APPLIED GEOPHYSICS
 
        首页  |  版权声明  |  期刊介绍  |  编 委 会  |  收录情况  |  期刊订阅  |  下载中心  |  联系我们  |  English
应用地球物理  2018, Vol. 15 Issue (3-4): 448-465    DOI: 10.1007/s11770-018-0695-4
论文 最新目录 | 下期目录 | 过刊浏览 | 高级检索 Previous Articles  |  Next Articles  
基于矢量化反射率法的多波叠前联合AVA反演
刘炜1,王彦春1,李景叶2,刘学清3,谢玮1
1. 中国地质大学(北京)地球物理与信息技术学院,北京 100083
2. 中国石油大学(北京)地球物理与信息工程学院,北京 102249
3. 北京京能油气资源开发有限公司,北京 100022
Prestack AVA joint inversion of PP and PS waves using the vectorized reflectivity method
Liu Wei1, Wang Yan-Chun1, Li Jing-Ye2, Liu Xue-Qing3, and Xie Wei1
1. School of Geophysics and Information Technology, China University of Geosciences, Beijing 100083, China.
2. College of Geophysics and Information Engineering, China University of Petroleum, Beijing 102249, China.
3. Beijing Energy Oil & Gas Resources Development Co. Ltd., Beijing 100022, China.
 全文: PDF (1946 KB)   HTML ( KB)   输出: BibTeX | EndNote (RIS)      背景资料
摘要 目前,大多数多波叠前联合AVA(AVO)反演方法都是基于精确Zoeppritz方程及其近似公式。然而,这些方程仅仅反映了反射振幅与入射角和界面两侧弹性参数之间的关系,没有考虑几何扩散、吸收衰减、透射损失、多次波和纵横波不匹配等传播效应,导致不能精确地描述地震波真实传播特征。传统的AVA反演方法通常需要在反演之前消除这些传播效应,而实际中很难满足此要求。在一维地质模型的假设条件下,反射率法可以模拟地震波全波场响应。基于此,本文提出了一种基于矢量化反射率法的非线性多波叠前联合AVA反演方法,其中引入了快速非支配排序遗传算法优化处理多目标函数从而获得纵、横波速度和密度等多个参数。因为该方法能在未引入权重系数的情况下同时优化多个目标函数,所以具有较强的鲁棒性。模型测试验证了该叠前联合AVA反演方法的有效性。结果显示:当透射损失和层间多次波等传播效应没有被很好校正时,基于反射率法的反演结果优于基于精确Zoeppritz方程的反演结果。
服务
把本文推荐给朋友
加入我的书架
加入引用管理器
E-mail Alert
RSS
作者相关文章
关键词反射率法   快速非支配排序遗传算法   多参数   叠前联合AVA反演     
Abstract: Most current prestack AVA joint inversion methods are based on the exact Zoeppritz equation and its various approximations. However, these equations only reflect the relation between reflection coefficients, incidence angles, and elastic parameters on either side of the interface, which means that wave-propagation effects, such as spherical spreading, attenuation, transmission loss, multiples, and event mismatching of P- and S-waves, are not considered and cannot accurately describe the true propagation characteristics of seismic waves. Conventional AVA inversion methods require that these wave-propagation effects have been fully corrected or attenuated before inversion but these requirements can hardly be satisfied in practice. Using a one-dimensional (1D) earth model, the reflectivity method can simulate the full wavefield response of seismic waves. Therefore, we propose a nonlinear multicomponent prestack AVA joint inversion method based on the vectorized reflectivity method, which uses a fast nondominated sorting genetic algorithm (NSGA II) to optimize the nonlinear multiobjective function to estimate multiple parameters, such as P- wave velocity, S-wave velocity, and density. This approach is robust because it can simultaneously cope with more than one objective function without introducing weight coefficients. Model tests prove the effectiveness of the proposed inversion method. Based on the inversion results, we find that the nonlinear prestack AVA joint inversion using the reflectivity method yields more accurate inversion results than the inversion by using the exact Zoeppritz equation when the wave-propagation effects of transmission loss and internal multiples are not completely corrected.
Key wordsReflectivity method   fast nondominated sorting genetic algorithm   multiple parameters   prestack AVA joint inversion   
收稿日期: 2018-04-25;
基金资助:

本研究由国家科技重大专项(编号:2016ZX05003-003)资助。

引用本文:   
. 基于矢量化反射率法的多波叠前联合AVA反演[J]. 应用地球物理, 2018, 15(3-4): 448-465.
