频率多尺度全波形速度反演

以二维声波方程为模型,在时间域深入研究了全波形速度反演.全波形反演要解一个非线性的最小二乘问题,是一个极小化模拟数据与已知数据之间残量的过程.针对全波形反演易陷入局部极值的困难,本文提出了基于不同尺度的频率数据的"逐级反演"策略,即先基于低频尺度的波场信息进行反演,得出一个合理的初始模型,然后再利用其他不同尺度频率的波场进行反演,并且用前一尺度的迭代反演结果作为下一尺度反演的初始模型,这样逐级进行反演.文中详细阐述和推导了理论方法及公式,包括有限差分正演模拟、速度模型修正、梯度计算和算法描述,并以Marmousi复杂构造模型为例,进行了MPI并行全波形反演数值计算,得到了较好的反演结果,验证了方法的有效性和稳健性.     

井间电磁测量的2．5维层析成像方法

利用正则化最小二乘反演方法实现了井间电磁测量数据的层析成像,对井间地层电阻率进行了重建。在成像算法中,我们假设了井间电磁的激发与接收采用电磁偶极子源,井间介质仅在二维（xoz）平面内变化。在数值模拟中,通过对构造走向（y方向）的Fourier变换,将三维电磁场问题转化为一系列二维问题,用等参有限元方法在波数域求解,使实际地层模型的处理得以实现。对于波数域中每个波数对应的电磁场方程采用等参有限元求解,并用高斯积分将波数域解变换为空间域电磁场。利用源与接收器电磁场的互易原理,实现了电磁场响应对电导率分布灵敏度的快速计算。针对正演模拟中源点的奇异性,我们采用具有一定面积的伪艿函数表达源电流分布,使数值解精度得到提高。用层状介质的解析解与数值计算结果的对比,验证了模拟算法的精度。用介质扰动产生的电磁场变化检验互易性定理计算灵敏度的有效性。对简单块状模型、斜向裂缝带模型及“大”字模型的模拟数据成像结果表明,本文介绍的层析成像方法是正确有效的。     

THE NON-LINEAR INVERSION OF SEISMIC WAVEFORMS CAN BE PERFORMED EITHER BY TIME EXTRAPOLATION OR BY DEPTH EXTRAPOLATION1

The classical aim of non-linear inversion of seismograms is to obtain the earth model which, for null initial conditions and given sources, best predicts the observed seismograms. This problem is currently solved by an iterative method: each iteration involves the resolution of the wave equation with the actual sources in the current medium, the resolution of the wave equation, backwards in time, with the current residuals as sources; and the correlation, at each point of space, of the two wavefields thus obtained. Our view of inversion is more general: we want to obtain a whole set of earth model, initial conditions, source functions, and predicted seismograms, which are the closest to some a priori values, and which are related through the wave equation. It allows us to justify the previous method, but it also allows us to set the same inverse problem in a different way: what is now searched for is the best fit between calculated and a priori initial conditions, for given sources and observed surface displacements. This leads to a completely different iterative method, in which each iteration involves the downward extrapolation of given surface displacements and tractions, down to a given depth (the‘bottom’), the upward extrapolation of null displacements and tractions at the bottom, using as sources the initial time conditions of the previous field, and a correlation, at each point of the space, of the two wavefields thus obtained. Besides the theoretical interest of the result, it opens the way to alternative numerical methods of resolution of the inverse problem. If the non-linear inversion using forward-backward time propagations now works, this non-linear inversion using downward-upward extrapolations will give the same results but more economically, because of some tricks which may be used in depth extrapolation (calculation frequency by frequency, inversion of the top layers before the bottom layers, etc.).     

