核磁共振测井TDA识别油气的影响因素

波谱学杂志 ›› 2012, Vol. 29 ›› Issue (1): 21-31.

• 低场磁共振技术与应用专栏 • 上一篇下一篇

核磁共振测井TDA识别油气的影响因素

李洋，肖立志*，孙华峰

油气资源与探测国家重点实验室，中国石油大学（北京），北京102249

收稿日期:2011-04-02 修回日期:2011-05-08 出版日期:2012-03-05 发布日期:2012-03-05
基金资助:
国家自然科学基金资助项目（41074102），科技部国际合作资助项目(2009DFA61030).

Analyses of Influencing Factors of Hydrocarbon Identification Using NMR Time Domain Analysis

LI Yang, XIAO Li-Zhi*, SUN Hua-Feng

State Key Laboratory of Petroleum Resource and Prospecting, China University of Petroleum, Beijing 102249, China

Received:2011-04-02 Revised:2011-05-08 Online:2012-03-05 Published:2012-03-05
Supported by:
国家自然科学基金资助项目（41074102），科技部国际合作资助项目(2009DFA61030).

摘要/Abstract

摘要：

TDA（时域分析）方法是核磁共振测井的主要方法之一，在判断储层流体类型、性质和孔隙度计算方面有很大的优势，但在应用中却存在一定的局限性. 针对TDA方法在流体识别中存在的一些问题，通过数值模拟不同条件的地层对其在油气识别中的影响因素及适用性进行分析. 研究结果表明：TDA主要用来识别轻烃，采用D9TW采集模式采集核磁自旋回波串，TDA能识别的轻质油粘度<9 mPa.s；长极化时间不变，短极化时间T_WS提高到2 s，TDA能识别的轻质油粘度<4 mPa.s. 双T_W回波串的差（差值信号，转换为孔隙度单位称为差分孔隙度）与地层孔隙度、含烃饱和度、含氢指数、极化函数等影响因素正相关. 对于低信噪比的核磁数据，综合各影响因素，发现烃的差分孔隙度要>1.5 p.u.，TDA方法才能有效识别油气和计算孔隙度.

关键词: 核磁共振测井, TDA, 油气识别, 影响因素

Abstract:

Time-domain analysis (TDA) is one of the most important NMR methods used in fluid identification and porosity calculation. It shows great advantages in reservoir evaluation, but there are also certain limitations. In order to investigate the adaptability of TDA in hydrocarbon identification under different reservoir conditions, numerical simulation was used in this study to analyze the factors influencing the outcomes of TDA, including longitudinal relaxation time T₁, polarization time T_W, porosity, hydrocarbon saturation, hydrogen index HI and polarization function. It is concluded that when acquisition mode D9TW is chosen, the viscosity of oil that can be measured by TDA is less than 9 mPa.s. After changing the short waiting time up to 2 s while keeping the long waiting time constant, the minimal viscosity reduces to less than 4 mPa.s. We also found the intensity of differential signals correlated positively with all the influencing factors mentioned above. With real low SNR NMR data, TDA can effectively identify hydrocarbon and calculate porosity only under the conditions that the differential porosities of hydrocarbon are greater than 1.5 p.u.

Key words: NMR logging, TDA, hydrocarbon identification, influencing factors

中图分类号:

P631.8

李洋, 肖立志, 孙华峰. 核磁共振测井TDA识别油气的影响因素[J]. 波谱学杂志, 2012, 29(1): 21-31.

LI Yang, XIAO Li-Zhi, SUN Hua-Feng. Analyses of Influencing Factors of Hydrocarbon Identification Using NMR Time Domain Analysis[J]. Chinese Journal of Magnetic Resonance, 2012, 29(1): 21-31.

参考文献

[1] Akkurt R, Vinegar H J, Tutunjian P N, et al. NMR logging of natural gas reservoirs[C]. 36^th Annual SPWLA Logging Symposium Transactions, 1995.

[2] Prammer M G, Mardon D, Coates G R, et al. Lithology-independent gas detection by gradient-NMR logging[C]. SPE Annual Technical Conference and Exhibition Proceedings, 1995. 

[3] Akkurt R, Prammer M, Moore A. Selection of optimal acquisition parameters for MRIL logs[C]. 37^thAnnual SPWLA Logging Symposium Transactions, 13p.Later Published in 1996 in The Log Analyst, 1996.

[4] Liu Jia-jun(刘家军). NMR logging fluid typing method and numerical simulation(核磁共振测井流体识别方法及其数值模拟)[D]. Beijing(北京)：China University of Petroleum, Beijing(中国石油大学,北京)，2008.

