P波和S波接收函数的贝叶斯联合反演

S波接收函数对于研究岩石圈速度结构具有重要价值. 本文利用合成地震图技术研究了S波接收函数的动力学特征. 在接收函数非线性复谱比反演方法的基础上,发展了基于贝叶斯理论的P波和S波接收函数的非线性联合反演方法. 结果表明:(1)适用于S波接收函数反演的震中距范围约为55°~80°,S波接收函数反演要求所用远震事件的震级大于5级; (2)与陡变的岩石圈底部界面(LAB)相比,梯度带类型LAB上生成的S_LP转换波相对较弱,台站下方的沉积盖层有助于相对增强S_LP震相; (3)由于S波接收函数径向分量不符合δ脉冲,不依赖于等效震源假定的三分量接收函数多道最大或然性反褶积方法更适合S波接收函数的估计;(4)数值检验的结果表明,在初始模型速度参数偏离真实模型20%的情况下,本文的方法能够预测300 km深度范围内的P波和S波速度结构;(5)观测数据的反演结果表明,由于P波接收函数低频分量相对不足,本文的联合反演方法对于大于100 km深度上地幔的S波速度结构约束相对较弱.     

横向非均匀介质远震体波接收函数的波场特征

系统研究了台站下方存在倾斜界面时,远震体波接收函数的波场特征及多方位接收函数对台站下方介质横向非均匀特征的反映能力．我们利用合成三维横向非均匀介质接收函数的Maslov方法,具体模拟了台站下方存在倾斜界面时的接收函数响应．结果表明,当台站下方存在倾向一致的倾斜界面时,远震体波接收函数的径向分量和切向分量分别随震源方位角的变化呈现对称和反对称的规律性变化．利用不同震源方位角接收函数径向分量和切向分量的变化规律,可以估计台站下方界面的倾向和倾角．当台站下方各界面的倾向不同时,随方位角的变化,接收函数只能直观给出界面的整体倾向．实际观测数据的分析结果表明,对于利用单个台站接收函数研究台站下方介质的横向非均匀特征来说,简单倾斜界面可以看作较好的一级近似．      

稳定的频率域提取接收函数方法研究

频率域提取接收函数时引入“水准量”来代替垂向分量频谱中比较小的成分以保证反褶积结果的稳定性,却降低了精度,尤其对反映深部壳幔结构的低频信息影响较大;实际的等效震源时间函数长度是有限的,由于地震记录上后续干扰震相能量的影响,垂直分量波形往往比较复杂,若将其直接作为等效震源时间函数必然影响所提取接收函数的精度.针对以上问题,本文改进“水准量”的使用方法,并采取折中方案选取“水准量”和等效震源时间函数的长度,以便在频率域反褶积中得到稳定的接收函数,同时提高反褶积的精度.对观测数据的试验效果显示,本文方法提取的接收函数稳定性好、精度高,是一种有效的提取台站高质量接收函数的方法.     

接收函数方法及研究进展

远震P波波形数据中包含了大量在台站下方地壳上地幔速度间断面所产生的P-S转换波及其多次反射波的信息，是研究台站下方局部区域S速度分布理想的震相，由此产生的接收函数方法是反演台站下方S波速度结构的有效手段。接收函数方法可以通过波形反演拟合接收函数的径向分量，对观测台站下方地球介质的S波速度结构进行估计，也可以通过偏移叠加获得的接收函数道集（地震剖面图）追踪速度间断面。这种方法避免了对天然地震震源及其附近结构混响效应等复杂因素的影响，对S波速度的垂向分布敏感，垂向分辨率高。由于宽频带流动地震台阵的发展，用此方法还可获得研究区域速度结构的横向变化，横向分辨能力主要取决于台站的间距。本文回顾20年来接收函数研究的进展，探讨了方法研究的发展趋势，介绍了对地壳-上地幔结构的部分研究结果。     

