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Cheng Xianqiong, Jiang Kezhi. 2021: Inversion of crustal thickness in Chinese mainland based on deep denoising autoencoder neural network. Acta Seismologica Sinica, 43(1): 34-47. DOI: 10.11939/jass.20200043
Citation: Cheng Xianqiong, Jiang Kezhi. 2021: Inversion of crustal thickness in Chinese mainland based on deep denoising autoencoder neural network. Acta Seismologica Sinica, 43(1): 34-47. DOI: 10.11939/jass.20200043
shu

Inversion of crustal thickness in Chinese mainland based on deep denoising autoencoder neural network

  • 1.

    College of Geophysics，Chengdu University of Technology，Chengdu 610059，China

  • 2.

    College of Engineering Technology，Chengdu University of Technology，Sichuan Leshan 614000，China

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  • Received Date: March 30, 2020
  • Revised Date: July 27, 2020
  • Available Online: March 19, 2021
  • Published Date: January 14, 2021
    Graphical Abstract
    • Abstract
  • Chinese mainland is a composite continent composed of many micro-blocks, fold belts and orogenic belts after evolution over a long geological period. Chinese mainland crust is of complex crust-mantle structure, and crustal thickness is one of the most important parameters. At the same time, Rayleigh surface wave group velocity and phase velocity have strong constraints on the crust and upper mantle structure. In this paper, a data driven, named deep denoising autoencoder （DDAE） neural network is used to explore the relationship of forward and inversion between Rayleigh wave group velocity and phase velocity and crustal thickness, and we invert the crustal thickness of Chinese mainland by the latest dispersion model. In this paper, the evaluation of neural network architecture is put forward. In addition to the traditional test error and training error, it is compared with the result of network prediction with the forward process of the known physical principles. When designing the network architecture, the forward and inverse problems of the earth model and the surface wave dispersion are considered simultaneously, that is, the corresponding forward process is decoded, and the encoding process corresponds to the inversion process. At the same time, in view of the noise characteristics of the observed dispersion data, the training sample is polluted by noise, so the decoder decodes the noise-free input to denoising the observed data. After debugging, analyzing and optimizing the various parameters of the network, a robust neural network was finally obtained, and the crust thickness of the Chinese mainland was reproduced accordingly. The results of this study are in good agreement with the crustal thickness models obtained by different methods, suggesting that the deep denoising autoencoder neural network can well reveal the nonlinear relationship between surface wave dispersion and crustal thickness, and it is a feasible and credible method to solve the problem of surface wave dispersion inversion for crustal thickness.
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  • 郭良辉,孟小红,石磊,陈召曦. 2012. 优化滤波方法及其在中国大陆布格重力异常数据处理中的应用[J]. 地球物理学报,55(12):4078–4088.
    Guo L H,Meng X H,Shi L,Chen Z X. 2012. Preferential filtering method and its application to Bouguer gravity anomaly of Chinese continent[J]. Chinese Journal of Geophysics,55(12):4078–4088 (in Chinese).
    胡卫剑,郝天珧,秦静欣,李志伟,江为为,姜迪迪,邢健,胡立天,徐亚,雷受旻. 2014. 中国海陆莫霍面及深部地壳结构特征:以阿尔泰—巴士海峡剖面为例[J]. 地球物理学报,57(12):3932–3943.
    Hu W J,Hao T Y,Qin J X,Li Z W,Jiang W W,Jiang D D,Xing J,Hu L T,Xu Y,Lei S M. 2014. Moho depth and deep crustal structure in the land and seas of China and adjacent areas:An example of the Altay-Bashi Channel profile[J]. Chinese Journal of Geophysics,57(12):3932–3943 (in Chinese).
    黄建平,傅容珊,许萍,黄建华,郑勇. 2006. 利用重力和地形观测反演中国及邻区地壳厚度[J]. 地震学报,28(3):250–258.
    Huang J P,Fu R S,Xu P,Huang J H,Zheng Y. 2006. Inversion of gravity and topography data for the crust thickness of China and its adjacency[J]. Acta Seismologica Sinica,28(3):250–258 (in Chinese).
    林彬华,金星,陈惠芳,廖诗荣,黄玲珠,张燕明,巫立华. 2019. 基于反向传播神经网络的闽台ML震级偏差分析与修正[J]. 地震学报,41(6):723–734.
    Lin B H,Jin X,Chen H F,Liao S R,Huang L Z,Zhang Y M,Wu L H. 2019. Analysis and revision of magnitude ML deviation between Fujian and Taiwan based on BP neural network[J]. Acta Seismologica Sinica,41(6):723–734 (in Chinese).