[5] Xiao Li-zhi(肖立志). NMR Imaging Logging and Rock NMR and Its Application(核磁共振成像测井与岩石核磁共振及其应用)[M]. Beijing(北京): Science Press(科学出版社), 1998.

[6] Coates G R, Xiao L Z, Prammer M G. NMR Logging Principles and Applications[M]. Texas: Gulf Publishing Company, 1999.

[7] Gong Guo-bo(龚国波), Sun Bo-qin(孙伯勤), Liu Mai-li(刘买利)，et al. NMR relaxation of the fluid in rock porous media(岩心孔隙介质中流体的核磁共振弛豫)[J]. Chinese J Magn Reson(波谱学杂志), 2006, 23(3): 379-395.

[8] Sun Hua-feng(孙华峰), Tao Guo(陶果), Zhou Yan-min(周艳敏), et al. The evaluative roles of WFT in formation and reservoir evaluations(电缆地层测试技术的发展及其在地层和油藏评价中的角色演变)[J]. Well Logging Technology(测井技术), 2010, 34(4): 314-322.

[9] Hu Hai-tao(胡海涛), Xiao Li-zhi(肖立志), Wu Xi-ling(吴锡令). A method for evaluating the performance of NMR logging device(一种评价核磁共振测井仪探测特性的方法)[J]. Chinese J Magn Reson(波谱学杂志), 2011, 28 (1) : 76-83.

[10] Li Xin(李新), Xiao Li-zhi(肖立志), Hu Hai-tao(胡海涛). Characteristics of NMR logging while drilling tools(随钻核磁共振测井仪探测特性研究)[J]. Chinese J Magn Reson(波谱学杂志), 2011, 28(1): 84-92.

[11] Zhang Q, Lo S W, Huang C C. et al. Some exceptions to default NMR rock and fluid properties[C]. 39^th Annual SPWLA Logging Symposium Transactions, 1998.

[12] Morriss, C.E. Hydrocarbon saturation and viscosity estimation from NMR logging in the Belridge Diatomite[J]. The Log Analyst, 1997.

[13] Chen S H, Olima O, Rivadavia C, et al. Estimation of hydrocarbon viscosity with multiple T_E dual waittime MRIL logs[C]. SPE Annual Technical Conference and Exhibition Proceedings, 1998.

[14] Hou B L, Coates G R. Nuclear magnetic resonance logging methods for fluid typing[C]. SPE Annual International Conference and Exhibition Proceedings, 1998.

核磁共振测井TDA识别油气的影响因素

Analyses of Influencing Factors of Hydrocarbon Identification Using NMR Time Domain Analysis

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 9

编辑推荐

Metrics

本文评价

[1]	崔帅帅, 何宗斌, 张宫, 高颖, 林佳敏, 曹文倩. 基于C#的二维核磁共振测井观测模式设计软件的开发[J]. 波谱学杂志, 2019, 36(1): 34-44.
[2]	张世懋, 张哨楠, 葛祥, 吴见萌. 川西致密气藏二维核磁共振测井优化设计与应用[J]. 波谱学杂志, 2018, 35(2): 234-242.
[3]	宋公仆，范伟，张嘉伟，薛志波，吴磊*. 核磁共振测井受激回波校正方法研究[J]. 波谱学杂志, 2013, 30(1): 103-112.
[4]	于慧俊, 肖立志, V. Anferov, S. Anferova, 朱万里, 刘化冰, 郭葆鑫. 基于FPGA的核磁共振测井仪控制逻辑设计[J]. 波谱学杂志, 2012, 29(2): 201-208.
[5]	胡海涛, 肖立志, 吴锡令. 一种评价核磁共振测井仪探测特性的方法[J]. 波谱学杂志, 2011, 28(1): 76-83.
[6]	李新, 肖立志, 胡海涛. 随钻核磁共振测井仪探测特性研究[J]. 波谱学杂志, 2011, 28(1): 84-92.
[7]	胡海涛, 肖立志. 电缆核磁共振测井仪探测特性研究[J]. 波谱学杂志, 2010, 27(4): 572-583.
[8]	孙伯勤, 邓克俊. 核磁自旋回波串的液体分量分解快速反演法[J]. 波谱学杂志, 2010, 27(3): 298-309.
[9]	车文华，张一鸣，夏平畴. 快速核磁共振测井实现方法的研究[J]. 波谱学杂志, 2001, 18(1): 73-78.