页岩油储层核磁有效孔隙度起算时间的确定——以吉木萨尔凹陷二叠系芦草沟组页岩油储层为例

doi:10.11743/ogg20190310

摘要/Abstract

摘要： 准噶尔盆地吉木萨尔凹陷芦草沟组页岩油储层岩性细，孔喉结构复杂，常规测井评价方法难以准确计算有效孔隙度。为此，选取5种粘土类型共30块砂岩样品，分别测量了氦气孔隙度、不同状态下的核磁T₂谱、粘土类型以及含量。通过对配套实验数据的分析，明确了粘土类型对储层核磁T₂信号短横向弛豫分量的影响机制。在此基础上，结合实验测量结果以及不同类型粘土束缚水的核磁共振弛豫时间，利用迭代法实现了研究区页岩油储层有效孔隙度的准确计算，并确定起算核磁时间为1.7 ms。该方法的计算结果得到了岩心分析数据以及实际测井资料的验证，应用效果较好，为页岩油储层有效孔隙度评价提供了一种新的技术思路和解决办法。

关键词: 核磁共振测井, 粘土矿物, 有效孔隙度, 页岩油, 芦草沟组, 二叠系, 吉木萨尔凹陷, 准噶尔盆地

Abstract: Due to the fine-grained lithology and complex pore throat structure of the Lucaogou shale oil reservoir in Jimusaer sag,Junggar Basin,it is difficult to accurately calculate the effective porosity by conventional logging interpretation methods.To solve this difficulty,30 sandstone samples of five clay types were selected for measurements such as porosity under helium expansion,nuclear magnetic resonance (NMR) T₂ spectrum under different conditions,type and content of clay.The mechanism of clay type effect on short lateral relaxation component of reservoir NMR T₂ signal was revealed through the analysis of matching experimental data.Subsequently,combined with the experimental results and the NMR relaxation time of bound water in various clay types,the effective porosity of shale oil reservoirs in the study area was calculated accurately by iteration method.The initial NMR time was determined to be 1.7 ms,which have been verified well by core analysis and actual logging.The study serves as a new technical solution for effective porosity evaluation of shale oil reservoir.

Key words: NMR logging, clay mineral, effective porosity, shale oil, Lucaogou Formation, Permian, Jimusaer sag, Junggar Basin

中图分类号:

TE121.2

王伟,赵延伟,毛锐,等. 页岩油储层核磁有效孔隙度起算时间的确定——以吉木萨尔凹陷二叠系芦草沟组页岩油储层为例[J]. 石油与天然气地质, 2019, 40(3): 550-557. doi: 10.11743/ogg20190310 Wang Wei,Zhao Yanwei,Mao Rui,et al. Determination of the starting time for measurement of NMR effective porosity in shale oil reservoir: A case study of the Permian Lucaogou shale oil reservoir,Jimusaer sag[J]. Oil & Gas Geology, 2019, 40(3): 550-557. doi: 10.11743/ogg20190310