    刘光鼎. 2007. 中国大陆构造格架的动力学演化[J]. 地学前缘,14(3):39–46.
    Liu G D. 2007. Geodynamical evolution and tectonic framework of China[J]. Earth Science Frontiers,14(3):39–46 (in Chinese). doi: 10.1016/S1872-5791(07)60021-9
    刘启民,赵俊猛,卢芳,刘宏兵. 2014. 用接收函数方法反演青藏高原东北缘地壳结构[J]. 中国科学:地球科学,44(4):668–679.
    Liu Q M,Zhao J M,Lu F,Liu H B. 2014. Crustal structure of northeastern margin of the Tibetan Plateau by receiver function inversion[J]. Science China Earth Sciences,57(4):741–750. doi: 10.1007/s11430-013-4772-5
    孙伟家,符力耘,魏伟,林羿,唐清雅. 2018. 中国东部地区的壳-幔过渡带结构[J]. 地球物理学报,61(3):845–855.
    Sun W J,Fu L Y,Wei W,Li Y,Tang Q Y. 2018. The crust-mantle transition structures beneath eastern China[J]. Chinese Journal of Geophysics,61(3):845–855 (in Chinese).
    滕吉文,曾融生,闫雅芬,张慧. 2002. 东亚大陆及周边海域Moho界面深度分布和基本构造格局[J]. 中国科学:D辑,32(2):89–100.
    Teng J W,Zeng R S,Yan Y F,Zhang H. 2002. Depth distribution of Moho and tectonic framework in eastern Asian continent and its adjacent ocean areas[J]. Science in China:Series D,46(5):428–446.
    隗永刚,杨千里,王婷婷,蒋长胜,边银菊. 2019. 基于深度学习残差网络模型的地震和爆破识别[J]. 地震学报,41(5):646–657.
    Wei Y G,Yang Q L,Wang T T,Jiang C S,Bian Y J. 2019. Earthquake and explosion identification based on Deep Learning residual network model[J]. Acta Seismologica Sinica,41(5):646–657 (in Chinese).
    危自根,储日升,杨小林,谢军,田忠华,凌媛,董非非. 2019. 汉中盆地及邻区地壳结构和地震活动性研究[J]. 地震学报,41(4):445–458.
    Wei Z G,Chu R S,Yang X L,Xie J,Tian Z H,Ling Y,Dong F F. 2019. Crustal structure and seismic activity in the Hanzhong basin and its adjacent areas[J]. Acta Seismologica Sinica,41(4):445–458 (in Chinese).
    熊小松. 2010. 中国大陆莫霍面深度与变化特征及其地球动力学意义[D]. 北京: 中国地质科学院: 91–93.
    Xiong X S. 2010. Moho Depth and Variation of the Continent in China and Its Geodynamic Implications[D]. Beijing: Chinese Academy of Geological Sciences: 91–93 （in Chinese）.
    杨宝俊,刘万崧,王喜臣,李勤学,王建民,赵雪平,李瑞磊. 2005. 中国东部大兴安岭重力梯级带域地球物理场特征及其成因[J]. 地球物理学报,48(1):86–97.
    Yang B J,Liu W S,Wang X C,Li Q X,Wang J M,Zhao X P,Li R L. 2005. Geophysical characteristics of Daxinganling gravitational gradient zone in the east China and its geodynamic mechanism[J]. Chinese Journal of Geophysics,48(1):86–97 (in Chinese).
    杨文采,瞿辰,侯遵泽,颜苹,于常青. 2017. 中国大陆造山带地壳密度结构特征[J]. 地质论评,63(3):539–548.
    Yang W C,Qu C,Hou Z Z,Yan P,Yu C Q. 2017. Crustal density structures beneath orogenic belts of Chinese continent[J]. Geological Review,63(3):539–548 (in Chinese).
    易桂喜,姚华建,朱介寿,van der Hilst R D. 2008. 中国大陆及邻区Rayleigh面波相速度分布特征[J]. 地球物理学报,51(2):402–411.
    Yi G X,Yao H J,Zhu J S,van der Hilst R D. 2008. Rayleigh-wave phase velocity distribution in China continent and its adjacent regions[J]. Chinese Journal of Geophysics,51(2):402–411 (in Chinese).
    易桂喜,姚华建,朱介寿,van der Hilst R D. 2010. 用Rayleigh面波方位各向异性研究中国大陆岩石圈形变特征[J]. 地球物理学报,53(2):256–268.
    Yi G X,Yao H J,Zhu J S,van der Hilst R D. 2010. Lithospheric deformation of continental China from Rayleigh wave azimuthal anisotropy[J]. Chinese Journal of Geophysics,53(2):256–268 (in Chinese).
