煤工业分析指标与测井参数的相关性及其模型

Relationship between approximate analysis of coal and log parameters and its models

  • 摘要: 以河南新郑矿区赵家寨井田为依托,通过试验和统计分析,建立了煤的工业分析指标与测井参数的相关关系及模型,揭示了煤质测井响应机制。研究结果表明,煤的工业分析指标与其测井参数之间存在明显的相关性,表现为:原煤水分含量与密度和视电阻率之间呈负相关关系,与自然电位和自然伽马呈正相关关系;灰分与密度和自然伽马以及自然电位呈正相关关系,与视电阻率呈负相关关系;原煤挥发分与视电阻率和密度呈负相关关系,挥发分与自然电位和自然伽马呈正相关关系。研究结果还显示,煤质指标与测井参数之间的相关性是由煤中有机质和无机质含量、性质和结构以及煤化作用等因素所决定的。分别建立了用测井曲线预测原煤工业分析指标的多元统计模型,在煤炭与煤层气勘探开发中,可以用测井曲线预测原煤工业分析指标。

     

    Abstract: The main indicator of raw coal quality evaluation is approximate analysis. Based on Zhaojiazhai coal field of Xinzheng mine area in Henan province, through the testing and statistical analysis, the relationship between coal approximate analysis and log parameters and its models have been established, and the logging response mechanism of coal quality was studied. The results show that between approximate analysis and log parameters exists an obvious correlation. There is the negative correlation between the moisture content of raw coal and the apparent resistivity and density, and the positive correlation between the moisture content of raw coal and the natural potential and natural gamma. The ash content of raw coal has a positive corelation with density, natural gamma and natural potential respectively, and a negative correlation with apparent resistivity. There is a negative correlation between the volatile of raw coal and apparent resistivity and density, and a positive corelation between the volatile of raw coal and natural potential and natural gamma. The correlation between the coal quality indicators and the log parameters is determined by the content of organic matter and inorganic matter in coal, the coal property, the coal structure, the coalification and other factors. The multi-statistical models were established respectively through logging curves predicting parameters for approximate analysis. In the process of exploring coal and coal bed methane, the purpose of predicting the parameters for approximate analysis can be realized by using logging curves.

     

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