. Prestack AVA joint inversion of PP and PS waves using the vectorized reflectivity method[J]. APPLIED GEOPHYSICS, 2018, 15(3-4): 448-465.
 
[1] Aki, K., and Richards, P. G., 1980, Quantitative seismology: Theory and Methods: W. H. Freeman and Co., San Francisco America.
[2] Alkhalifah, T., 1997, Velocity analysis using nonhyperbolic moveout in transversely isotropic media: Geophysics, 62(6), 1839-1854.
[3] Castagna, J. P., 1991, Petrophysical imaging using AVO: The Leading Edge, 12(3), 172-178.
[4] Deb, K., 2000, An efficient constraint handling method for genetic algorithm: Computer Methods in Applied Mechanics and Engineering, 186, 311-338.
[5] Deb, K., and Agrawal, R. B., 1995, Simulated binary crossover for continuous search space: Complex Systems, 9, 115-148.
[6] Deb, K., and Agrawal, S., 1999, A niched-penalty approach for constraint handling in genetic algorithms: International Conference on Artificial Neural Networks and Genetic Algorithms, 235−243.
[7] Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T., 2002, A fast and elitist multi-objective genetic algorithm: NSGA-II: IEEE Transactions on Evolutionary Computation, 6(2), 182-197.
[8] Debski, W., and Tarantola, A., 1995, Information on elastic parameters obtained from the amplitudes of reflected waves: Geophysics, 60(5), 1426-1436.
[9] Fatti, J. L., Smith, G. C., Vail, P. J., Strauss, P. J., and Levitt, P. R., 1994, Detection of gas in sandstone reservoirs using AVO analysis: A 3-D seismic case history using the geostack technique: Geophysics, 59(9), 1362-1376.
[10] Fryer, G. J., 1980, A slowness approach to the reflectivity method of seismogram synthesis: Geophysical Journal International, 63(3), 747-758.
[11] Fryer, G. J., and Frazer, L. N., 1984, Seismic waves in stratified anisotropic media: Geophysical Journal of the Royal Astronomical Society, 78(3), 691-710.
[12] Fuchs, K., and Müller, G., 1971, Computation of synthetic seismograms with the reflectivity method and comparison with observations: Geophysical Journal International, 23(4), 417-433.
[13] Gardner, G. H. F., Gardner, L.W., and Gregory, A. R., 1974, Formation velocity and density-the diagnostic basis for stratigraphic traps: Geophysics, 39(6), 770-780.
[14] Goldberg, D. E., 1989, Genetic algorithms in search, optimization and machine learning: Addison-Wesley.
[15] Gouveia, W. P., and Scales, J. A., 1998, Bayesian seismic waveform inversion: Parameter estimation and uncertainty analysis: Journal of Geophysical Research, 103, 2759-2779.
[16] Gray, F. D., and Andersen, E., 2000, The application of AVO and inversion to the estimation of rock properties: 70th Annual International Meeting, SEG, Expanded Abstracts, 549-552.
[17] Heyburn, R., and Fox, B., 2010, Multi-objective analysis of body and surface waves from the Market Rasen (UK) earthquake: Geophysical Journal International, 181, 532-544.
[18] Jin, S., 1999, Characterizing reservoir by using jointly P- and S- wave AVO analysis: 69th Annual International Meeting, SEG, Expanded Abstracts, 687-690.
[19] Kennett, B. L. N., 1983, Seismic wave propagation in stratified media: Cambridge University Press, UK.
[20] Kozlovskaya, E., Vecsey, L., Plomerova, J., and Raita, T., 2007, Joint inversion of multiple data types with the use of multiobjective optimization: problem formulation and application to the seismic anisotropy investigations: Geophysical Journal International, 171(2), 761-779.
[21] Larsen, J. A., 1999, AVO inversion by simultaneous P-P and P-S inversion: M.S. thesis, University of Calgary.
[22] Li, T., and Mallick, S., 2015, Multicomponent, multi-azimuth prestack seismic waveform inversion for azimuthally anisotropic media using a parallel and computationally efficient non-dominated sorting genetic algorithm: Geophysical Journal International, 200(2), 1134-1152.
[23] Liu, H. X., Li, J. Y., Chen, X. H., Hou, B., and Chen, L., 2016, Amplitude variation with offset inversion using the reflectivity method: Geophysics, 81(4), R185−R195.
[24] Lu, J., Yang, Z., Wang, Y., and Shi, Y., 2015, Joint PP and PS AVA seismic inversion using exact Zoeppritz equations: Geophysics, 80(5), R239-R250.