    张广成,吴庆举,潘佳铁,张风雪,余大新. 2013. 利用H-K叠加方法和CCP叠加方法研究中国东北地区地壳结构与泊松比[J]. 地球物理学报,56(12):4084–4094.
    Zhang G C,Wu Q J,Pan J T,Zhang F X,Yu D X. 2013. Study of crustal structure and Poisson ratio of NE China by H-K stack and CCP stack methods[J]. Chinese Journal of Geophysics,56(12):4084–4094 (in Chinese).
    张攀,朱良保,陈浩朋,王清东,杨颖航. 2014. 用接收函数方法研究中国境内地壳结构[J]. 地震学报,36(5):850–861.
    Zhang P,Zhu L B,Chen H P,Wang Q D,Yang Y H. 2014. Crustal structure in China from teleseismic receiver function[J]. Acta Seismologica Sinica,36(5):850–861 (in Chinese).
    曾融生,孙为国,毛桐恩,林中洋,胡鸿翔,陈光英. 1995. 中国大陆莫霍界面深度图[J]. 地震学报,17(3):322–327.
    Zeng R S,Sun W G,Mao T E,Lin Z Y,Hu H X,Chen G Y. 1995. The depth of Moho in the mainland of China[J]. Acta Seismologica Sinica,17(3):322–327 (in Chinese).
    朱介寿,曹家敏,蔡学林,严忠琼,曹小林. 2002. 东亚及西太平洋边缘海高分辨率面波层析成像[J]. 地球物理学报,45(5):646–664.
    Zhu J S,Cao J M,Cai X L,Yan Z Q,Cao X L. 2002. High resolution surface wave tomography in East Asia and West Pacific marginal seas[J]. Chinese Journal of Geophysics,45(5):646–664 (in Chinese).
    Bassin C G L, Laske G, Masters G. 2000. The current limits of resolution for surface wave tomography in North America[J]. EOS Trans Am Geophys Union, 81（48）: F897.
    Chen Y L,Niu F L,Liu R F,Huang Z B,Tkalčić H,Sun H,Chan W. 2010. Crustal structure beneath China from receiver function analysis[J]. J Geophys Res:Solid Earth,115(B3):B03307.
    Cheng X Q,Liu Q H,Li P P,Liu Y. 2019. Inverting Rayleigh surface wave velocities for crustal thickness in eastern Tibet and the western Yangtze craton based on deep learning neural networks[J]. Nonlin Process Geophys Discuss,26:61–71. doi: 10.5194/npg-26-61-2019
    de Wit R W L,Valentine A P,Trampert J. 2013. Bayesian inference of Earth’s radial seismic structure from body-wave travel times using neural networks[J]. Geophys J Int,195(1):408–422. doi: 10.1093/gji/ggt220
    de Wit R W L,Käufl P J,Valentine A P,Trampert J. 2014. Bayesian inversion of free oscillations for earth’s radial (an)elastic structure[J]. Phys Earth Planet Int,237:1–17. doi: 10.1016/j.pepi.2014.09.004
    Devilee R J R,Curtis A,Roy-Chowdhury K. 1999. An efficient,probabilistic neural network approach to solving inverse problems:Inverting surface wave velocities for Eurasian crustal thickness[J]. J Geophys Res:Solid Earth,104(B12):28841–28857. doi: 10.1029/1999JB900273
    Feng M,An M J,Dong S W. 2017. Tectonic history of the Ordos block and Qinling orogen inferred from crustal thickness[J]. Geophys J Int,210(1):303–320. doi: 10.1093/gji/ggx163
    He R Z,Shang X F,Yu C Q,Zhang H J,van der Hilst R D. 2014. A unified map of Moho depth and vP/vS ratio of continental China by receiver function analysis[J]. Geophys J Int,199:1910–1918. doi: 10.1093/gji/ggu365
    Hinton G E,Salakhutdinov R R. 2006. Reducing the dimensionality of data with neural networks[J]. Science,313(5786):504–507. doi: 10.1126/science.1127647
    Huang Z X,Su W,Peng Y J,Zheng Y J,Li H Y. 2003. Rayleigh wave tomography of China and adjacent regions[J]. J Geophys Res:Solid Earth,108(B2):ES4-1–4-10.
    Lebedev S,Adam J M C,Meier T. 2013. Mapping the Moho with seismic surface waves:A review resolution analysis and recommended inversion strategies[J]. Tectonophysics,609(1):377–394.
    Legendre C P,Deschamps F,Zhao L,Chen Q F. 2015. Rayleigh-wave dispersion reveals crust-mantle decoupling beneath eastern Tibet[J]. Sci Rep,5(16644):1–7.