利用宽频带远震体波波形研究青藏高原地壳上地幔速度结构的初步结果

利用根据中美合作研究青藏高原深部结构计划布设在青藏高原上的11个宽频带数字地震仪记录到的远震体波数据,采用接收函数(receiver function)反演的方法,对各台站下面地壳上地幔地震波速度结构进行了研究。台站接收函数是通过将三分向地震记录的两个水平分量旋转合成得到径向分量,然后在频率域除以垂直分量并变换回到时间域得到的,它仅与台站下面介质结构有关,而基本上与震源函数和传播路径无关。为压制噪声干扰,对来自同一方向上一定震中距范围内的远震记录得到的接收函数进行了叠加。采用分层弹性介质中弹性波传播矩阵理论,我们可以计算得到分层介质的理论接收函数以及它对各层弹性参数的偏导数,从而利用迭代线性反演可从观测接收函数得到台站下面的一维速度结构。本文给出了其中3个台,即温泉台、格尔木台和日喀则台的初步结果,它们分别位于高原的中部、北部和南部。从各台的接收函数中都可看到清晰的 Moho 面上的 P-S 转换波震相,其相对直达 P 波的走时延迟分别为:温泉台7.9s(东北方向结果),8.3s(东南方向结果);格尔木台8.2s;日喀则台9.0s,如此大的延迟表明高原地壳的巨厚.      

2001年11月14日昆仑山库赛湖地震(M_S8.1)地表破裂带的基本特征

震后野外考察表明 ,2 0 0 1年 11月 14日昆仑山库赛湖地震 (MS8 1)发生在青藏高原北部东昆仑断裂带库赛湖段上 ,发震断层具有高速率左旋滑动的基本特征 ,晚更新世晚期以来的平均滑动速率达 (14 8± 2 4 )mm/a ;地震地表破裂带沿库赛湖段西起布喀达板峰东缘 (91°0 8′E) ,向东经库赛湖北缘、青藏公路 2 894里程碑、玉珠峰南麓 ,东止于青藏公路东 70km附近 (94°4 8′E) ,地震地表破裂带沿N70°～ 90°W走向线状展布 ,全长约 35 0km ,由一系列走向N4 5°～ 5 0°E拉开状张裂缝、走向N6 0°～ 75°E张剪切裂缝、走向N80°W剪切裂缝以及隆起鼓包或开裂陷坑等斜列状组合而成 ,显示出纯剪切走滑的破裂特征 ,最大左旋水平位移 6m ;宏观震中位于昆仑山口西 80～ 90km附近的库赛湖东北角山麓地带 ,地震地表破裂带宽度 30 0m ,在库赛湖北岸至山麓地带的地震地表破裂带和由地震动或重力效应引起的次生破裂带总宽度可达 2km。库赛湖地震地表破裂的左旋走滑特征表明 ,青藏高原物质确实存在着向东的滑移或流动 ,东昆仑断裂带东部与库赛湖段斜列的东大     

利用近场强震记录反演2016年日本熊本县地震震源破裂过程

2016年4月15日16时25分（UTC）,日本熊本县发生M_W7.1强烈地震,给当地人员、建筑及经济造成严重灾难和巨大损失.日本地震观测网F-net给出的震源机制解显示此次地震的震源位置为130.7630°E,32.7545°N,深度12.45 km,节面Ⅰ：走向N131°E、倾角53°、滑动角-7°;节面Ⅱ：走向N226°E、倾角84°、滑动角-142°.与此同时,余震的震中分布及其震源机制结果显示主震的震源机制在破裂过程中有可能发生了变化,单一的震源机制不足以充分解释观测数据.本文依据GNSS和InSAR地表形变反演结果为约束,并结合活动构造资料为参考,构建了震源机制变化的有限断层模型,采用水平层状介质模型,利用日本强震观测台网K-NET和KiK-net的近场加速度观测记录,通过多时间窗线性波形反演方法反演了此次地震的震源破裂过程.研究结果显示,这是一次沿Futagawa-Hinagu断层带发生的右旋走滑破裂事件,发震断层分为南北两段,其中北段走向N235°E、倾角60°,南段走向N205°E、倾角72°,断层深度范围和余震深度分布基本一致,断层面上滑动主要集中于断层北段,最大滑动量约7.9 m,整个断层的破裂过程持续约18 s,释放地震矩5.47×10¹⁹ N·m（M_W7.1）.     

