吉林大学学报(地球科学版) ›› 2017, Vol. 47 ›› Issue (2): 606-615.doi: 10.13278/j.cnki.jjuese.201702304

• 地球探测与信息技术 • 上一篇    下一篇

基于岩石物理模型的页岩孔隙结构反演及横波速度预测

逄硕1, 刘财1, 郭智奇1, 刘喜武2, 霍志周2, 刘宇巍2   

  1. 1. 吉林大学地球探测科学与技术学院, 长春 130026;
    2. 中国石油化工股份有限公司石油勘探开发研究院, 北京 100083
  • 收稿日期:2016-07-21 出版日期:2017-03-26 发布日期:2017-03-26
  • 通讯作者: 刘财(1963),男,教授,博士生导师,主要从事地震波场正反演理论、综合地球物理研究等工作,E-mail:liucai@jlu.edu.cn E-mail:liucai@jlu.edu.cn
  • 作者简介:逄硕(1991),女,博士研究生,主要从事地震岩石物理研究等工作,E-mail:angelpsh@163.com
  • 基金资助:
    国家自然科学基金重点项目(41430322);国家自然科学基金青年科学基金项目(41404090)

Estimation of Pore-Shape and Shear Wave Velocity Based on Rock-Physics Modelling in Shale

Pang Shuo1, Liu Cai1, Guo Zhiqi1, Liu Xiwu2, Huo Zhizhou2, Liu Yuwei2   

  1. 1. College of GeoExploration Science and Technology, Jilin University, Changchun 130026, China;
    2. Petroleum Exploration and Production Research Institute, Sinopec, Beijing 100083, China
  • Received:2016-07-21 Online:2017-03-26 Published:2017-03-26
  • Supported by:
    Supported by the Key Program of the National Natural Science Foundation of China (41430322) and the Youth Science Fund of the National Natural Science Foundation of China (41404090)

摘要: 准确预测储层的等效孔隙纵横比对页岩储层岩石物理建模及横波速度预测具有重要意义。为分析页岩储层孔隙纵横比及预测横波速度,提出了基于岩石物理模型的页岩孔隙纵横比反演及横波速度预测方法。本文首先通过岩石物理模型建立岩石的纵、横波速度与孔隙纵横比、孔隙度和矿物组分等参数之间的定量关系,寻找最佳孔隙纵横比;然后通过使理论预测与实际测量的纵波速度之间误差达到最小的方式反演孔隙纵横比,并以此为约束预测横波速度。实际测井数据反演结果表明,龙马溪组页岩地层的孔隙纵横比稳定,而围岩的孔隙纵横比变化范围较大;说明与围岩相比,页岩的孔隙结构更为稳定。同时,预测得到的页岩横波速度与实测横波速度的误差较小,另外对于缺少矿物组分资料的页岩层段,用平均矿物组分预测得到的横波速度误差仍较小;说明与矿物组分相比,龙马溪组页岩的纵、横波速度对孔隙纵横比参数更敏感。综上所述,利用该方法可预测到较为准确的等效孔隙纵横比和横波速度。

关键词: 页岩, 岩石物理模型, 孔隙纵横比, 横波速度预测

Abstract: Accurate estimation of effective pore aspect ratio for shale reservoir is significant in rock-physics modeling and shear-wave velocity prediction. In order to estimate pore structure and S-wave velocity, a rock-physics-based method is proposed for effective pore aspect ratio and shear-wave velocity prediction in shale. We build a quantitative relationship among P-wave velocity, S-wave velocity, pore aspect ratio, porosity and mineral compositions through rock-physics model. Then, through finding the best estimation of pore aspect ratio by minimizing the error between theoretical predictions and field measurements, we invert the effective pore aspect ratio and the shear wave is predicted with this constraint. The inversion results of the well logging data show that the aspect ratio remains stable in Longmaxi shale formation, while the aspect ratio of the surrounding rock varies in wide range. It indicates that the micro-structure in shale is more stable than in surrounding rock. The error between the predicted and measured shear wave velocities is small. In addition, for shale formation lacking mineral components data, the error in prediction of shear wave velocity calculated by average mineral compositions is still small. This shows that compared with mineral compositions, Longmaxi shale is more sensitive to pore aspect ratio. In conclusion, the effective pore aspect ratio and shear-wave velocity can be predicted accurately by the method proposed in this study.

Key words: shale, rock-physics model, pore aspect ratio, prediction of shear wave velocity

中图分类号: 