    Li Y H,Gao M T,Wu Q J. 2014. Crustal thickness map of the Chinese mainland from teleseismic receiver functions[J]. Tectonophysics,611:51–60. doi: 10.1016/j.tecto.2013.11.019
    Liu Q H,Li X,Ye M,Ge S S,Du X S. 2014. Drift compensation for electronic noise by semi-supervised domain adaption[J]. IEEE Sensors Journal,14(3):657–665. doi: 10.1109/JSEN.2013.2285919
    Liu Q H,Hu X N,Ye M,Cheng X Q,Li F. 2015. Gas recognition under sensor drift by using deep learning[J]. Inter J Intelli Syst,30(8):907–922. doi: 10.1002/int.21731
    Liu Q Y,van der Hilst R D,Li Y,Yao H J,Chen J H,Guo B,Qi S H,Wang J,Huang H,Li S C. 2014. Eastward expansion of the Tibetan Plateau by crustal flow and strain partitioning across faults[J]. Nat Geosci,7(5):361–365. doi: 10.1038/ngeo2130
    Marone C. 2018. Training machines in earthly ways[J]. Nat Geosci,11(5):301–302. doi: 10.1038/s41561-018-0117-5
    Masters G, Barmine M P, Pasadena K S. 2007. Mineos User’s Manual in Computational Infrastructure for Geodynamics[M]. Pasadena: California Institute of Technology: 9–89.
    Meier U,Curtis A,Trampert J. 2007. Global crustal thickness from neural network inversion of surface wave data[J]. Geophys J Int,169:706–722. doi: 10.1111/j.1365-246X.2007.03373.x
    Meier U,Trampert J,Curtis A. 2009. Global variations of temperature and water content in the mantle transition zone from higher mode surface waves[J]. Earth Planet Sci Lett,282(1/2/3/4):91–101.
    Rifai S, Vincent P, Muller X, Glorot X, Bengio Y. 2011. Contractive autoencoders: Explicit invariance during feature extraction[C]//Proceedings of the 28th International Conference on Machine Learning. Madison: Omnipress: 833–840.
    Rumelhart D E,Hinton G E,Williams R J. 1986. Learning representations by back-propagating errors[J]. Nature,323(6088):533–536. doi: 10.1038/323533a0
    Shapiro N M,Ritzwoller M H. 2002. Monte-Carlo inversion for a global shear-velocity model of the crust and upper mantle[J]. Geophys J Int,151:88–105. doi: 10.1046/j.1365-246X.2002.01742.x
    Shen W S,Ritzwoller M H,Kang D,Kim Y,Lin F C,Ning J Y,Wang W T,Zheng Y,Zhou L Q. 2016. A seismic reference model for the crust and uppermost mantle beneath China from surface wave dispersion[J]. Geophys J Int,206(2):954–979. doi: 10.1093/gji/ggw175
    Stolk W,Kaban M,Beekman F,Tesauro M,Mooney W D,Cloetingh S. 2013. High resolution regional crustal models from irregularly distributed data:Application to Asia and adjacent areas[J]. Tectonophysics,602:55–68. doi: 10.1016/j.tecto.2013.01.022
    van der Baan M,Jutten C. 2000. Neural networks in geophysical applications[J]. Geophysics,65(4):1032–1047. doi: 10.1190/1.1444797
    Vincent P, Larochelle H, Bengio Y, Manzagol P A. 2008. Extracting and composing robust features with denoising autoencoders[C]//Proceedings of the 25th International Conference on Machine Learning. New York, NY: ACM: 1096–1103.
    Wang W L,Wu J P,Fang L H,Lai G J,Cai Y. 2017. Crustal thickness and Poisson’s ratio in southwest China based on data from dense seismic arrays[J]. J Geophys Res:Solid Earth,122(9):7219–7235. doi: 10.1002/2017JB013978
    Wei Z G,Chen L,Li Z W,Ling Y,Li J. 2016. Regional variation in Moho depth and Poisson’s ratio beneath eastern China and its tectonic implications[J]. J Asia Earth Sci,115:308–320. doi: 10.1016/j.jseaes.2015.10.010
    Zhang P,Yao H J,Chen L,Fang L H,Wu Y,Feng J K. 2019. Moho depth variations from receiver function imaging in the northeastern North China Craton and its tectonic implications[J]. J Geophys Res:Solid Earth,124(2):1–19.
    Zhou Y,Nolet G,Dahlen F A,Laske G. 2006. Global upper-mantle structure from finite-frequency surface-wave tomography[J]. J Geophys Res:Solid Earth,111:B04304.
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