In-situ gas contents of a multi-section coal seam in Sydney basin for coal and gas outburst management

The gas content is crucial for evaluating coal and gas outburst potential in underground coal mining. This study focuses on investigating the in-situ coal seam gas content and gas sorption capacity in a representative coal seam with multiple sections (A1, A2, and A3) in the Sydney basin, where the CO_(2) composition exceeds 90%. The fast direct desorption method and associated devices were described in detail and employed to measure the in-situ gas components (Q_(1), Q_(2), and Q_(3)) of the coal seam. The results show that in-situ total gas content (Q_(T)) ranges from 9.48 m^(3)/t for the A2 section to 14.80 m^(3)/t for the A3 section, surpassing the Level 2 outburst threshold limit value, thereby necessitating gas drainage measures. Among the gas components, Q_(2) demonstrates the highest contribution to Q_(T), ranging between 55% and 70%. Furthermore, high-pressure isothermal gas sorption experiments were conducted on coal samples from each seam section to explore their gas sorption capacity. The Langmuir model accurately characterizes CO_(2) sorption behavior, with ft coefcients (R^(2)) greater than 0.99. Strong positive correlations are observed between in-situ gas content and Langmuir volume, as well as between residual gas content (Q_(3)) and sorption hysteresis. Notably, the A3 seam section is proved to have a higher outburst propensity due to its higher Q_(1) and Q_(2) gas contents, lower sorption hysteresis, and reduced coal toughness f value. The insights derived from the study can contribute to the development of efective gas management strategies and enhance the safety and efciency of coal mining operations.

A rapid and accurate direct measurement method of underground coal seam gas content based on dynamic diffusion theory

Coal seam gas content is frequently measured in quantity during underground coal mining operation and coalbed methane(CBM)exploration as a significant basic parameter.Due to the calculation error of lost gas and residual gas in the direct method,the efficiency and accuracy of the current methods are not inadequate to the large area multi-point measurement of coal seam gas content.This paper firstly deduces a simplified theoretical dynamic model for calculating lost gas based on gas dynamic diffusion theory.Secondly,the effects of various factors on gas dynamic diffusion from coal particle are experimentally studied.And sampling procedure of representative coal particle is improved.Thirdly,a new estimation method of residual gas content based on excess adsorption and competitive adsorption theory is proposed.The results showed that the maximum error of calculating the losing gas content by using the new simplified model is only 4%.Considering the influence of particle size on gas diffusion law,the particle size of the collected coal sample is below 0.25 mm,which improves the measurement speed and reflects the safety representativeness of the sample.The determination time of gas content reduced from 36 to 3 h/piece.Moreover,the absolute error is 0.15–0.50 m^3/t,and the relative error is within 5%.A new engineering method for determining the coal seam gas content is developed according to the above research.

Seismic studies of coal bed methane content in the west coal mining area of Qinshui Basin

The coal bed methane content(CBMC)in the west mining area of Jincheng coalfield,southeastern Qjnshui Basin,is studied based on seismic data and well-logs together with laboratory measurements.The results show that the Shuey approximation has better adaptability according to the Zoeppritz equation result;the designed fold number for an ordinary seismic data is sufficient for post-stack data but insufficient for pre-stack data regarding the signal to noise ratio(SNR).Therefore a larger grid analysis was created in order to improve the SNR.The velocity field created by logging is better than that created by stack velocity in both accuracy and effectiveness.A reasonable distribution of the amplitude versus offset(AVO)attributes can be facilitated by taking the AVO response from logging as a standard for calibrating the amplitude distribution.Some AVO attributes have a close relationship with CBMC.The worst attribute is polarization magnitude,for which the correlation coefficient is 0.308;and the best attribute is the polarization product from intercept,of which the correlation coefficient is-0.8136.CBMC predicted by AVO attributes is better overall than that predicted by direct interpolation of CBMC;the validation error of the former is 14.47%,which is lower than that of the latter 23.30%.CBMC of this area ranges from2.5 m^3/t to 22 m^3/t.Most CBMC in the syncline is over 10m^3/t,but it is below 10m^3/t in the anticline;on the whole,CBMC in the syncline is higher than that in anticline.