  • P631.4
[1] 李志明, 芮晓庆, 黎茂稳, 等. 北美典型混合页岩油系统特征及其启示[J]. 吉林大学学报(地球科学版), 2015, 45(4):1060-1072. Li Zhiming, Rui Xiaoqing, Li Maowen, et al. Characteristics of Typical Hybrid Shale-Oil System in North America and Its Implications[J]. Journal of Jilin University (Earth Science Edition), 2015, 45(4):1060-1072.
[2] 楚泽涵, 陈丰, 刘祝萍,等. 估算地层横波速度的新方法[J]. 测井技术,1995,19(5):313-318. Chu Zehan, Chen Feng, Liu Zhuping, et al. Estimation of Formation vS[J]. Well Logging Technology, 1995, 19(5):313-318.
[3] Castagna J P, Batzle M L, Eastwood R L. Relation-ships Between Compressional-Wave and Shear-Wave Velocities in Clastic Silicate Rocks[J]. Geophysics, 1985, 50(4):571-581.
[4] Han D H, Nur A, Morgan D. Effects of Porosity and Clay Content on Wave Velocities[J]. Geophysics, 1986, 51(11):2093-2107.
[5] Greenberg M L, Castagna J P. Shear-Wave Velocity Estimation in Porous Rocks:Theoretical Formulation, Preliminary Verification and Applications[J]. Geophysical Prospecting, 1982, 40(2):195-209.
[6] Xu S, White R E. A Physical Model for Shear-Wave Velocity Prediction[J]. Geophysical Prospecting, 1996, 44(4):687-717.
[7] Kuster G T, ToksÖz M N. Velocity and Attenuation of Seismic Waves in Two-Phase Media:Part Ι:Theoretical Formulations[J]. Geophysics, 1974, 39(5):587-606.
[8] Chen C H, ToksÖz M N. Inversion of Seismic Velo-cities for Pore Aspect Ratio Spectrum of a Rock[J]. Journal of Geophysical Research, 1979, 84(B13):7533-7543.
[9] 白俊雨,宋志翔,苏凌,等. 基于Xu-White模型横波速度预测的误差分析[J]. 地球物理学报,2012,55(2):589-595. Bai Junyu, Song Zhixiang, Su Ling, et al. Error Analysis of Shear-Velocity Prediction by the Xu-White Model[J]. Chinese Journal of Geophysics, 2012, 55(2):589-595.
[10] 刘欣欣,印兴耀,张峰. 一种碳酸盐岩储层横波速度估算方法[J]. 中国石油大学学报(自然科学版),2013,37(1):42-49. Liu Xinxin, Yin Xingyao, Zhang Feng. S-Wave Velocity Estimation Mehod in Carbonate Reservoir[J]. Journal of China University of Petroleum (Nature Science Edition), 2013, 37(1):42-49.
[11] 张广智,陈怀震,王琪,等. 基于碳酸盐岩裂缝岩石物理模型的横波速度和各向异性参数预测[J]. 地球物理学报,2013,56(5):1707-1715. Zhang Guangzhi, Chen Huaizhen, Wang Qi, et al. Estimation of S-Wave Velocity and Anisotropic Parameters Using Fractured Carbonate Rock Physics Model[J]. Chinese Journal of Geophysics, 2013, 56(5):1707-1715.
[12] Pan J G, Wang H B, Li C, et al. Effect of Pore Structure on Seismic Rock-Physics Characteristics of Dense Carbonates[J]. Applied Geophysics, 2015, 12(1):1-10.
[13] 李宏兵,张佳佳,姚逢昌. 岩石的等效孔隙纵横比反演及其应用[J]. 地球物理学报,2013,56(2):608-615. Li Hongbing, Zhang Jiajia, Yao Fengchang. Inversion of Effective Pore Aspect Ratio for Porous Rocks and Its Applications[J].Chinese Journal of Geophysics, 2013, 56(2):608-615.
[14] 印兴耀,李龙.基于岩石物理模型的纵、横波速度反演方法[J]. 石油物探,2015,54(3):249-253. Yin Xingyao, Li Long. P-Wave and S-Wave Velocities Inversion Based on Rock Physics Model[J]. Geophysical Prospecting for Petroleum, 2015, 54(3):249-253.
[15] 胡起,陈小宏,李景叶. 基于各向异性岩石物理模型的页岩气储层横波速度预测[J]. 石油物探,2014,53(3):254-261. Hu Qi, Chen Xiaohong, Li Jingye. Shear Wave Velocity Prediction for Shale Gas Reservoirs Based on Anisotropic Rock Physics Model[J]. Geophysical Prospecting for Petroleum, 2014, 53(3):254-261.
[16] Berryman J G. Long-Wavelength Propagation in Com-posite Elastic Media[J]. The Journal of the Acoustical Society of America, 1980, 68(6):1809-1831.
[17] Wu T T. The Effect of Inclusion Shape on The Ela-stic Moduli of a Two-Phase Material. Int J Solids Structures, 1996, 2(1):1-8.
[18] Mavko G, Mukerji T, Dvorkin J. The Rock Physics Handbook[M]. 2nd ed. Cambridge:Cambridge University Press, 2009.
[19] Reuss A. Berechnung Der Fliessgrenze Von Misch-kristallen Auf Grund Der Plastizitätsbedingungen Für Einkristalle[J]. Zeitschrift Für Angewandte Mathematic Und Mechanik, 1929, 9(1):49-58.
[20] Carcione J M. A Model for Seismic Velocity and Attenuation in Petroleum Source Rocks[J]. Geophysics, 2000, 65(4):1080-1092.
[21] 邓继新,王欢,周浩,等.龙马溪组页岩微观结构、地震岩石物理特征与建模[J].地球物理学报,2015,58(6):2123-2136. Deng Jixin, Wang Huan, Zhou Hao, et al. Microtexture, Seismic Rock Physical Properties and Modeling of Longmaxi Formation Shale[J].Chinese Journal of Geophysics, 2015, 58(6):2123-2136.
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