2018年9月8日墨江地震及周边地区构造应力场特征分析   总被引：1，自引：0，他引：1       下载免费PDF全文

李泽潇  万永革  崔华伟  李振月  胡晓辉  黄骥超  靳志同 《地球物理学报》2020,63(4):1431-1443

2018年9月8日,云南省墨江县发生MS5.9地震并伴随一系列余震,探究该地震周围的应力场对于理解该地震的发生机制和后续地震的发展趋势具有着重要的参考意义.本研究收集了震源及其邻区中前人研究和Global CMT所给出的震源机制资料,对该地区进行了构造应力场反演,并同时利用反演得到的应力张量模拟墨江地区的震源机制解表现.结果表明:(1)在应力轴整体分布上,自西向东σ1轴(压轴)从NNE-SSW向逐渐转向NNW-SSE向,σ3轴(张轴)从WWN-EES向逐渐转向WWS-EEN向,张轴呈弧形分布,压轴呈放射状分布.(2)在应力轴倾伏角上,研究区域内的压应力轴和张应力轴倾伏角都比较小,即两轴均接近水平.(3)R值分布大体是在东南部相较于西北部大,结合当地地质背景分析得到,物质逃逸自西北向东南呈逐渐变缓的趋势.(4)利用反演得到的应力张量和应力状态计算墨江地震震源区的相对剪应力和相对正应力大小.由此推测,墨江地震恰好发生在相对剪切应力值和相对正应力正值最大的节面上.从而可以确定墨江地震的发震节面的基本参数:走向216.32°,倾角86.91°,滑动角0.27°,相对剪应力值0.9,相对正应力值0.3.本研究为此次墨江地震的发震背景和地震动力学研究提供了基础性资料.  相似文献   

Estimation of the 3D correlation structure of an alluvial aquifer from surface-based multi-frequency ground-penetrating radar reflection data     

Zhiwei Xu  James Irving  Kyle Lindsay  John Bradford  Peimin Zhu  Klaus Holliger 《Geophysical Prospecting》2020,68(2):678-689

Knowledge about the stochastic nature of heterogeneity in subsurface hydraulic properties is critical for aquifer characterization and the corresponding prediction of groundwater flow and contaminant transport. Whereas the vertical correlation structure of the heterogeneity is often well constrained by borehole information, the lateral correlation structure is generally unknown because the spacing between boreholes is too large to allow for its meaningful inference. There is, however, evidence to suggest that information on the lateral correlation structure may be extracted from the correlation statistics of the subsurface reflectivity structure imaged by surface-based ground-penetrating radar measurements. To date, case studies involving this approach have been limited to 2D profiles acquired at a single antenna centre frequency in areas with limited complementary information. As a result, the practical reliability of this methodology has been difficult to assess. Here, we extend previous work to 3D and consider reflection ground-penetrating radar data acquired using two antenna centre frequencies at the extensively explored and well-constrained Boise Hydrogeophysical Research Site. We find that the results obtained using the two ground-penetrating radar frequencies are consistent with each other, as well as with information from a number of other studies at the Boise Hydrogeophysical Research Site. In addition, contrary to previous 2D work, our results indicate that the surface-based reflection ground-penetrating radar data are not only sensitive to the aspect ratio of the underlying heterogeneity, but also, albeit to a lesser extent, to the so-called Hurst number, which is a key parameter characterizing the local variability of the fine-scale structure.  相似文献   

Combining discrete cosine transform and convolutional neural networks to speed up the Hamiltonian Monte Carlo inversion of pre-stack seismic data     