基于三维应变格林函数反演中小震震源机制

随着复杂速度结构反演的发展和高性能计算能力的提升,基于高精度3D介质模型计算格林函数反演震源机制更具可行性。中小地震因具有更好的覆盖和近似点源效应,在区域结构成像中有着广泛的应用。基于波形类的反演方法如波动方程层析成像\,全波形反演都需要震源机制解,而传统的震源机制反演方法不能很好地应用于中小地震。采用有限差分法构建应变格林张量(Strain Green Tensor,SGT)数据库,将合成波形和实际波形按震相截窗并滤波到不同的频带范围,先通过最小化互相关走时差来进行震源重定位,再通过最小化波形残差反演震源机制。通过合成数据测试验证方法的正确性,随后将该方法应用于青藏高原东部边缘龙门山地区,反演一系列M_W3.4～5.7的中小地震震源机制。由于应变格林张量数据库可预先构建,该方法可以应用于(近)实时震源机制解反演。     

时间域航空电磁2.5维非线性共轭梯度反演

对于时间域航空电磁法二维和三维反演来说,最大的困难在于有效的算法和大的计算量需求.本文利用非线性共轭梯度法实现了时间域航空电磁法2.5维反演方法,着重解决了迭代反演过程中灵敏度矩阵计算、最佳迭代步长计算、初始模型选取等问题.在正演计算中,我们采用有限元法求解拉式傅氏域中的电磁场偏微分方程,再通过逆拉氏和逆傅氏变换高精度数值算法得到时间域电磁响应.在灵敏度矩阵计算中,采用了基于拉式傅氏双变换的伴随方程法,时间消耗只需计算两次正演,从而节约了大量计算时间.对于最佳步长计算,二次插值向后追踪法能够保证反演迭代的稳定性.设计两个理论模型,检验反演算法的有效性,并讨论了选择不同初始模型对反演结果的影响.模型算例表明:非线性共轭梯度方法应用于时间域航空电磁2.5维反演中稳定可靠,反演结果能够有效地反映地下真实电性结构.当选择的初始模型电阻率值与真实背景电阻率值接近时,能得到较好的反演结果,当初始模型电阻率远大于或远小于真实背景电阻率值时反演效果就会变差.     

估计辐射参数的井间电磁波层析成像技术

为了避免使用不合理初始辐射场强和方向性因子带来的误差,研究了估计辐射参数的井间电磁波层析成像技术.通过时域有限差分法模拟表明,天线长度与波长的比值、钻孔充填情况、钻孔周围介质的物性均会影响偶极天线的初始辐射场强或方向性因子;为此结合已知的分层资料,将它们设为未知参数,并设定初始辐射场强与发射点位置相关,方向性因子随射线角度而变化;采用正则化反演方法,由钻孔资料建立了模型方差目标函数,使得反演结果与钻遇的地质特征保持一致.通过理论模型试验和实例应用分析表明,相对于传统射线层析成像方法,估计辐射参数的正则化层析成像技术有助于提高反演的准确性.     

基于对数目标函数的跨孔雷达频域波形反演

波形反演在探地雷达领域的应用已有十余年历史,但绝大部分算例属于时间域波形反演.频率域波形反演由于能够灵活地选择迭代频率并可以使用不同类型的目标函数,因而更加多样化.本文的频率域波形反演基于时间域有限差分(FDTD)法,采用对数目标函数,可在每一次迭代过程中同时或者单独反演介电常数和电导率.文中详细推导了频率域波形反演的理论公式,给出对数目标函数下的梯度表达式,并使用离散傅氏变换(DFT)实现数据的时频变换,能够有效地减少大模型反演的内存需求.在后向残场源的时频域转换过程中,提出仅使用以当前频点为中心的一个窄带数据,可以消除高频无用信号的干扰,获得可靠的反演结果.为加速收敛,采用每迭代十次则反演频率跳跃一定频带宽度的反演策略.实验证明适当的频率跳跃能够在不降低分辨率的基础上有效地提高反演效率.通过两组不同情形下合成数据反演的分析对比,证明基于对数目标函数的波形反演结果准确可靠.最后,将该方法应用到一组实际数据,得到较好的反演结果.     