Quantitative Analysis of Carbon Content in Bituminous Coal by Laser-Induced Breakdown Spectroscopy Using UV Laser Radiation

The carbon content of bituminous coal samples was analyzed by laser-induced breakdown spectroscopy. The 266 nm laser radiation was utilized for laser ablation and plasma generation in air. The partial least square method and the dominant factor bused PLS method were used to improve the measurement accuracy of the carbon content of coal. The results showed that the PLS model could achieve good measurement accuracy, and the dominant factor based PLS model could further improve the measurement accuracy. The coefficient of determination and the root-mean-square error of prediction of the PLS model were 0.97 and 2.19%, respectively; and those values for the dominant factor based PLS model were 0.99 and 1.51%, respectively. The results demonstrated that the 266 nm wavelength could accurately measure the carbon content of bituminous coal.

Discussion on determination of gas content of coal and uncertainties of measurement

Gas content of coal is mostly determined using a direct method, particularly in coal mining where mine safety is of paramount importance. Direct method consists of measuring directly the volume of gas desorbed from coal in several steps, from solid then crushed coal. In mixed gas conditions the composition of the desorbed gas is also measured to account for contribution of various coal seam gas in the mix. The determination of gas content using the direct method is associated with errors of measurement of volume of gas but also the errors associated with measurement of composition of the desorbed gas. These errors lead to uncertainties in reporting the gas content and composition of in-situ seam gas. This paper discusses the current direct method practised in Australia and potential errors and uncertainty associated with this method. Generic methods of estimate of uncertainties are also developed and are to be included in reporting gas content of coal. A method of direct measurement of remaining gas in coal following the completion of standard gas content testing is also presented. The new method would allow the determination of volume of almost all gas in coal and therefore the value of total gas content. This method is being considered to be integrated into a new standard for gas content testing.

Calculation of gas content in coal seam influenced by in-situ stress grads and ground temperature

On the basis of the analysis of coal bed gas pressure in deep mine, and the coal bed permeability ( k ) and the characteristic of adsorption parameter ( b ) changing with temperature, the author puts forward a new calculating method of gas content in coal seam influenced by in situ stress grads and ground temperature. At the same time, the contrast of the measuring results of coal bed gas pressure with the computing results of coal bed gas pressure and gas content in coal seam in theory indicate that the computing method can well reflect the authenticity of gas content in coal seam,and will further perfect the computing method of gas content in coal seam in theory,and have important value in theory on analyzing gas content in coal seam and forecasting distribution law of gas content in coal seam in deep mine.

Preparation of activated carbon with low ash content and high specific surface area from coal in the presence of KOH

An activated carbon with ash content less than 10% and specific surface area more than 1 600 m 2 /g was prepared from coal and the effect of K containing compounds in preparation of coal based activated carbon was investigated in detail in this paper. KOH was used in co carbonization with coal, changes in graphitic crystallites in chars derived from carbonization of coal with and without KOH were analyzed by X ray diffraction (XRD) technique, activation rates of chars with different contents of K containing compounds were deduced, and resulting activated carbons were characterized by nitrogen adsorption isotherms at 77 K and iodine numbers. The results showed that the addition of KOH to the coal before carbonization can realize the intensive removal of inorganic matters from chars under mild conditions, especially the efficient removal of dispersive quartz, an extremely difficult separated mineral component in other processes else. Apart from this, KOH demonstrates a favorable effect in control over coal carbonization with the goal to form nongraphitizable isotropic carbon precursor, which is a necessary prerequisite for the formation and development of micro pores. However, the K containing compounds such as K 2 CO 3 and K 2 O remaining in chars after carbonization catalyze the reaction between carbon and steam in activation, which leads to the formation of macro pores. In the end an innovative method, in which KOH is added to coal before carbonization and K containing compounds are removed by acid washing after carbonization, was proposed for the synthesis of quality coal based activated carbon.