用Wiener滤波方法提取台站接收函数

本文提出了一种在时间域用Wiener滤波方法提取台站接收函数的方法，用远震P波波形的垂直分量为输入，接收函数作为滤波因子，远震P波波形的径向和切向分量作为期望输出，通过期望输出与实际输出的均方误差达极小，来提取接收函数。接收函数的计算可归结为Toeplitz方程的求解，可以采用Levinson递推算法。Toeplitz方程的非奇异性保证了Wiener滤波反褶积方法的稳定性。合成地震图与观测地震图的检验表明，用Wiener滤波方法测定台站接收函数是一种有效的时间域反褶积方法。     

基于贝叶斯理论的接收函数与环境噪声联合反演

基于Bayes反演理论(Tarantola,1987,2005),在接收函数非线性复谱比反演方法基础上(刘启元等,1996),本文讨论了接收函数与地震环境噪声Rayleigh波相速度频散的联合反演.本文采用修正后的快速广义反射/透射系数方法(Pei et al., 2008,2009) 计算Rayleigh波相速度频散, 并引入地壳泊松比的全局性搜索.数值检验表明:(1)接收函数与环境噪声的联合反演能够有效地解决反演结果对初始模型依赖的问题,即使对地壳速度结构仅有非常粗略的初始估计(例如,垂向均匀模型),本文方法仍能给出模型参数的可靠估计;(2)由于环境噪声与接收函数在频带上的适配性明显优于地震面波,接收函数与环境噪声的非线性联合反演能更好地约束台站下方近地表的速度结构;对于周期范围为2~40s的环境噪声相速度频散,利用本文方法能够可靠推测台站下方0~80 km深度范围的S波速度结构, 其浅表速度结构的分辨率可达到1 km; (3)本文方法能够可靠地估计地壳泊松比,泊松比的全局性搜索有助于合理解释接收函数和环境噪声的面波频散数据.利用本文方法对川西台阵KWC05台站观测的接收函数与环境噪声的联合反演表明,该台站下方地壳厚度为44 km,上地壳具有明显的高速结构,24~42 km范围的中下地壳具有低速结构.该台站下方地壳的平均泊松比为0.262,壳内低速带的泊松比为0.27.     

核幔边界反射P波对接收函数影响的研究

远震P波接收函数是探测壳幔结构的有效方法,它采用平面波入射假定,将入射波视为具有相同射线参数的单一震相.然而,在一定震中距时,核幔边界反射P波(如PcP震相)会进入接收函数提取窗口,其射线参数与直达P波相差较大,可能导致提取的接收函数存在偏差.本文理论测试了不同震源机制,震中距以及震源深度等情况下核幔边界反射P波对远震P波接收函数的影响,并结合实际观测资料进行对比分析.测试结果显示,与走滑断层产生的PcP震相对接收函数影响较小不同,倾滑断层产生的PcP震相会使接收函数出现虚假震相并降低直达P波及后续震相的振幅,从而干扰壳幔间断面(如410 km和660 km间断面)的识别,并导致反演的台站下方S波速度降低达到5%.进一步分析倾滑型地震对接收函数波形影响发现,当震源深度小于300 km时,PcP震相导致接收函数直达P波振幅要低于4%.在震源深度在300～450 km、震中距为50°～60°、断层倾角在大约30°～60°,以及震源深度大于450 km、震中距为50°～60°、断层倾角大约25°～65°情况下影响可达20%.接收函数叠加方法可以有效压制结果中PcP震相导致的虚假信号,但是仍然无法完全去除PcP对接收函数振幅的影响,叠加后直达P波振幅降低仍然能够达到4%.本文结果表明,在计算接收函数时,剔除掉产生较强PcP的特定震源机制、震中距和震源深度的地震事件有助于反演精确的壳幔结构.     

Receiver function method in reflection seismology

The receiver function method was originally developed to analyse earthquake data recorded by multicomponent (3C) sensors and consists in deconvolving the horizontal component by the vertical component. The deconvolution process removes travel path effects from the source to the base of the target as well as the earthquake source signature. In addition, it provides the possibility of separating the emergent P and PS waves based on adaptive subtraction between recorded components if plane waves of constant ray parameters are considered. The resulting receiver function signal is the local PS wave's impulse response generated at impedance contrasts below the 3C receiver.We propose to adapt this technique to the wide‐angle multi‐component reflection acquisition geometry. We focus on the simplest case of land data reflection acquisition. Our adapted version of the receiver function approach consists in a multi‐step procedure that first removes the P wavefield recorded on the horizontal component and next removes the source signature. The separation step is performed in the τ?p domain while the source designature can be achieved in either the τ?p or the t?x domain. Our technique does not require any a priori knowledge of the subsurface. The resulting receiver function is a pure PS‐wave reflectivity response, which can be used for amplitude versus slowness or offset analysis. Stack of the receiver function leads to a high‐quality S wave image.     