Mattia Aleardi 《Geophysical Prospecting》2020,68(9):2738-2761

Markov chain Monte Carlo algorithms are commonly employed for accurate uncertainty appraisals in non-linear inverse problems. The downside of these algorithms is the considerable number of samples needed to achieve reliable posterior estimations, especially in high-dimensional model spaces. To overcome this issue, the Hamiltonian Monte Carlo algorithm has recently been introduced to solve geophysical inversions. Different from classical Markov chain Monte Carlo algorithms, this approach exploits the derivative information of the target posterior probability density to guide the sampling of the model space. However, its main downside is the computational cost for the derivative computation (i.e. the computation of the Jacobian matrix around each sampled model). Possible strategies to mitigate this issue are the reduction of the dimensionality of the model space and/or the use of efficient methods to compute the gradient of the target density. Here we focus the attention to the estimation of elastic properties (P-, S-wave velocities and density) from pre-stack data through a non-linear amplitude versus angle inversion in which the Hamiltonian Monte Carlo algorithm is used to sample the posterior probability. To decrease the computational cost of the inversion procedure, we employ the discrete cosine transform to reparametrize the model space, and we train a convolutional neural network to predict the Jacobian matrix around each sampled model. The training data set for the network is also parametrized in the discrete cosine transform space, thus allowing for a reduction of the number of parameters to be optimized during the learning phase. Once trained the network can be used to compute the Jacobian matrix associated with each sampled model in real time. The outcomes of the proposed approach are compared and validated with the predictions of Hamiltonian Monte Carlo inversions in which a quite computationally expensive, but accurate finite-difference scheme is used to compute the Jacobian matrix and with those obtained by replacing the Jacobian with a matrix operator derived from a linear approximation of the Zoeppritz equations. Synthetic and field inversion experiments demonstrate that the proposed approach dramatically reduces the cost of the Hamiltonian Monte Carlo inversion while preserving an accurate and efficient sampling of the posterior probability.  相似文献   

一种移动视频与地理场景的融合方法     

赵维淞  钱建国  汤圣君  王伟玺  李晓明  郭晗 《测绘通报》2020,(12):11-16

快速准确地了解灾害现场状况是救灾过程中的重中之重。通常发生灾害都会使用无人机进行现场勘察，但是无人机视频难以与实际的地理场景关联起来，为此本文提出了一种移动视频与地理场景的融合方法。该方法首先采用具有仿射不变性的ASIFT算法检测特征点，将匹配后的特征点采用RANSAC算法进行迭代剔除噪点，计算视频与地理场景最优的透视变换矩阵模型参数；然后将计算得到的透视变换参数应用到视频数据，恢复视频角点坐标；最后通过内插得出所有视频帧的角点坐标，实现视频与DOM的精确融合。试验结果表明，对视频数据匹配的间隔帧越短，其整体融合精度越高，通过本文方法进行视频与地理场景融合的误差标准差低于10 m。  相似文献   

Jason-2高度计电离层GIM误差分析及修正研究     

黄霞凤  苗洪利  苗翔鹰  薛文文 《海洋学报》2019,41(7):143-148

基于Jason-2高度计2015年地球物理数据集(GDR)38个周期太平洋海域的全球电离层图(GIM)电离层校正值和双频校正值的数据，分不同季度和不同纬度区域比较二者的差异，结果表明:GIM值与双频校正值之间存在明显的差异，GIM校正值普遍高于双频校正值，说明GIM高估了电离层路径延迟，GIM校正值与双频校正值的差异与季节和纬度区间有关。用梯度下降法得到GIM值的修正方程，将修正方程应用于2016年Jason-2的全年数据，修正后的GIM值与双频校正值十分接近，在各年份中均具有良好的适用性。在单频高度计不能使用电离层双频校正算法的情况下，可以利用不同季度和不同纬度区域的修正方程对同等高度的高度计GIM值进行修正以达到双频校正值的精度水平。  相似文献   

重力数据约束的二维地震层析成像在台湾海峡南部的应用     

王笋  闫培  刘善虎 《大地测量与地球动力学》2019,39(3):302-306

地震-重力联合反演可以降低多解性，针对大勘探范围内岩石波速-密度关系存在较大散布的问题，引入交叉梯度结构约束构建统一的目标函数是一种有效的解决方案。利用台湾海峡南部HX-13测线进行验证：由于火成岩侵入体的存在，部分区域难以拾取可靠的地震初至，常规的走时反演无法准确恢复基底面的形态。搜集研究区的船测重力资料，根据地震地质条件和数据特点设置合适的反演参数，实现基于物性和结构双重约束的重力-地震联合反演。由对反演结果的分析和解释可以看出，该方法可在很大程度上弥补地震数据不完备的缺陷，使反演过程稳定，并提高模型的可靠性。  相似文献   

Full moment tensor inversion constrained by double-couple focal mechanism for induced seismicity*          下载免费PDF全文