Analysis of the traveltime sensitivity kernels for an acoustic transversely isotropic medium with a vertical axis of symmetry

In anisotropic media, several parameters govern the propagation of the compressional waves. To correctly invert surface recorded seismic data in anisotropic media, a multi‐parameter inversion is required. However, a tradeoff between parameters exists because several models can explain the same dataset. To understand these tradeoffs, diffraction/reflection and transmission‐type sensitivity‐kernels analyses are carried out. Such analyses can help us to choose the appropriate parameterization for inversion. In tomography, the sensitivity kernels represent the effect of a parameter along the wave path between a source and a receiver. At a given illumination angle, similarities between sensitivity kernels highlight the tradeoff between the parameters. To discuss the parameterization choice in the context of finite‐frequency tomography, we compute the sensitivity kernels of the instantaneous traveltimes derived from the seismic data traces. We consider the transmission case with no encounter of an interface between a source and a receiver; with surface seismic data, this corresponds to a diving wave path. We also consider the diffraction/reflection case when the wave path is formed by two parts: one from the source to a sub‐surface point and the other from the sub‐surface point to the receiver. We illustrate the different parameter sensitivities for an acoustic transversely isotropic medium with a vertical axis of symmetry. The sensitivity kernels depend on the parameterization choice. By comparing different parameterizations, we explain why the parameterization with the normal moveout velocity, the anellipitic parameter η, and the δ parameter is attractive when we invert diving and reflected events recorded in an active surface seismic experiment.     

基于GPU并行的时间域全波形优化共轭梯度法快速GPR双参数反演

探地雷达（GPR）时间域全波形反演计算量巨大,内存要求高,在微机上计算难度大.本文中作者基于GPU并行加速的维度提升反演策略,采用优化的共轭梯度法,避免了Hessian矩阵的计算,在普通微机上实现了时间域全波形二维GPR双参数（介电常数和电导率）快速反演.论文首先推导了二维TM波的时域有限差分法（FDTD）的交错网格离散差分格式及波场更新策略.然后,基于Lagrange乘数法,将约束问题转化为无约束最小问题,构建了共轭梯度法反演目标函数,采用Fletcher-Reeves公式与非精确线搜索Wolfe准则,确保了梯度方向修正因子及迭代步长选取的合理性.而GPU并行计算及维度提升反演策略的应用,数倍地提升了反演速度.最后,开展了3个模型的合成数据的反演实验,分别从观测方式、梯度优化及天线频率等方面,分析了这些因素对雷达全波形反演的影响,说明双参数的反演较单一的介电常数反演,能提供更丰富的信息约束,有效提高模型重建的精度.     

地层衰减对地震波速度逆散射反演的影响研究

在利用地震波数据进行地球物理反演时,地层对地震波的吸收衰减效应会对地层物性参数的准确反演产生较大的影响,因此利用黏弹性声波方程进行反演更符合实际情形.本文在考虑地层衰减效应进行频率空间域正演模拟的基础上,提出基于黏弹性声波方程的频率域逆散射反演算法并对地震波传播速度进行反演重建,在反演过程中分别用地震波传播复速度和实速度来表征是否考虑地层吸收衰减效应.基于反演参数总变差的正则化处理使反演更加稳定,在反演中将低频反演速度模型作为高频反演的背景模型进行逐频反演,由于单频反演过程中背景模型保持不变,故该方法不需要在每次迭代中重新构造正演算子,具有较高的反演效率;此外本文在反演过程中采用了基于MPI的并行计算策略,进一步提高了反演计算的效率.在二维算例中分别对是否考虑地层吸收衰减效应进行了地震波速度反演,反演结果表明考虑衰减效应可以得到与真实模型更加接近的速度分布结果,相反则无法得到正确的地震波速度重建结果.本文算法对复杂地质模型中浅层可以反演得到分辨率较高的速度模型,为其他地震数据处理提供比较准确的速度信息,在地层深部由于地震波能量衰减导致反演分辨率不太理想.     