参考文献

[1] 丁娱娇,邵维志,常静春,等.过渡岩类致密储层特征及测井评价[J].测井技术,2016,40(3):331-338. Ding Yujiao,Shao Weizhi,Chang Jingchun,et al.Transitional rock tight reservoir characteristics and log evaluation[J].Well logging technology,2016,40(3):331-338.
[2] 张琦斌,郭智奇,刘财,等.针对有机质微观特性的页岩储层岩石物理建模及应用[J].地球物理学进展,2018,33(5):2083-2091. Zhang Qinbin,Guo Zhiqi,Liu Cai,et al.Rock physics model and its applications in the Longmaxi shale based on the quantification of microstructural properties of organic matter[J].Progress in Geophysi-cs,2018,33(5):2083-2091.
[3] 李超,张立宽,罗晓容,等.泥岩压实研究中有机质导致声波时差异常的定量校正方法[J].中国石油大学学报(自然科学版),2016,40(3).:77-87. Li Chao,Zhang Likuang,Luo Xiaorong,et al.A quantitative method for revising abnormally high sonic data in rich-organic rock during compaction study[J].Journal of China University of Petroleum(Edition of Natural Science),2016,40(3):77-87.
[4] 张冲,郭聪,朱林奇,等.考虑有机质校正的页岩气储层总孔隙度测井评价方法[J].煤炭学报,2017(6):1527-1534. Zhang Chong,Guo Cong,Zhu Linqi,et al.A logging interpretation method for total porosity considering organic matter correction of shalegas reservoirs[J].Journal of China Coal Society,2017,42(6):1527-1534.
[5] 高衍武,赵延静,李国利,等.基于核磁和密度测井评价准噶尔盆地致密油烃源岩有机碳含量[J].油气藏评价与开发,2014(2):5-8. Gao Yanwu,Zhao Yanjing,Li Guoli,et al.Total organic carbon evalua-tion of tight oil source rocks in Junggar basin based on nuclear magnetic logging and density logging[J].Reservoir Evaluation and Development,2014(2):5-8.
[6] 吴勇,侯雨庭,李会庚,等.高精度地层元素测井在页岩油储层评价中的应用——以鄂尔多斯盆地长7段为例[J].非常规油气,2016,3(2):1-10. Wu Yong,Hou Yuting,Li Huigeng,et al.Application of high-precision formation elements logging to shale oil reservoir evaluation——A case study of Seventh Member of Yanchang Formation,Ordos Basin[J].Unconventional Oil & Gas,2016,3(2):1-10.
[7] 蔡德洋,章成广,信毅,等.利用元素俘获测井评价致密砂岩岩性及有效性[J].工程地球物理学报,2012,09(4):440-444. Cai Deyang,Zhang Chengguang,Xin Yi,et al.Using Elemental Capture Spectroscopy(ECS)logging to evaluate tght sandstone lithology and its effectiveness[J].Chinese Journal of Engineering Geophysics,2012,09(4):440-444.
[8] 张晋言.页岩油测井评价方法及其应用[J].地球物理学进展,2012,27(3):1154-1162. Zhang Jinyan.Well logging evaluation method of shale oil reservoirs and its applications[J].Progress in Geophysics,2012,27(3):1154-1162.
[9] 张笑,王殿生,安祥,等.致密油岩心孔隙度核磁共振实验测量的杂质信号处理方法[J].核电子学与探测技术,2015(4):411-416. Zhang Xiao,Wang Diansheng,An Xiang,et al.Methods of processing impurity signals on measuring porosity of cores from tight oil reservoir by NMR[J].Nuclear Electronics & Detection Technology,2015(4):411-416.
[10] Martin P,Dacy J.Effective Qv by NMR tests[C]//SPWLA 45th Annual Logging Symposium,2004.
[11] 成志刚,吴有彬,李戈理,等.核磁共振测井技术在致密油储层评价中的应用研究[J].测井技术,2016,40(6):719-725. Cheng Zhigang,Wu Youbin,Li Geli,et al.Application of NMR logging to the evaluation of Tight Oil Reservoirs[J].Well Logging Technology,2016,40(6):719-725.
[12] 宋永,周路,郭旭光,等.准噶尔盆地吉木萨尔凹陷芦草沟组湖相云质致密油储层特征与分布规律[J].岩石学报,2017,33(4):1159-1170. Song Yong,Zhou Lu,Guo Xuguang,et al.Characteristics and occurrence of lacustrine dolomitic tight-oil reservoir in the Middle Permian Lucaogou Formation,Jimusaer sag,southeastern Junggar Basin[J].Acta Petrologica Sinica,2017,33(4):1159-1170.