Prediction of ash content of unloaded coal based on a discrete element simulation

Based on analysis of regularity of stacking coal,discrete element simultaneous simulation is adopted to predict the process of unloading coal,which is proved to be effcient in the prediction of ash content.The results show that the altitude of new irregular coal is equal to the income coal volume divided by area of cabin.The distribution of infnitesimal flow velocity helps to induce the motion equation of infnitesimal element,which provides the mathematical model for computer simulation.Swarm,a computer programming language,is utilized in this study.Adaptive infnitesimal stacking algorithm helps settle the diffculties in attainment of infnitesimal elements.The result of simulation is similar to the actual situation,which can accurately predict the ash contents of current time and cumulative time.Coal movement in the cabin is a new project,the result of which can also be applied to other solid particles and the widespread of the result will be highly valued.

Study on Filling Cross-Roadway in Fully-Mechanized Coal Faces with High Water-Content Material

A new method using high water content material to mechanically fill cross roadways to form artificial bottom for coal faces was introduced. The reasonable determination of filling range, the optimization of the compounding ratio of high water content material, and the filling technique were discussed in detail. This new method has been spread after industrial testing in Baodian Colliery. Compared with the traditional method, the manual wooden chock method, the new one decreases about 40% of the filling range and cost in dealing every one set of cross roadway in the testing condition.

FAST MEASUREMENT OF ASH CONTENT IN COAL WASHING PLANT

The coal filter cake is a product of fine coal after floatation which has an ash content of 7-13%, water content of 30±2%, and a particle size of less than 1 mm. The ash content was measured by the intensity of the single backscattered gamma-ray, and its accuracy is mainly dependent on the energy of the gamma-ray. The 238Pu low energy photon source is selected in this work. The energy of its gamma-ray is 15 keV, which can result not only in the best sensitivity, but also in the lowest contribution to the environment radiation. The root mean square deviation of the ash measurement is±0.33% (±1σ).

Evaluation of coal bed methane content using BET adsorption isotherm equation

Coal bed methane is unconventional raw natural gas stored in coal seam with considerable reserves in China.In recent years,as the coal bed methane production,the safety and the use of resources have been paid more attentions.Evaluating coal bed methane content is an urgent problem.A BET adsorption isotherm equation is used to process the experimental data.The various parameters of BET equation under different temperatures are obtained;a theoretical gas content correction factor is proposed,and an evaluation method of actual coal bed methane is established.

煤层瓦斯含量测定技术及装备研究进展

瓦斯含量是煤与瓦斯突出危险预测、煤层瓦斯资源量估算、矿井瓦斯治理工程设计的重要参数。围绕如何在大区域准确快速测定煤层瓦斯含量,依托国家科技重大专项、国家自然科学基金和煤炭企业联合基金等项目科技攻关,在取样、测试方面取得了一定进展。主要表现在如下4个方面:①煤层瓦斯含量测定取样经历了孔口接样、岩心管定点取样、压力引射定点取样和密闭取样4个阶段,密闭取样装备保压能力达到11.5 MPa,煤心直径达到38 mm;②针对不同煤层地质条件,发展形成了顺煤层定向长钻孔密闭取样、底板穿层钻孔密闭取样和顶(底)板梳状定向长钻孔密闭取样3种取样技术;③在河南焦作和山西晋城矿区硬煤层中,顺层定向长钻孔取样深度达到516 m,密闭取样法测得煤层瓦斯含量较常规取样法分别平均提高了0.44倍和1.04倍。在安徽淮南矿区碎软煤层中,穿层钻孔密闭取样深度达到209 m,测得煤层瓦斯含量较常规取样法平均提高了0.26倍;在安徽淮北矿区碎软煤层中,顶(底)板梳状钻孔密闭取样深度达到484 m,测得煤层瓦斯含量较常规取样法平均提高了0.19倍,密闭取样法在煤层瓦斯含量测定精度、探测范围上优于常规取样法;④在瓦斯含量测试方面,除了传统解吸法测试,发展了系列煤矿井下瓦斯含量快速测试装备,可实现最快30 min内测得煤层瓦斯含量,一般用于百米孔内的瓦斯含量测试。提出了煤层瓦斯含量测定密闭取样装备需向小型化、轻量化的方向发展,并能实现随钻密闭取样。在测试上,应根据实际情况确定合理的解吸终止限,并将测试装备和密闭取样装备进一步结合,以实现深孔瓦斯含量快速准确测定。密闭取样技术已成为煤层瓦斯含量大区域精准勘查、预测的主要手段,是煤炭安全高效开采的重要技术保障。

