烷水合物的地质自然源甲烷释放对大气甲烷源与汇的贡献及其影响因素;说明由于地质成因甲烷分布的区域性、不均匀性和时空的高度变化性,以及目前地质成因甲烷的通量估算仅建立在区域性的少量甲烷通量测试基础上,造成了地质成因甲烷释放通量估算的高度不确定性;指出研究中国西北地区油气田集聚区的甲烷释放通量,对油气田地质成因甲烷释放通量的估算具有重要意义. 相似文献
14.
Hazard maps of ground subsidence around abandoned underground coal mines (AUCMs) in Samcheok, Korea, were constructed using fuzzy ensemble techniques and a geographical information system (GIS). To evaluate the factors related to ground subsidence, a spatial database was constructed from topographic, geologic, mine tunnel, land use, groundwater, and ground subsidence maps. Spatial data, topography, geology, and various ground-engineering data for the subsidence area were collected and compiled in a database for mapping ground-subsidence hazard (GSH). The subsidence area was randomly split 70/30 for training and validation of the models. The relationships between the detected ground-subsidence area and the factors were identified and quantified by frequency ratio (FR), logistic regression (LR) and artificial neural network (ANN) models. The relationships were used as factor ratings in the overlay analysis to create ground-subsidence hazard indexes and maps. The three GSH maps were then used as new input factors and integrated using fuzzy-ensemble methods to make better hazard maps. All of the hazard maps were validated by comparison with known subsidence areas that were not used directly in the analysis. As the result, the ensemble model was found to be more effective in terms of prediction accuracy than the individual model. 相似文献
15.
Coalbed methane: From hazard to resource 总被引：4，自引：0，他引：4
Coalbed gas, which mainly consists of methane, has remained a major hazard affecting safety and productivity in underground coal mines for more than 100 years. Coalbed gas emissions have resulted in outbursts and explosions where ignited by open lights, smoking or improper use of black blasting powder, and machinery operations. Investigations of coal gas outbursts and explosions during the past century were aimed at predicting and preventing this mine hazard. During this time, gas emissions were diluted with ventilation by airways (e.g., tunnels, vertical and horizontal drillholes, shafts) and by drainage boreholes. The 1970's ‘energy crisis' led to studies of the feasibility of producing the gas for commercial use. Subsequent research on the origin, accumulation, distribution, availability, and recoverability has been pursued vigorously during the past two decades. Since the 1970's research investigations on the causes and effects of coal mine outbursts and gas emissions have led to major advances towards the recovery and development of coalbed methane for commercial use. Thus, coalbed methane as a mining hazard was harnessed as a conventional gas resource. 相似文献
16.
Coal seam degasification and its success are important for controlling methane, and thus for the health and safety of coal miners. During the course of degasification, properties of coal seams change. Thus, the changes in coal reservoir conditions and in-place gas content as well as methane emission potential into mines should be evaluated by examining time-dependent changes and the presence of major heterogeneities and geological discontinuities in the field. In this work, time-lapsed reservoir and fluid storage properties of the New Castle coal seam, Mary Lee/Blue Creek seam, and Jagger seam of Black Warrior Basin, Alabama, were determined from gas and water production history matching and production forecasting of vertical degasification wellbores. These properties were combined with isotherm and other important data to compute gas-in-place (GIP) and its change with time at borehole locations. Time-lapsed training images (TIs) of GIP and GIP difference corresponding to each coal and date were generated by using these point-wise data and Voronoi decomposition on the TI grid, which included faults as discontinuities for expansion of Voronoi regions. Filter-based multiple-point geostatistical simulations, which were preferred in this study due to anisotropies and discontinuities in the area, were used to predict time-lapsed GIP distributions within the study area. Performed simulations were used for mapping spatial time-lapsed methane quantities as well as their uncertainties within the study area. The systematic approach presented in this paper is the first time in literature that history matching, TIs of GIPs and filter simulations are used for degasification performance evaluation and for assessing GIP for mining safety. Results from this study showed that using production history matching of coalbed methane wells to determine time-lapsed reservoir data could be used to compute spatial GIP and representative GIP TIs generated through Voronoi decomposition. Furthermore, performing filter simulations using point-wise data and TIs could be used to predict methane quantity in coal seams subjected to degasification. During the course of the study, it was shown that the material balance of gas produced by wellbores and the GIP reductions in coal seams predicted using filter simulations compared very well, showing the success of filter simulations for continuous variables in this case study. Quantitative results from filter simulations of GIP within the studied area briefly showed that GIP was reduced from an initial ～73 Bcf (median) to ～46 Bcf (2011), representing a 37 % decrease and varying spatially through degasification. It is forecasted that there will be an additional ～2 Bcf reduction in methane quantity between 2011 and 2015. This study and presented results showed that the applied methodology and utilized techniques can be used to map GIP and its change within coal seams after degasification, which can further be used for ventilation design for methane control in coal mines. 相似文献
17.
