天然气勘探

烃源岩TOC测井评价方法及应用——以珠江口盆地文昌组为例

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  • 中海石油(中国)有限公司深圳分公司研究院,广东 深圳 518054
王清辉(1986-),男,湖北咸宁人,工程师,硕士,主要从事珠江口盆地(东部)地区测井评价研究.E-mail:wangqh24@cnooc.com.cn.

收稿日期: 2017-08-28

  修回日期: 2017-11-22

  网络出版日期: 2018-02-10

基金资助

“十三五”国家重大科技专项课题“南海东部海域勘探新领域及关键技术”(编号:2016ZX05024-004)资助.

The TOClogging evaluation methods and application of source rock:A case study of Wenchang Formation in Pearl River Mouth Basin

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    (Research Institute of CNOOC Shenzhen Branch,Shenzhen 518054,China)

Received date: 2017-08-28

  Revised date: 2017-11-22

  Online published: 2018-02-10

摘要

利用纵向高分辨率的测井信息评价烃源岩的总有机碳含量(TOC),弥补了利用有限地球化学分析数据表征烃源岩有机质丰度分布特征的不足,为珠江口盆地资源量计算和油气勘探决策提供依据。通过分析岩心总有机碳含量与对应的测井响应参数之间的关系,建立总有机碳含量预测的多参数回归模型、核磁共振与密度孔隙度差异模型和多矿物反演模型。运用以上3种模型对研究区内6口井文昌组烃源岩的总有机碳含量进行预测,预测结果与地球化学分析数据具有良好的一致性,相对误差平均值小于20%。对比分析表明核磁共振与密度孔隙度差异模型的精度最高,具有较好的应用前景。

本文引用格式

王清辉,冯进 . 烃源岩TOC测井评价方法及应用——以珠江口盆地文昌组为例[J]. 天然气地球科学, 2018 , 29(2) : 251 -258 . DOI: 10.11764/j.issn.1672-1926.2017.11.020

Abstract

The total organic carbon content (TOC) of the source rock is evaluated by longitudinal high-resolution logging information,which makes up the deficiency of the distribution of organic matter abundance in the source rock by finite geochemical analytical data.This method can provide a basis for the calculation of the amount of resources and the oil and gas exploration decision in the Pearl River Mouth Basin.Based on the analysis of total organic carbon content (TOC) and corresponding logging response parameters,the multi-parameter regression model,the differentiation porosity between nuclear magnetic resonance and density model and multi-mineral reaction model of total organic carbon content prediction were established.Using the above three models,the total organic carbon content of the six source wells of Wenchang Formation in the study area is predicted.The prediction results are in good agreement with the geochemical analytical data,and the average relative error is less than 20%.The comparison shows that the accuracy of the differentiation porosity between nuclear magnetic resonance and density model is the highest,and it has a good application prospect.
 

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