[25] Mahmoudian, F., and Margrave, G. F., 2004, Three parameter AVO inversion with PP and PS data using offset binning: SEG Technical Program Expanded Abstracts, 240-243.
[26] Mallick, S., 1999, Some practical aspects of prestack waveform inversion using a genetic algorithm: An example from the east Texas Woodbine gas sand: Geophysics, 64(2), 326-336.
[27] Mallick, S., and Frazer, L. N., 1987, Practical aspects of reflectivity modeling: Geophysics, 52(10), 1355-1364.
[28] Mukherji, A., Sen, M. K., and Stoffa, P. L., 2005, Travel time computation and prestack time migration in transversely isotropic media: Journal of Seismic Exploration, 13(3), 201-226.
[29] Müller, G., 1985, The reflectivity method: A tutorial: Journal of Geophysics, 58, 153-174.
[30] Ostrander, W. J., 1984, Plane-wave reflection coefficients for gas sands at non-normal angles of incidence: Geophysics, 49(10), 1637-1648.
[31] Padhi, A., and Mallick, S., 2013, Accurate estimation of density from the inversion of multicomponent prestack seismic waveform data using a nondominated sorting genetic algorithm: The Leading Edge, 32(1), 94-98.
[32] Padhi, A., and Mallick, S., 2014, Multicomponent prestack seismic waveform inversion in transversely isotropic media using a non-dominated sorting genetic algorithm: Geophysical Journal International, 196(3), 1600-1618.
[33] Phinney, R. A., Odom, R. I., and Fryer, G. J., 1987, Rapid generation of synthetic seismograms in layered media by vectorization of the algorithm: Bulletin of the Seismological Society of America, 77, 2218-2226.
[34] Sen, M. K., and Mukherji, A., 2003, τ-p analysis in transversely isotropic media: Geophysical Journal International, 154(3), 647-658.
[35] Sen, M. K., and Roy, I. G., 2003, Computation of differential seismograms and iteration adaptive regularization in prestack waveform inversion: Geophysics, 68(6), 2026-2039.
[36] Shuey, R. T., 1985, A simplification of the Zoeppritz equations: Geophysics, 50(4), 609-614.
[37] Singh, V. P., Duquet, B., Léger, M., and Schoenauer, M., 2008, Automatic wave-equation migration velocity inversion using multi-objective evolutionary algorithms: Geophysics, 73(5), VE61-VE73.
[38] Stewart, R. R., 1990, Joint P and P-SV inversion: CREWES, Research Report 2.
[39] Ti?rek, S., Slob, E. C., Dillen, M. W. P., Cloetingh, S. A. P. L., and Fokkema, J. T., 2005, Linking dynamic elastic parameters to static state of stress: Toward an integrated approach to subsurface stress analysis: Tectonophysics, 397, 167-179.
[40] Virieux, J., and Operto, S., 2009, An overview of full waveform inversion in exploration geophysics: Geophysics, 74(6), WCC1-WCC26.
[41] Wang, Y. M., Wang, X. P., Meng, X. J., and Niu, X. M., 2011, Prestack inversion of wide incident angle seismic data: 81th Annual International Meeting, SEG, Expanded Abstracts, 2507-2511.
[42] Zhao, H. S., Ursin, B., and Amundsen, L., 1994, Frequency-wavenumber elastic inversion of marine seismic data: Geophysics, 59(12), 1868-1881.
[43] Zheng, X. D., 1991, Approximation of Zoeppritz equation and its application: Oil Geophysical Prospecting (in Chinese), 26(2), 129-144.
[44] Zhi, L. X., Chen, S. Q., and Li, X. Y., 2013, Joint AVO inversion of PP and PS waves using exact Zoeppritz equation: 83th Annual International Meeting, SEG, Expanded Abstracts, 457-461.
[45] Zhi, L. X., Chen, S. Q., Li, X. Y., and Zhang, W. L., 2015, An improved strategy for exact Zoeppritz equations AVA inversion: 85th Annual International Meeting, SEG, Expanded Abstracts, 654-658.
[1] 曲英铭,黄崇棚,刘畅,周昌,李振春,吾拉力. 基于海底电缆数据的声弹耦合介质多参数最小二乘逆时偏移*[J]. 应用地球物理, 2019, 16(3): 327-337.
版权所有 © 2011 应用地球物理
技术支持 北京玛格泰克科技发展有限公司