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《Journal of China Coal Society》 2012-S2
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High precision and quantitative prediction mechanics method of coalbed methane enrichment area in geo-stress and geothermal field

LI Zhi-qiang1,XIAN Xue-fu2,HUANG Gun2(1.Henan Provincial Key Lab of Gas Geology and Control-Cultivation Base of Provincial and Ministry Joint State Key,Henan Polytecnnic University,Jiaozuo 454000,China;2.State Key Laboratory of Coal Mine Disaster Dynamics and Control,Chongqing University,Chongqing 400030,China)  
Aiming at the shortcomings of inaccurate predicting position,qualitative description and low precision about coalbed methane enrichment region predicting in China,this paper proposed quantitative prediction mechanics method of coalbed methane enrichment region,established prediction equations of gas pressure and coalbed methane(CBM) content influenced by stress and temperature.The equations reflects influence of ground stress and ground temperature on gas pressure,content of CBM and coal porosity.The stress and temperature affects gas pressure and changes gas adsorption content,affects gas pressure and coal porosity and changes gas free content.In addition,temperature affects adsorption parameter b and changes adsorption content.Took Libixia Yanjing mining area in Chongqing as an example,experiments of initial rock stress testing based on Kaiser AE method,methane adsorption testing at different temperatures,coal porosity testing at different depth,were carried out.Adsorption experiment indicates that adsorption parameter a is not obviously changed with temperature,b is linearly reduced with temperature increasing.Based on experiment and geological data,distribution of CBM content was predicted quantitatively.According to the dissimilarity of enrichment degree,the research area was divided into two-level enrichment region by CBM content as index.The prediction method overcomes the shortcomings of qualitative description,error prediction,low precision of CBM predicting.
【Fund】: 国家重点基础研究发展计划(973)资助项目(2011CB201203);; 国家自然科学基金青年基金资助项目(51004041);国家自然科学基金资助项目(51174241)
【CateGory Index】: TD713.2
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