水分对CH_(4)和CO_(2)在煤中竞争吸附特性影响研究

为研究水分对CH_(4)和CO_(2)及混合气体在煤中竞争吸附的影响,通过自主研发的含瓦斯煤多元气体竞争吸附试验系统进行不同含水率煤对CH_(4)和CO_(2)单组分吸附研究,试验结果表明:水分并没有改变CH_(4)和CO_(2)等温吸附曲线的基本规律,在相同条件下,水分也未影响煤对单组分气体吸附能力的排序,始终是煤对CO_(2)的吸附能力大于对CH_(4)的吸附能力。相同条件下,水分对CH_(4)的抑制率大于CO_(2)吸附量抑制率,说明水分对煤吸附弱吸附性气体的抑制程度更大。在进行水对混合气体的竞争吸附影响研究试验,发现:当注入煤体的气体比例保持不变时,在同一吸附平衡压力下,混合气体的吸附总量随着水分含量的升高而降低,并且吸附平衡后的CH_(4)吸附量和CO_(2)吸附量都随着煤体中水分含量的增大而减小;而当含水率不变时,同一注气比例下的气体吸附平衡压力越大,吸附平衡后的CH_(4)吸附量和CO_(2)吸附量越大。游离相中的CO_(2)的体积分数始终低于气源,而CH_(4)体积分数始终高于气源。不同条件下CO_(2)/CH_(4)选择系数的数值均大于1,范围处在4.8~5.4,煤对CO_(2)的吸附亲和能力大于CH_(4)。相同组分混合气体吸附条件下,CO_(2)/CH_(4)选择系数均随着试验煤样含水率变大而降低。该研究进一步完善影响煤对气体吸附的因素的理论分析,以及为工程实践为井下注气促抽瓦斯技术提供理论依据。

开采保护层与预抽煤层瓦斯防突效果分析

为比较开采保护层与预抽煤层瓦斯防突效果,以1124(3)运顺开采保护层段和预抽煤层瓦斯段煤巷掘进为试验对象,统计了试验地点煤巷掘进期间残余瓦斯含量、钻屑瓦斯解吸指标K1、钻屑量等防突指标,采用假设检验方法推断了各防突指标是否有差别,分析了开采保护层段和预抽煤层瓦斯段各防突指标产生差别的原因,验证了开采保护层区域防突措施比预抽煤层瓦斯区域防突措施更加安全可靠。

基于数据生命周期的煤泥浮选智能控制技术研究进展

随着国家政策和新一代人工智能技术的持续牵引,矿山智能化研究取得突破,其中,选煤厂智能化建设受到高度关注,煤泥浮选智能控制技术一直是阻碍选煤厂智能化建设的关键瓶颈之一。以煤泥浮选数据生命周期为主线,从浮选精煤/尾煤灰分在线预测、浮选药剂智能添加和煤泥浮选系统智能决策3个角度综述了煤泥浮选智能控制技术的研究进展,并展望未来煤泥浮选智能控制技术发展趋势。浮选精煤灰分在线预测困难重重,单一视觉特征信息并不可靠,尾矿灰分的预测技术相对更加成熟可靠;浮选药剂添加量受多个过程变量同时制约,模型性能在整个工况区间的自适应性和泛化能力还需进一步提升;当前浮选工业系统智能控制技术的进一步发展严重受限于浮选精煤/尾煤灰分等指标的预测精度、传感器检测精度、药剂添加精度等因素。浮选过程数据集维度更高,难以建立可靠的知识库,以深度学习为代表的新一代人工智能技术能适应这类数据结构。此外,已有浮选监测系统只针对特定矿物,唯一性较高。未来浮选智能控制系统应集中攻克指标预测、传感器检测精度等方面限制,建立多煤种、模板化的煤泥浮选智能控制资料大数据集和大模型。

