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作 者:高鉴东 傅雪海[1,2] 刘爱华[1,2] 罗培培[1,2]
机构地区:[1]中国矿业大学资源与地球科学学院,江苏徐州221116 [2]煤层气资源与成藏过程教育部重点实验室,江苏徐州221008
出 处:《西安科技大学学报》2015年第1期50-55,共6页Journal of Xi’an University of Science and Technology
基 金:国家科技重大专项(2011ZX05034-004);煤层气973项目(2009CB219605)
摘 要:为了解释全煤层连续煤质参数,基于山西和顺煤层气区块4口煤层气井28层次的煤质及测井成果数据,运用岩石物理体积模型法和统计回归法,建立了15#煤层测井响应值与纯煤、灰分、水分间的体积模型和统计回归模型。选择另外2口煤层气井实测煤心煤质成果对模型进行了检验,最后进行误差分析。结果表明:对煤质参数测井响应较为敏感的有中子、密度、自然伽玛曲线,岩石物理体积模型法较统计回归法拟合效果更好,且预测值在有效参考范围内;测井体积模型可用于研究区15#煤层连续的煤质参数预测,建议今后选取更为贴近原位煤层的煤质测试数据,并选取合适的煤岩骨架参数,可以得到更为精确的预测模型。In order to explain the consecutive coal quality parameters of the whole coal seam, volume model between well logging responses of coal No. 15 and content of pure coal, water and ash as well as the statistical regression model were established by means of rock physical volume model method and statistical regression method based on the coal quality testing results of 28 seams in 4 CBM ( coalbed methane) wells and well logging data in Heshun CBM block of Shanxi province. Measured results of coal core quality in another two CBM wells were then selected to inspect the predicted value of the models, and finally came the error analysis on the predicted results. It shows that neutron, density and natural gamma curve were sensitive to the logging response of coal quality parameters, compared with the statistical regres- sion method, the rock physical volume model method matched more effectively with higher accuracy and all the predictive values were within the useful reference range, which shows that the log equivalent volume model can be used to predict the consecutive coal quality parameters of coal No. 15 in the study area, it suggests that more accurate prediction model could be obtained if coal quality test data was carried out more close to in-situ coal seam with suitable coal rock frame parameters.
分 类 号:P631.8[天文地球—地质矿产勘探]
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