Multifocusing revisited ‐ inhomogeneous media and curved interfaces*

We review the multifocusing method for traveltime moveout approximation of multicoverage seismic data. Multifocusing constructs the moveout based on two notional spherical waves at each source and receiver point, respectively. These two waves are mutually related by a focusing quantity. We clarify the role of this focusing quantity and emphasize that it is a function of the source and receiver location, rather than a fixed parameter for a given multicoverage gather. The focusing function can be designed to make the traveltime moveout exact in certain generic cases that have practical importance in seismic processing and interpretation. The case of a plane dipping reflector (planar multifocusing) has been the subject of all publications so far. We show that the focusing function can be generalized to other surfaces, most importantly to the spherical reflector (spherical multifocusing). At the same time, the generalization implies a simplification of the multifocusing method. The exact traveltime moveout on spherical surfaces is a very versatile and robust formula, which is valid for a wide range of offsets and locations of source and receiver, even on rugged topography. In two‐dimensional surveys, it depends on the same three parameters that are commonly used in planar multifocusing and the common‐reflection surface (CRS) stack method: the radii of curvature of the normal and normal‐incidence‐point waves and the emergence angle. In three dimensions the exact traveltime moveout on spherical surfaces depends on only one additional parameter, the inclination of the plane containing the source, receiver and reflection point. Comparison of the planar and spherical multifocusing with the CRS moveout expression for a range of reflectors with increasing curvature shows that the planar multifocusing can be remarkably accurate but the CRS becomes increasingly inaccurate. This can be attributed to the fact that the CRS formula is based on a Taylor expansion, whereas the multifocusing formulae are double‐square root formulae. As a result, planar and spherical multifocusing are better suited to model the moveout of diffracted waves.     

地形表面反射强度的数学层析成像方法

若二维ＲＦ窄波反射函数是定义在地面一圆形区域内部的，并假定该圆域表面介质是弱反射介质，那么在给定时刻，接收发射器（如机载合成孔径雷达）所接收到的近回数据可视 过该圆域的一圆弧上的线积分值，Ｍｕｍｓｏｎ，ｅｔ，ａｌ。在假定圆域半径与接收发射器运动路径到该圆域中心的距离相比很小的情况，用直线上的线积分值来代替圆弧线上的线积分值，利用古典的Ｒａｄｏｎ变换方法，给出了该圆域反射函数的成像模式。本文将克服这     

基于稀疏约束反演的三维混采数据分离

混合震源采集技术相对于传统的地震数据采集,在极大提高采集效率的同时引入了混叠噪声,很大程度上影响了成像结果的精度.二维混采数据中,我们通常利用混叠噪声在非共炮域呈非相干分布这一特点来压制混叠噪声,从而实现混合震源数据分离.相对于二维混采数据,三维混采数据具有数据量巨大,构建混合震源算子困难,混合度的增加引入了高强度混叠噪声的特点.针对上述问题,本文采用稀疏约束反演方法在Radon域实现混采数据分离,混叠噪声强度比较大的情况下,稀疏约束反演方法能够得到更高精度的分离结果;利用震源激发的GPS时间通过长记录的方式在共接收点道集对上一次迭代分离结果做混合、伪分离,实现了单个共接收点道集自身混合、伪分离,避免了对整个数据做运算,同时不需要构建混合震源算子.通过模拟数据和实际数据计算来验证上述方法的适用性.     