基于EMD-GRU的港口堆场煤炭含水率智能预测与实验研究

针对煤炭港口堆场洒水抑尘需求,提出了基于EMD-GRU的煤炭含水率预测模型并进行了实验验证。通过建立煤炭堆场含水率预测模型,利用实时数据驱动预测煤炭堆垛含水率变化,根据气象数据与含水率变化情况判断煤炭堆垛未来起尘情况并制定相应的洒水策略。实验结果表明,EMD-GRU模型的均方根误差、平均绝对误差、平均绝对百分比误差和决定系数分别为0.768、0.566、9.52%、0.944,与SVR、DTR、RNN、LSTM、GRU等预测模型相比,EMD-GRU预测模型的各误差值均最低,决定系数为最高,且预测精度与拟合效果最好。

基于PROSAIL模型和Sentinel-2数据的陕北煤炭矿区植被叶绿素含量监测

为满足煤炭矿区植被叶绿素含量高精度动态监测需求,该文以陕北大柳塔矿区为研究区,首先分析PROSAIL模型对矿区典型植被欧李、野樱桃的适用性,然后根据PROSAIL辐射传输模型建立查找表,结合基于正则化的代价函数对欧李、野樱桃叶绿素含量进行反演,并利用SNAP软件反演结果与地面实测数据对PROSAIL模型反演结果进行验证,最后利用所构建模型反演得到2016—2019年大柳塔矿区植被叶绿素含量空间分布。结果表明:PROSAIL模型模拟光谱与地面实测光谱的绝对偏差平均值最大为0.016,该精度满足植被参数反演;PROSAIL模型反演得到的欧李、野樱桃叶绿素含量与地面实测数据的决定系数、均方根误差和相对均方根误差分别为0.679、1.926和4.625%,优于SNAP软件反演结果,反演得到的大柳塔矿区叶绿素含量时空变化与实际植被生态修复情况和土地利用覆盖类型一致。研究结果可为矿区植被叶绿素反演和生态修复效果评估提供技术参考。

基于GRA-GASA-SVM的煤层瓦斯含量预测方法研究

为提升煤层瓦斯含量预测精度,提出一种采用遗传模拟退火算法混合优化支持向量机(SVM)参数的瓦斯含量预测模型(GRA-GASA-SVM模型)。该模型将GA和SA整合为遗传模拟退火算法协同优化SVM的参数,以解决传统网格寻优算法取值范围无法确定和单一智能算法优化程度有限等问题。利用灰色关联分析(GRA)压缩数据集维度,建立瓦斯含量预测参数体系并作为GASA-SVM的输入数据集。结果表明:SVM模型、GA-SVM模型和GASA-SVM模型10折交叉验证瓦斯含量预测总平均相对误差分别为15.98%、13.55%和10.58%。相比SVM模型和GA-SVM模型,GASA-SVM模型预测稳定性更优、预测精准度更高且对新样本泛化能力更强。

低煤化欠饱和煤心含气量预测数值模拟

为对比分析长焰煤储层煤心现场解吸动态与数值模拟解吸动态,实测了新疆某井长焰煤煤心现场含气量,构建了吸附气欠饱和储层煤心数值模型,并基于此分析了损失气量计算方法。结果表明:构建的吸附气欠饱和煤心(吸附气饱和度54.77%、77.51%、99.79%)数值模型计算的损失气量、解吸气量和残余气量与现场测试相应结果接近(误差<10.12%),可近似反映欠饱和储层煤心含气量构成;对于构建的含气饱和(吸附气饱和与游离气饱和)储层煤心数值模型,损失气时间与解吸时间和的平方根与解吸初期累计解吸气量回归分析预测损失气量误差较大,已不适用;相同损失气时间下,饱和煤心损失气占比(18.64%)高于吸附气欠饱和煤心损失气占比(11.95%),饱和煤心解吸气占比(80.90%)低于吸附气欠饱和煤心解吸气占比(87.32%),饱和煤心残余气占比(0.46%)低于吸附气欠饱和煤心残余气占比(0.63%)。