Yuyang Tan  Haijiang Zhang  Junlun Li  Chen Yin  Furong Wu 《地震科学（英文版）》2020,33(4):177-193

In this study, we propose a new method to determine full moment tensor solution for induced seismicity. This method generalizes the full waveform matching algorithm we have developed to determine the double-couple (DC) focal mechanism based on the neighbourhood algorithm. One major difference between the new method and the former one is that we adopt a new misfit function to constrain the candidate moment tensor solutions with respect to a reference DC solution in addition to other misfit terms characterizing the waveform matching. Through synthetic tests using a real passive seismic survey geometry, the results show the new constraint can help better recover the DC components of inverted moment tensors. We further investigate how errors in the velocity model and source location affect the moment tensor solution. The synthetic test results indicate that the constrained inversion is robust in recovering both the DC and non-DC components. We also test the proposed method on several real induced events in an oil/gas field in Oman using the same observation system as synthetic tests. While it is found that the full moment tensor solutions without using the DC constraints have much larger non-DC components than solutions with the DC constraints, both solutions are able to fit the observed waveforms at similar levels. The synthetic and real test results suggest the proposed DC constrained inversion method can reliably retrieve full moment tensor solutions for the induced seismicity.  相似文献   

基于遗传算法优化BP神经网络的玉米遥感估产方法     

于海洋  陈圣波  杨北萍  安秦 《世界地质》2020,39(1):208-214

以内蒙古自治区开鲁县玉米作物为研究对象,将生育期内玉米遥感影像所提取的多种植被指数和实地采样点的测产数据作为训练值,利用BP(back propagation)神经网络和遗传算法优化BP(GA-BP)神经网络估产模型,得出网络预测的玉米产量数值。通过决定系数R 2和均方根误差RMSE,比较实测产量与预测产量之间的精度,BP神经网络模型R^2为0.8452,RMSE(%)为28.37;遗传算法优化BP神经网络模型R^2为0.9850,RMSE(%)为6.70,表明遗传算法优化BP神经网络估产模型具有一定可行性和可信度。  相似文献   

深厚软土场地基岩地震动反演——以天津波为例          下载免费PDF全文

梁建文  张萍  何颖 《世界地震工程》2020,(3):001-11

根据天津波地表加速度记录和相应实测场地钻孔资料，采用等效线性化方法模拟土体非线性，进行了深厚软土场地基岩地震动反演，研究了频率截断对深厚软土场地基岩地震动反演的影响，为天津波地表加速度记录提供了相应的基岩地震动输入。研究表明:不同截断频率情况下，反演得到的基岩地震动峰值和反应谱曲线形状均相差悬殊，但反演后再正演所得到的地面运动与原地表记录相比，加速度时程曲线形状和峰值大小、反应谱曲线形状和峰值大小均非常接近；可根据工程需要对地表加速度记录进行不同频率的截断，反演得到所需强度的基岩地震动。  相似文献   

双稀疏字典和FISTA的地震数据去噪          下载免费PDF全文

张良  韩立国  方金伟  张盼  刘争光 《地球物理学报》2019,62(7):2671-2683

地震数据的随机噪声去除是地震数据处理中的一项重要步骤，双稀疏字典提供了两层稀疏模型，比单层稀疏模型可以更好地去除噪声.该方法首先利用contourlet变换对地震数据进行稀疏表示，然后在contourlet域中使用快速迭代收缩阈值算法（fast iterative shrinkage-thresholding algorithm，FISTA）对初始字典系数进行更新，接着采用数据驱动紧标架（data-driven tight frame，DDTF）在contourlet域中得到DDTF字典并通过FISTA得到更新后的字典系数，最后通过DDTF字典和更新后的字典系数获得新的contourlet系数，并对新的contourlet系数进行硬阈值和contourlet反变换得到去噪后的数据.通过模拟数据和实际数据的实验证明：与固定基变换去噪方法相比，该方法可以自适应地对地震数据进行稀疏表示，在地震数据较为复杂时得到更高的信噪比；与字典学习去噪方法相比，该方法不仅拥有较快的去噪速度，而且克服了字典学习因为缺少先验约束造成瑕疵的缺点.  相似文献