四川盆地焦石坝地区页岩气储层孔隙参数测井评价方法

舒志国; 关红梅; 喻璐; 柳筠

doi:10.11781/sysydz201801038

四川盆地焦石坝地区页岩气储层孔隙参数测井评价方法

doi: 10.11781/sysydz201801038

1.
中国石化江汉油田分公司, 湖北潜江 433124
2. 中国石化江汉油田分公司勘探开发研究院, 武汉 430223

基金项目: 国家科技重大专项（2016ZX05060）和中国石化科技项目（P17014-3）资助。

详细信息

作者简介:
舒志国(1962-),男,研究员,从事油气勘探开发与科技管理。E-mail:1157664151@qq.com。

中图分类号: TE132.2
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出版历程
- 收稿日期: 2017-10-13
- 修回日期: 2017-12-08
- 刊出日期: 2018-01-28

Well logging evaluation of pore parameters for shale gas reservoirs in Jiaoshiba area, Sichuan Basin

1.
SINOPEC Jianghan Oilfield Company, Qianjiang, Hubei 433124, China
2. Research Institute of Petroleum Exploration and Development, SINOPEC Jianghan Oilfield Company, Wuhan, Hubei 430223, China

摘要

摘要: 四川盆地焦石坝地区页岩储层具有孔隙度低、孔隙结构复杂的特点，五峰-龙马溪组页岩储层段发育无机孔隙、有机质孔隙和微裂缝3种孔隙类型，核磁共振测井作为岩石孔隙参数评价的一项有效技术，在该区储层孔隙度和孔隙结构的评价中发挥了重要作用。基于岩心刻度测井解释的方法，通过对常规测井资料和岩心核磁共振实验数据的相关性研究，建立了焦石坝地区页岩储层的总孔隙度和有效孔隙度解释模型。总孔隙度解释模型是将岩心核磁实验的总孔隙度分析结果与测井资料进行最佳深度匹配后，根据最优化数学方法，确定多元线性回归法为最佳计算方法，即总孔隙度与密度测井、声波时差、补偿中子测井进行多元线性拟合；有效孔隙度解释模型是根据岩心核磁实验的有效孔隙度与密度测井具有较好的正相关性，建立根据密度测井求取有效孔隙度的关系式。孔隙度计算结果与岩心实测结果对比显示，91.7%的数据其绝对误差都小于0.5%，实现了对该区页岩储层孔隙参数的较好评价。
- 核磁共振测井 /
- 孔隙参数 /
- 页岩气 /
- 储层 /
- 焦石坝地区 /
- 四川盆地
Abstract: The shale reservoirs in the Jiaoshiba area of Sichuan Basin have the characteristics of low porosity and complex pore structure. Inorganic and organic pores, and micro cracks developed in the shale reservoirs in the Wufeng and Longmaxi formations. NMR logging played an important role in evaluating the porosity and pore structure of shale reservoirs in the study area. Based on core scale logging interpretation, we correlated conventional logging data with core NMR data, and established a total porosity and effective porosity interpretation model for shale reservoirs in the Jiaoshiba area. The total porosity interpretation model was based on the optimal matching between the total porosity analysis results of core NMR experiments and logging data. The optimization indicates that the multiple linear regression method is the best, that is, the total porosity and density logging, sonic time difference and compensated neutron logging provide multivariate linear fitting. The effective porosity interpretation model was based on the positive correlation between effective porosity and density logging of core NMR experiments, and the effective porosity could be calculated by density logging. Comparisons between the calculated results of porosity and core measurements showed that the absolute errors of 91.7% of the data were <0.5%, indicating a high quality evaluation of the pore parameters of shale reservoirs in the study area.
- NMR logging /
- pore parameters /
- shale gas /
- reservoir /
- Jiaoshiba area /
- Sichuan Basin

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