四川和云南地区场地平均剪切波速vS20vS30的经验预测模型研究

贾琳 谢俊举 李小军 温增平 陈文彬 周健

贾琳,谢俊举,李小军,温增平,陈文彬,周健. 2021. 四川和云南地区场地平均剪切波速vS20和vS30的经验预测模型研究. 地震学报,43(5):629−644 doi: 10.11939/jass.20200193
引用本文: 贾琳,谢俊举,李小军,温增平,陈文彬,周健. 2021. 四川和云南地区场地平均剪切波速vS20vS30的经验预测模型研究. 地震学报,43(5):629−644 doi: 10.11939/jass.20200193
Jia L,Xie J J,Li X J,Wen Z P,Chen W B,Zhou J. 2021. Empirical prediction models of time-averaged shear wave velocity vS20 and vS30 in Sichuan and Yunnan areas. Acta Seismologica Sinica,43(5):629−644 doi: 10.11939/jass.20200193
Citation: Jia L,Xie J J,Li X J,Wen Z P,Chen W B,Zhou J. 2021. Empirical prediction models of time-averaged shear wave velocity vS20 and vS30 in Sichuan and Yunnan areas. Acta Seismologica Sinica43(5):629−644 doi: 10.11939/jass.20200193

四川和云南地区场地平均剪切波速vS20vS30的经验预测模型研究

doi: 10.11939/jass.20200193
基金项目: 国家重点研发计划项目(2018YFE0109800)、中国地震局地球物理研究所基本科研业务费专项(DQJB20B23)和国家自然科学基金项目(51639006,51738001)共同资助
详细信息
    通讯作者:

    谢俊举,e-mail:xiejunjv05@mails.ucas.ac.cn

  • 中图分类号: P315.09

Empirical prediction models of time-averaged shear wave velocity vS20 and vS30 in Sichuan and Yunnan areas

  • 摘要: 利用四川和云南地区共973个工程场地钻孔资料,分别基于常速度外推模型、对数线性模型和条件独立模型的经验外推方法建立了该区域20 m和30 m平均剪切波速VS20VS30的经验预测模型。研究表明常速度外推模型的预测误差最大,当波速资料深度小于10 m时,常速度外推方法会显著低估实际场地平均波速。基于对数线性外推方法建立了四川和云南地区波速经验预测模型,对比结果表明四川和云南地区平均波速预测结果与北京和加州地区较接近,明显低于日本地区。基于三种不同外推方法的预测误差对比分析结果表明条件独立性模型的预测结果在不同深度时误差均为最小,建议优先采用该方法建立的区域波速预测模型。

     

  • 图  1  收集的四川和云南地区973个钻孔的位置分布

    Ⅰ扬子准地台;Ⅱ秦岭-大别造山带;Ⅲ松潘-甘孜造山带;Ⅳ羌塘地带;Ⅴ中缅地块;Ⅵ改则-那曲造山带;Ⅶ右江造山带

    Figure  1.  Location of 973 borehole sites of Sichuan and Yunnan Provinces used in this study

    ⅠYantze Platform;ⅡQinling-Dabie orogenic belt;ⅢSongpan-Ganzi orogenic belt;ⅣQiangtang block;ⅤSino-Burmese block;Ⅵ Greze-Nakchu orogenic belt;ⅦYoujiang orogenic belt

    图  2  收集的四川和云南地区973个钻孔数据的第四系沉积物厚度分布

    Figure  2.  Distribution of Quaternary sediment depth from 973 boreholes in Yunnan and Sichuan Provinces

    图  3  四川和云南地区典型钻孔柱状图

    (a) 四川挖角乡;(b) 云南坝心乡

    Figure  3.  Typical drilling column map in Sichuan and Yunnan region

    (a) Wajiao township in Sichuan;(b) Baxin township in Yunnan

    图  4  基于不同深度钻孔数据采用BCV方法的预测值vS20est与实际平均波速vS20的对比

    Figure  4.  Comparison between the estimate vS20est and the measured vS20 in BCV model at different depths

    图  5  基于不同深度钻孔资料采用BCV法的预测值vS30est与实际波速vS30的对比

    Figure  5.  Comparison between the estimate vS30est and the measured vS30 in BCV model at different depths