基于概率成像技术的低纬度磁异常化极方法

化极转换是磁异常解释的重要基础,为了克服在地磁纬度较低的地区尤其是磁赤道附近化极不稳定的问题,出现了多种化极方法．本文基于概率成像技术提出了一种等效物性的反演方法,实现对地下等效场源的反演成像,取得了对低纬度磁异常稳定化极的效果．化极反演中逐次对剩余异常进行反演成像,实现由概率模型到物性模型的复杂映射,避免了类似反演中需要大型方程组求解等问题,并将概率模型的构制、物性参数的反演和反演评价有机地集成到一起,加速了反演成像的进程,使反演成像速度与目前概率成像的计算速度达到可相比拟的程度．对理论模型和实际资料的计算表明,该方法对低纬度磁异常化极处理是稳定有效的,而且可以较好地压制噪声干扰,能够在噪声干扰条件下进行反演化极．     

基于Contourlet域自适应Wiener阈值的同时震源波场分离

同时震源数据包含了多炮之间的串扰噪声,不能直接用于常规数据处理流程.因此,需要对混叠的波场进行分离得到常规采集的单炮记录.本文基于稀疏迭代反演分离,提出了一种具有尺度与空间自适应的Wiener阈值选取方法.该阈值选取方法能够根据不同迭代环境计算不同尺度下串扰噪声的方差和不同空间位置有效信号的方差,从而自适应调整阈值大小,最终通过对变换域系数进行收缩来达到去除串扰噪声的目的.理论模型数据和实际数据测试结果表明,本文方法能够快速有效地压制串扰噪声和保护弱有效信号,取得了比Contourlet域子带一致Wiener阈值方法和Curvelet域指数衰减阈值方法更好的分离效果.     

地面矩形大定源电磁法频率域三维非线性共轭梯度反演

本文实现了地面矩形大定源三维频率域反演.矩形大定源三维模型响应计算采用交错网格有限差分技术.正演的微分方程为异常电场满足的非齐次Helmholtz方程,方程右手边源项中的大定源产生的背景格林函数由虚界面法结合虚框法计算.频率域三维反演采用非线性共轭梯度反演技术.反演的数据类型为垂直磁场的频率域响应Hz的实部和虚部分量.数值结果表明,(1)三维模型正演模拟数值结果与前人一致,为三维反演奠定基础;(2)针对两个三维导电模型,分别进行了三维反演数值试算.反演结果可以清晰恢复出异常体的电阻率和位置信息,表明地面矩形大定源三维频率域非线性共轭梯度反演具有可行性.本文研究的意义在于,在电磁响应时频转换技术的基础上,如果将野外实测的瞬变电磁数据变换为对应的频率响应,则结合本文提出的三维反演技术,可以为矩形大定源瞬变电磁数据的三维解释提供一个新的思路.     

Non-linear three-dimensional inversion of cross-well electrical measurements

Cross-well electrical measurement as known in the oil industry is a method for determining the electrical conductivity distribution between boreholes from the electrostatic field measurements in the boreholes. We discuss the reconstruction of the conductivity distribution of a three-dimensional domain. The measured secondary electric potential field is represented in terms of an integral equation for the vector electric field. This integral equation is taken as the starting point to develop a non-linear inversion method, the so-called contrast source inversion (CSI) method. The CSI method considers the inverse scattering problem as an inverse source problem in which the unknown contrast source (the product of the total electric field and the conductivity contrast) in the object domain is reconstructed by minimizing the object and data error using a conjugate-gradient step, after which the conductivity contrast is updated by minimizing only the error in the object. This method has been tested on a number of numerical examples using the synthetic 'measured' data with and without noise. Numerical tests indicate that the inversion method yields a reasonably good reconstruction result, and is fairly insensitive to added random noise.     