基于解析时间波场外推与波场分解的逆时偏移方法研究

双程波方程逆时深度偏移是复杂介质高精度成像的有效技术,但其结果中通常包含成像方法引起的噪音和假象,一般的滤波方法会破坏成像剖面上的振幅,其中的假象也会给后续地质解释带来困扰.将波场进行方向分解然后实现入射波与反射波的相关成像能够有效地消除这类成像噪音,并提高逆时偏移成像质量.波传播方向的分解通常在频率波数域实现,它会占用大量的存储和计算资源,不便于在沿时间外推的逆时深度偏移中应用.本文提出解析时间波场外推方法,可以在时间外推的每个时间片上实现波传播方向的显式分解,逆时深度偏移中利用分解后的炮检波场进行对应的相关运算,实现成像噪音和成像信号的分离.在模型和实际数据上的测试表明,相比于常规互相关逆时偏移成像结果,本文方法能够有效地消除低频成像噪音和特殊地质构造导致的成像假象.     

Scattered ground‐roll attenuation using model‐driven interferometry

Scattered ground roll is a type of noise observed in land seismic data that can be particularly difficult to suppress. Typically, this type of noise cannot be removed using conventional velocity‐based filters. In this paper, we discuss a model‐driven form of seismic interferometry that allows suppression of scattered ground‐roll noise in land seismic data. The conventional cross‐correlate and stack interferometry approach results in scattered noise estimates between two receiver locations (i.e. as if one of the receivers had been replaced by a source). For noise suppression, this requires that each source we wish to attenuate the noise from is co‐located with a receiver. The model‐driven form differs, as the use of a simple model in place of one of the inputs for interferometry allows the scattered noise estimate to be made between a source and a receiver. This allows the method to be more flexible, as co‐location of sources and receivers is not required, and the method can be applied to data sets with a variety of different acquisition geometries. A simple plane‐wave model is used, allowing the method to remain relatively data driven, with weighting factors for the plane waves determined using a least‐squares solution. Using a number of both synthetic and real two‐dimensional (2D) and three‐dimensional (3D) land seismic data sets, we show that this model‐driven approach provides effective results, allowing suppression of scattered ground‐roll noise without having an adverse effect on the underlying signal.     

A platform for Kirchhoff data mapping in scalar models of data acquisition

Kirchhoff data mapping (KDM) is a procedure for transforming data from a given input source/receiver configuration and background earth model to data corresponding to a different output source/receiver configuration and background model. The generalization of NMO/DMO, datuming and offset continuation are three examples of KDM applications. This paper describes a 'platform' for KDM for scalar wavefields. The word, platform, indicates that no calculations are carried out in this paper that would adapt the derived formula to any one of a list of KDMs that are presented in the text. Platform formulae are presented in 3D and in 2.5D. For the latter, the validity of the platform equation is verified — within the constraints of high-frequency asymptotics — by applying it to a Kirchhoff approximate representation of the upward scattered data from a single reflector and for an arbitrary source/receiver configuration. The KDM formalism is shown to map this Kirchhoff model data in the input source/receiver configuration to Kirchhoff data in the output source/receiver configuration, with one exception. The method does not map the reflection coefficient. Thus, we verify that, asymptotically, the ray theoretical geometrical spreading effects due to propagation and reflection (including reflector curvature) are mapped by this formalism, consistent with the input and output modelling parameters, while the input reflection coefficient is preserved. In this sense, this is a 'true-amplitude' formalism. As with earlier Kirchhoff inversion, a slight modification of the kernel of KDM provides alternative integral operators for estimating the specular reflection angle, both in the input configuration and in the output configuration, thereby providing a basis for amplitude-versus-angle analysis of the data.     

The effects of source and receiver motion on seismic data1

The effects of source and receiver motion on seismic data are considered using extensions of the standard convolutional model. In particular, receiver motion introduces a time-variant spatial shift into data, while source motion converts the effect of the source signature from a single-channel convolution in time to a multichannel convolution in time and space. These results are consistent with classical Doppler theory and suggest that Doppler shifting can introduce distortions into seismic data even at relatively slow acquisition speeds. It is shown that, while both source and receiver motion are known to be important for marine vibroseis acquisition, receiver motion alone can produce significant artifacts in marine 3D data. Fortunately, the convolutional nature of the distortions renders them amenable to correction using simple deconvolution techniques. Specifically, the effects of receiver motion can be neutralized by applying an appropriate reverse time-variant spatial shift, while those due to source motion can be addressed by introducing time-variant spatial shifts both before and after standard, deterministic, signature deconvolution or correlation.