    图  6  基于Boore (2004)方法得到不同深度下lgvS20与lgvSz的拟合回归分析结果

    Figure  6.  Regression results of lgvS20 and lgvSz at different depths based on Boore (2004) method

    图  7  基于Boore (2004)方法得到不同深度下lgvS30与lgvSz的拟合回归分析结果

    Figure  7.  Regression results of lgvS30 and lgvSz at different depths based on Boore (2004) method

    图  8  基于条件独立模型得到不同深度下lgvS[z,30]与lgvSz)的拟合回归分析结果

    Figure  8.  Regression results of lgvS[z,30] and lgvSz) at different depths based on the conditional independence property model

    图  9  基于条件独立模型得到不同深度下lgvS[z,20]与lgvSz)的拟合回归分析结果

    Figure  9.  Regression results of lgvS[z,20] and lgvSz) at different depths based on the conditional independence property model

    图  10  采用BCV模型、Boore对数线性模型和Markov条件独立模型建立的四川和云南地区vS20 (a)和vS30 (b)预测模型的误差对比

    Figure  10.  Comparison of the estimation errors of vS20 (a) and vS30 (b) for the BCV model, the Boore log-linear model, and the conditional independence property model (labeled as Markov process) in Sichuan and Yunnan regions

    表  1  钻孔深度统计表

    Table  1.   Drilling depth statistics

    钻孔深度/m钻孔个数
    0<d<53
    5≤d<20330
    20≤d<30369
    d≥30271
    下载: 导出CSV

    表  2  采用BCV方法得到的vS20estvS20相关系数r及预测误差的标准差σRES

    Table  2.   List of correlation coefficients r and standard deviation σRES of vS20est and vS20 by BCV method

    深度/mr$ {\sigma }_{\mathrm{R}\mathrm{E}\mathrm{S}} $深度/mr$ {\sigma }_{\mathrm{R}\mathrm{E}\mathrm{S}} $
    6 0.811 3 22.06 13 0.986 2 2.89
    7 0.867 0 17.79 14 0.989 7 1.50
    8 0.902 6 15.13 15 0.993 7 1.24
    9 0.937 5 10.61 16 0.995 7 0.67
    10 0.952 9 8.24 17 0.997 8 0.36
    11 0.968 1 3.47 18 0.999 0 0.53
    12 0.977 7 3.33 19 0.999 8 0.32
    注:σRES为预测误差(估计值—实际值)的标准差,下同。
    下载: 导出CSV

    表  3  采用BCV方法得到的vS30estvS30相关系数r及预测误差的标准差σRES

    Table  3.   List of correlation coefficients r and standard deviation σRES of vS30est and vS30 by BCV method

    深度/mrσRES深度/mrσRES
    6 0.733 8 26.303 18 0.976 0 2.594
    7 0.767 6 23.926 19 0.990 2 0.245
    8 0.813 6 21.711 20 0.991 7 0.224
    9 0.882 2 12.613 21 0.992 5 0.275
    10 0.899 7 10.458 22 0.994 1 0.581
    11 0.925 4 6.408 23 0.996 3 0.758
    12 0.940 2 4.946 24 0.996 5 0.922
    13 0.952 2 3.752 25 0.997 9 1.167
    14 0.962 8 0.897 26 0.997 6 0.272
    15 0.968 0 1.221 27 0.999 0 0.179
    16 0.970 5 0.637 28 0.999 8 0.016
    17 0.979 5 0.375 29 1.000 0 0.007
    下载: 导出CSV

    表  4  基于Boore(2004)方法(式5)建立四川和云南地区vS20预测经验关系的回归分析结果

    Table  4.   Regression results of vS20 predictive empirical relationships for Sichuan and Yunnan region based on Boore (2004) method of equation 5

    深度/m$ {a}_{0} $$ {a}_{1} $相关系数r$ {\sigma }_{\mathrm{R}\mathrm{E}\mathrm{S}} $
    60.8240.5370.7450.072
    70.8800.3940.7950.066
    80.9250.2770.8350.059
    90.9630.1760.8720.053
    100.9920.0970.9020.047
    111.0070.0510.9260.041
    121.0210.0090.9470.035
    131.025−0.0100.9620.029
    141.026−0.0210.9740.025
    151.024−0.0240.9830.020
    161.020−0.0210.9900.016
    171.014−0.0140.9940.012
    181.009−0.0100.9970.008
    191.005−0.0070.9990.004
    注:σRES为预测误差(此处取估计值相对于实际值的对数残差,即lg估计值−lg实际值)的标准差,下同。
    下载: 导出CSV

