基于主成分分析法的煤体结构预测方法研究  

Research on Coal Structure Prediction Method Based on Principal Component Analysis

作　　者：林龙生[1] 王文文 谢岚 LIN Long-sheng;WANG Wen-wen;XIE Lan(Oilfield Technology Department,China Oilfield Services Limited,Langfang 065201,China;China United Coalbed Methane Co.,Ltd.,Beijing 100016,China)

机构地区：[1]中海油田服务股份有限公司油田技术事业部,河北廊坊065201 [2]中联煤层气有限责任公司,北京100016

出　　处：《煤炭技术》2021年第6期101-102,共2页Coal Technology

摘　　要：煤体结构是确定煤层气吸附能力和渗透性的重要因素之一,为了能够精确刻画煤体结构,选择A工区井径CAL、密度DEN、自然伽马GR、电阻率RD等测井数据为输入变量,采用主成分分析法(PCA),建立了新的煤体结构预测模型,对目标煤体结构进行曲线重构。结果表明,主成分分析法是提高煤体结构识别的有效方法,预测结果与不同等级煤层岩心具有很好的一致性。Coal structure is one of the important factors to determine the adsorption capacity and permeability of coalbed methane,taking the well diameter CAL,density DEN,gamma ray GR,resistivity RD and other logging data of work area a as input variables,a new coal structure prediction model is established by principal component analysis(PCA),and the target coal structure curve is reconstructed.The results show that the principal component analysis method is an effective method to improve the recognition of coal structure,and the prediction results are in good agreement with the cores of different grades of coal seams.

关 键 词：煤体结构 PCA 测井数据 

分 类 号：P618.11[天文地球—矿床学]