Control of gas emissions in underground coal mines 总被引：4，自引：0，他引：4
Klaus Noack 《International Journal of Coal Geology》1998,35(1-4)
A high level of knowledge is now available in the extremely relevant field of underground gas emissions from coal mines. However, there are still tasks seeking improved solutions, such as prediction of gas emissions, choice of the most suitable panel design, extension of predrainage systems, further optimization of postdrainage systems, options for the control of gas emissions during retreat mining operations, and prevention of gas outbursts. Research results on these most important topics are presented and critically evaluated. Methods to predict gas emissions for disturbed and undisturbed longwall faces are presented. Prediction of the worked seam gas emission and the gas emission from headings are also mentioned but not examined in detail. The ventilation requirements are derived from the prediction results and in combination with gas drainage the best distribution of available air currents is planned. The drainage of the gas from the worked coal seam, also referred to as predrainage, can be performed without application of suction only by over or underworking the seam. But in cases where this simple method is not applicable or not effective enough, inseam-boreholes are needed to which suction is applied for a relatively long time. The reason for this is the low permeability of deep coal seams in Europe. The main influences on the efficiency of the different degasing methods are explained. Conventional gas drainage employing cross measure boreholes is still capable of improvement, in terms of drilling and equipment as well as the geometrical borehole parameters and the operation of the overall system. Improved control of gas emissions at the return end of retreating faces can be achieved by installation of gas drainage systems based on drainage roadways or with long and large diameter boreholes. The back-return method can be operated safely only with great difficulty, if at all. Another method is lean-gas drainage from the goaf. The gas outburst situation in Germany is characterized by events predominantly in the form of ‘nonclassical' outbursts categorized as ‘sudden liberation of significant quantities of gas'. Recent research results in this field led to a classification of these phenomena into five categories, for which suitable early detection and prevention measures are mentioned. 相似文献
18.
Abidin Kaya 《Geotechnical and Geological Engineering》2009,27(2):281-288
A backpropagation artificial neural network (ANN) model is developed to predict the secant friction angle of residual and
fully softened soils, using data reported by Stark et al. (J Geotech Geoenviron Eng ASCE 131:575–588, 2005). In the ANN model, index properties such as liquid limit, plastic limit, activity, clay fraction and effective normal stress
are used as input variables while secant residual friction angle is used as output variable. The model is verified using data
that were not used for model training and testing. The results also indicate that the secant residual friction angle of cohesive
soils can be predicted quite accurately using liquid limit, clay fraction and effective normal stress as input variables with
R
2 = 0.93. The sensitivity analysis results indicate that plastic limit and activity have no appreciable effect on ANN predicted
secant friction angles. The secant friction angle predictions of the ANN model were also compared with those of Stark’s et
al. (2005) curves and the empirical formulas suggested for the same data sets by Wright (Evaluation of soil shear strengths for slope
and retaining wall stability with emphasis on high plasticity clays, 2005). The comparison shows that the ANN model predictions are very close to those suggested by the Stark et al. (2005) curves but much better than the prediction of Wright’s (2005) empirical equations. The results also show that ANN is an alternative powerful tool to predict the secant friction angle
of soils. 相似文献
19.
Mohammad Arab Amiri Yazdan Amerian Mohammad Saadi Mesgari 《Arabian Journal of Geosciences》2016,9(5):421
This paper aims to provide a spatial and temporal analysis to prediction of monthly precipitation data which are measured at irregularly spaced synoptic stations at discrete time points. In the present study, the rainfall data were used which were observed at four stations over the Qara-Qum catchment, located in the northeast of Iran. Several models can be used to spatially and temporally predict the precipitation data. For temporal analysis, the wavelet transform with artificial neural network (WTANN) framework combines with the wavelet transform, and an artificial neural network (ANN) is used to analyze the nonstationary precipitation time-series. The time series of dew point, temperature, and wind speed are also considered as ancillary variables in temporal prediction. Furthermore, an artificial neural network model was used for comparing the results of the WTANN model. Therefore, four models were developed, including WTANN and ANN with and without ancillary data. Several statistical methods were used for comparing the results of the temporal analysis. It was evident that at three of the four stations, the WTANN models were more effective than the ANN models, and only at one station, the ANN model with ancillary data had better performance than the WTANN model without ancillary data. The values of correlation coefficient and RMSE for WTANN model with ancillary data for the validation period at Mashhad station which showed the best results were equal to 0.787 and 13.525 mm, respectively. Finally, an artificial neural network model was used as an alternative interpolating technique for spatial analysis. 相似文献
20.
Prediction of longitudinal dispersion coefficient in natural rivers using a cluster-based Bayesian network 总被引：1，自引：0，他引：1
Mohamad Javad Alizadeh Hosein Shahheydari Mohammad Reza Kavianpour Hamid Shamloo Reza Barati 《Environmental Earth Sciences》2017,76(2):86
The longitudinal dispersion coefficient is a key element in determining the distribution and transmission of pollution, especially when cross-sectional mixing is completed. However, the existing predictive techniques for this purpose exhibit great amounts of uncertainty. The main objective of this study is to present a more accurate model for predicting longitudinal dispersion coefficient in natural rivers and streams. Bayesian network (BN) approach was considered in the modeling procedure. Two forms of input variables including dimensional and dimensionless parameters were examined to find the best model structure. In order to increase the performance of the model, the clustering method as a preprocessing data technique was applied to categorize the data in separate groups with similar characteristics. An expansive data set consisting of 149 field measurements was used for training and testing steps of the developed models. Three performance evaluation criteria were adopted for comparison of the results of the different models. Comparison of the present results with the artificial neural network (ANN) model and also well-known existing equations showed the efficiency of the present model. The performance of dimensionless BN model 30% is more than dimensional ones in terms of the root mean square error. The accuracy criterion was increased from 70 to 83% by performing clustering analysis on the BN model. The BN-cluster model 43% is more accurate than ANN model in terms of the accuracy criterion. The results indicate that the BN-cluster model give 16% better results than the best available considered model in terms of the accuracy criterion. The developed model provides a suitable approach for predicting pollutant transport in natural rivers. 相似文献