    表  5  基于Boore (2004)方法(式5)建立四川和云南地区vS30预测经验关系的回归分析结果

    Table  5.   Regression results of vS30 predictive empirical relationships for Sichuan and Yunnan regions based on Boore (2004) method

    深度/m$ {a}_{0} $$ {a}_{1} $相关系数r标准差${\sigma }_{{\rm{RES}}}$
    61.4580.4400.4450.101 1
    71.3640.4790.4540.100 6
    81.1910.5530.4920.098 3
    90.9460.6570.5530.094 0
    100.7340.7460.6070.089 7
    110.5780.8090.6610.084 7
    120.4550.8590.7060.079 9
    130.3240.9120.7480.074 9
    140.2080.9580.7890.069 3
    150.1021.0000.8270.063 4
    160.0211.0310.8610.057 4
    17−0.0401.0530.8880.051 9
    18−0.0561.0570.9060.047 7
    19−0.0641.0580.9210.044 0
    20−0.0651.0550.9330.040 6
    21−0.0621.0520.9440.037 2
    22−0.0591.0480.9520.034 5
    23−0.0601.0460.9610.031 4
    24−0.0641.0460.9690.028 1
    25−0.0641.0440.9750.025 0
    26−0.0611.0400.9810.022 0
    27−0.0531.0350.9850.019 3
    28−0.0421.0290.9890.016 7
    29−0.0321.0230.9920.014 1
    下载: 导出CSV

    表  6  基于条件独立模型(式6)得到的vS[z,30]vSz)之间的经验关系

    Table  6.   Regression results for vS[z,30] and vSz) empirical relationships based on the conditional independence property model of equation 6

    深度/m${c}_{0}$${c}_{1}$相关系数r标准差${\sigma }_{{\rm{RES}}}$
    6 1.038 0.608 0.649 0.153
    7 0.882 0.669 0.666 0.150
    8 0.651 0.762 0.723 0.146
    9 0.481 0.831 0.821 0.141
    10 0.499 0.822 0.823 0.134
    11 0.561 0.796 0.849 0.136
    12 0.530 0.806 0.843 0.136
    13 0.426 0.847 0.861 0.134
    14 0.494 0.820 0.877 0.128
    15 0.442 0.840 0.878 0.125
    16 0.522 0.808 0.865 0.123
    17 0.359 0.870 0.895 0.120
    18 0.338 0.878 0.885 0.118
    19 0.265 0.908 0.928 0.118
    20 0.255 0.909 0.934 0.118
    21 0.295 0.893 0.930 0.117
    22 0.313 0.885 0.927 0.116
    23 0.326 0.879 0.933 0.114
    24 0.387 0.854 0.907 0.118
    25 0.289 0.892 0.944 0.094
    26 0.279 0.895 0.943 0.095
    27 0.154 0.942 0.960 0.080
    28 0.063 0.977 0.979 0.064
    29 0.067 0.975 0.986 0.057
    下载: 导出CSV

    表  7  基于条件独立模型(式6)得到vS[z,20]vSz)之间的经验关系

    Table  7.   Regression results for vS[z,20] and vSz) empirical relationships based on the conditional independence property model of equation 6

    深度/m${c}_{0}$${c}_{1}$相关系数r标准差$ {\sigma }_{\mathrm{R}\mathrm{E}\mathrm{S}} $
    61.1610.6480.6980.152
    71.0120.7120.7250.147
    80.8260.7910.7780.140
    90.6790.8550.8500.132
    100.7120.8470.8520.128
    110.8070.8150.8750.126
    120.7390.8490.8840.123
    130.5910.9150.9230.110
    140.7170.8780.9250.107
    150.6900.9030.9360.099
    160.7920.8820.9390.099
    170.7770.9130.9520.089
    180.7680.9510.9620.081
    190.8380.9780.9840.061
    下载: 导出CSV
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  • 收稿日期:  2020-11-26
  • 修回日期:  2021-01-21
  • 网络出版日期:  2021-11-11

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