[13] Coates G R,Xiao L Z,Prammer M G.NMR logging principles and applications[M].Texas:Gulf Publishing Company,1999:20-60.
[14] 匡立春,孙中春,毛志强,等.核磁共振测井技术在准噶尔盆地油气勘探开发中的应用[M].北京:石油工业出版社,2015:51-59. Kuang Lichun,Sun Zhongchun,Mao Zhiqiang,et al.Application of NMR logging technology in oil and gas exploration and development in Junggar Basin[M]:Beijing:Petroleum Industry Press,2015:51-59.
[15] Straley C,Rossini D,Vinegar H,et al.Core analysis by low field NMR[C]//SCA Conference Paper,1994:9404.
[16] Freedman R,Boyd A,Gubelin G,et al.Measurement Of Total Nmr Porosity Adds New Value To Nmr Logging[C]//SPWLA 38th Annual Logging Symposium,1997.
[17] Martin P,Dacy J.Effective Qv by NMR tests[C]//SPWLA 45th Annual Logging Symposium,2004.
[18] 匡立春,胡文瑄,王绪龙,等.吉木萨尔凹陷芦草沟组致密油储层初步研究:岩性与孔隙特征分析[J].高校地质学报,2013(3):529-535. Kuang Lichun,Hu Wenxuan,Wang Xulong,et al.Research of the tight oil reservoir in the Lucaogou Formation in Jimusar Sag:Analysis of lithology and porosity characteristics[J].Geological Journal of China Universities,2013(3):529-535.
[19] 匡立春,孙中春,欧阳敏,等.吉木萨尔凹陷芦草沟组复杂岩性致密油储层测井岩性识别[J].测井技术,2013,37(6):638-642. Kuang Lichun,Sun Zhongchun,Ouyang Min.et al.Complication lithology logging identification of the Lucaogou tight oil reservoir in Jimusaer Depression[J].Well Logging Technology,2013,37(6):638-642.
[20] 穆永利,陈建,张丽华,等.致密油储层测井评价及研究-以吉木萨尔凹陷芦草沟组为例[J].长江大学学报(自科版),2015,12(32):21-26. Mu Yongli,Chen Jian,Zhang Lihua,etal.Well logging evaluation and study of tight oil reservoirs-By taking Luocaogou Formation in Jimsar Depression for example[J].Journal of Yangtze University(Natural Science Edition),2015,12(32):21-26.
[21] 葸克来,操应长,朱如凯,等.吉木萨尔凹陷二叠系芦草沟组致密油储层岩石类型及特征[J].石油学报,2015,36(12):1495-1507. Xi Kelai,Cao Yingchang,Zhu Rukai,et al.Rock types and characteri-stics of tight oil reservoir in Permian LucaogouFormation,Jimsar sag[J].Acta PetroleiSinica,2015,36(12):1495-1507.
[22] 王振林,毛志强,孙中春,等.致密油储层孔隙结构核磁共振测井评价方法[J].断块油气田,2017,24(6):53-57. Wang Zhenlin,Mao Zhiqiang,Sun Zhongchun,et al.Evaluation of pore structure using NMR logs for tight oil reservoirs[J].Fault-Block Oil and Gas Field,2017,24(6):53-57.
[23] 赵培强,孙中春,罗兴平,等.致密油储层核磁共振测井响应机理研究[J].地球物理学报,2016,59(5):1927-1937. Zhao Peiqing,Sun Zhongchun,Luo Xingping,et al.Study on the response mechanisms of nuclear magnetic resonance(NMR) log in tight oil reservoirs[J].Chinese Journal of Geophysics,2016,59(5):1927-1937.
[24] Prammer M G,Drack E D,Bouton J C,et al.Measurements of clay-bound water and total porosity by magnetic resonance Logging[J].Log Analyst,1996,37(6):61-97.
[25] 毛志强,张冲,肖亮.一种基于核磁共振测井计算低孔低渗气层孔隙度的新方法[J].石油地球物理勘探,2010,45(1):105-109. Mao Zhiqiang,Zhang Chong,Xiao Liang.A NMR-based porosity calculation method for low porosity and low permeability gas reservoir[J].Oil Geophysical Prospecting,2010,45(1):105-109.
[26] 谢然红,肖立志,邓克俊.核磁共振测井孔隙度观测模式与处理方法研究[J].地球物理学报,2006,49(5):1567-1572. Xie Ranhong,Xiao Lizhi,Deng Kejun.NMR logging porosity activation and data processing method[J].Chinese Journal of Geophysics,2006,49(5):1567-1572.