[1]高鉴东,傅雪海,刘爱华,等.沁水盆地和顺15# 煤层煤质参数的测井响应预测[J].西安科技大学学报,2015,(01):50-55.[doi:10.13800/j.cnki.xakjdxxb.2015.0109]
 GAO Jian-dong,FU Xue-hai,LIU Ai-hua,et al.Logging response prediction of 15# coalbed coal quality parameters in Heshun area Qingshui Basin[J].Journal of Xi'an University of Science and Technology,2015,(01):50-55.[doi:10.13800/j.cnki.xakjdxxb.2015.0109]
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沁水盆地和顺15# 煤层煤质参数的测井响应预测(/HTML)
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西安科技大学学报[ISSN:1672-9315/CN:61-1434/N]

卷:
期数:
2015年01期
页码:
50-55
栏目:
出版日期:
2015-02-28

文章信息/Info

Title:
Logging response prediction of 15# coalbed coal quality parameters in Heshun area Qingshui Basin
文章编号:
1672-9315(2015)01-0050-06
作者:
高鉴东12傅雪海12刘爱华12 罗培培12
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
Author(s):
GAO Jian-dong 12FU Xue-hai 12LIU Ai-hua 12LUO Pei-pei 12
1.School of Resources & Earth Science,China University of Mining & Technology,Xuzhou 221116,China;
2.Key Laboratory of CBM Resources and Dynamic Accumulation Process(CUMT),Xuzhou 221008,China
关键词:
煤质 测井响应 体积模型 回归模型
Keywords:
coal quality logging response volume model regression method
分类号:
P 631.8
DOI:
10.13800/j.cnki.xakjdxxb.2015.0109
文献标志码:
A
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。
Abstract:
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 twoCBM 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 regression 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.

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备注/Memo

备注/Memo:
基金项目:国家科技重大专项(2011ZX05034-004); 煤层气973项目(2009CB219605) <
通讯作者:高鉴东(1989-),男,内蒙古集宁人,硕士研究生,E-mail:gaojiandong723@163.com
更新日期/Last Update: 2015-01-15