A gas mixture enhanced coalbed methane recovery technology applied to underground coal mines

被引:0
|
作者
Z. Fang
X. Li
G. G. X. Wang
机构
[1] Chinese Academy of Sciences,State Key Laboratory of Geomechanics and Geotechnical Engineering, Institute of Rock and Soil Mechanics
[2] The University of Queensland,School of Chemical Engineering
来源
Journal of Mining Science | 2013年 / 49卷
关键词
oal; coalbed methane; coal mine methane; gas mixture injection; enhanced coalbed methane recovery; underground drainage system; field trial;
D O I
暂无
中图分类号
学科分类号
摘要
This paper presents a field trial for developing a gas mixture enhanced coalbed methane (GECBM) technology that can be integrated with underground coal mine methane (CMM) drainage systems. The field trial was carried out in a deep underground coalmine roadway in two stages, initially degassing using a conventional method for 30 days in three boreholes installed in the underground coal seam and then injecting the gas mixture from one of the boreholes for about 2 months. The field trial focuses on the investigation of the technical and economic feasibilities of G-ECBM technology applied to underground CMM drainage systems. The results revealed that the G-ECBM technology integrated with underground methane drainage systems can provide an effective method to enhance the coalbed methane (CBM) recovery from coal mines and the efficiency of underground gas drainage systems, and hence improve the mining safety. The field measurements showed that the single-borehole flow rate and concentration of CH4 for the production boreholes with G-ECBM have increased by a factor of 4.73 and 1.68 on average, respectively, compared with the conventional production boreholes without G-ECBM. The results also showed the economic prospect of applying G-ECBM technology to underground CMM drainage systems.
引用
收藏
页码:106 / 117
页数:11
相关论文
共 50 条
  • [41] Enhanced coalbed gas drainage based on hydraulic flush from floor tunnels in coal mines
    Liu Yanwei
    Wang Qian
    Chen Wenxue
    Liu Mingju
    Mitri, Hani
    INTERNATIONAL JOURNAL OF MINING RECLAMATION AND ENVIRONMENT, 2016, 30 (01) : 37 - 47
  • [42] Coal permeability evolution triggered by variable injection parameters during gas mixture enhanced methane recovery
    Zhou, Lijun
    Zhou, Xihua
    Fan, Chaojun
    Bai, Gang
    ENERGY, 2022, 252
  • [43] Multiscale model for flow and transport in CO2-enhanced coalbed methane recovery incorporating gas mixture adsorption effects
    Le, T. D.
    Ha, Q. D.
    Panfilov, I
    Moyne, C.
    ADVANCES IN WATER RESOURCES, 2020, 144
  • [44] Review of coal and gas outburst in Australian underground coal mines
    Dennis J.Black
    International Journal of Mining Science and Technology, 2019, 29 (06) : 815 - 824
  • [45] Review of coal and gas outburst in Australian underground coal mines
    Black, Dennis J.
    INTERNATIONAL JOURNAL OF MINING SCIENCE AND TECHNOLOGY, 2019, 29 (06) : 815 - 824
  • [46] Computer modeling of coal bed methane recovery in coal mines
    AGH University of Science and Technology, Mickiewicza Avenue 30, 30-059 Krakow, Poland
    J Energy Resour Technol Trans ASME, 3
  • [47] Computer Modeling of Coal Bed Methane Recovery in Coal Mines
    Stopa, Jerzy
    Nawrat, Stanislaw
    JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME, 2012, 134 (03):
  • [48] Pore/fracture structure and gas permeability alterations induced by ultrasound treatment in coal and its application to enhanced coalbed methane recovery
    Liu, Peng
    Liu, Ang
    Zhong, Fangxiang
    Jiang, Yongdong
    Li, Jiajun
    JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2021, 205
  • [49] Forecasting of methane gas in underground coal mines: univariate versus multivariate time series modeling
    Juan Diaz
    Zach Agioutantis
    Dionissios T. Hristopulos
    Kray Luxbacher
    Steven Schafrik
    Stochastic Environmental Research and Risk Assessment, 2023, 37 : 2099 - 2115
  • [50] Forecasting of methane gas in underground coal mines: univariate versus multivariate time series modeling
    Diaz, Juan
    Agioutantis, Zach
    Hristopulos, Dionissios T.
    Luxbacher, Kray
    Schafrik, Steven
    STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2023, 37 (06) : 2099 - 2115