Effects of the sea floor topography on the 1D inversion of time‐domain marine controlled source electromagnetic data

Time‐domain marine controlled source electromagnetic methods have been used successfully for the detection of resistive targets such as hydrocarbons, gas hydrate, or marine groundwater aquifers. As the application of time‐domain marine controlled source electromagnetic methods increases, surveys in areas with a strong seabed topography are inevitable. In these cases, an important question is whether bathymetry information should be included in the interpretation of the measured electromagnetic field or not. Since multi‐dimensional inversion is still not common in time‐domain marine controlled source electromagnetic methods, bathymetry effects on the 1D inversion of single‐offset and multi‐offset joint inversions of time‐domain controlled source electromagnetic methods data are investigated. We firstly used an adaptive finite element algorithm to calculate the time‐domain controlled source electromagnetic methods responses of 2D resistivity models with seafloor topography. Then, 1D inversions are applied on the synthetic data derived from marine resistivity models, including the topography in order to study the possible topography effects on the 1D interpretation. To evaluate the effects of topography with various steepness, the slope angle of the seabed topography is varied in the synthetic modelling studies for deep water (air interaction is absent or very weak) and shallow water (air interaction is dominant), respectively. Several different patterns of measuring configurations are considered, such as the systems adopting nodal receivers and the bottom‐towed system. According to the modelling results for deep water when air interaction is absent, the 2D topography can distort the measured electric field. The distortion of the data increases gradually with the enlarging of the topography's slope angle. In our test, depending on the configuration, the seabed topography does not affect the 1D interpretation significantly if the slope angle is less or around 10°. However, if the slope angle increases to 30° or more, it is possible that significant artificial layers occur in inversion results and lead to a wrong interpretation. In a shallow water environment with seabed topography, where the air interaction dominates, it is possible to uncover the true subsurface resistivity structure if the water depth for the 1D inversion is properly chosen. In our synthetic modelling, this scheme can always present a satisfactory data fit in the 1D inversion if only one offset is used in the inversion process. However, the determination of the optimal water depth for a multi‐offset joint inversion is challenging due to the various air interaction for different offsets.     

2D acoustic‐elastic coupled waveform inversion in the Laplace domain

Although waveform inversion has been intensively studied in an effort to properly delineate the Earth's structures since the early 1980s, most of the time‐ and frequency‐domain waveform inversion algorithms still have critical limitations in their applications to field data. This may be attributed to the highly non‐linear objective function and the unreliable low‐frequency components. To overcome the weaknesses of conventional waveform inversion algorithms, the acoustic Laplace‐domain waveform inversion has been proposed. The Laplace‐domain waveform inversion has been known to provide a long‐wavelength velocity model even for field data, which may be because it employs the zero‐frequency component of the damped wavefield and a well‐behaved logarithmic objective function. However, its applications have been confined to 2D acoustic media. We extend the Laplace‐domain waveform inversion algorithm to a 2D acoustic‐elastic coupled medium, which is encountered in marine exploration environments. In 2D acoustic‐elastic coupled media, the Laplace‐domain pressures behave differently from those of 2D acoustic media, although the overall features are similar to each other. The main differences are that the pressure wavefields for acoustic‐elastic coupled media show negative values even for simple geological structures unlike in acoustic media, when the Laplace damping constant is small and the water depth is shallow. The negative values may result from more complicated wave propagation in elastic media and at fluid‐solid interfaces. Our Laplace‐domain waveform inversion algorithm is also based on the finite‐element method and logarithmic wavefields. To compute gradient direction, we apply the back‐propagation technique. Under the assumption that density is fixed, P‐ and S‐wave velocity models are inverted from the pressure data. We applied our inversion algorithm to the SEG/EAGE salt model and the numerical results showed that the Laplace‐domain waveform inversion successfully recovers the long‐wavelength structures of the P‐ and S‐wave velocity models from the noise‐free data. The models inverted by the Laplace‐domain waveform inversion were able to be successfully used as initial models in the subsequent frequency‐domain waveform inversion, which is performed to describe the short‐wavelength structures of the true models.     

全球地磁感应测深数据三维反演

全球地磁感应测深能获得地幔转换带及下地幔上部的导电结构.但目前稀疏的地磁台站分布及部分台站的观测数据稳定性较差,影响了三维反演对地下电性结构的分辨力和反演可靠性.为此,区别于传统的L2-范数反演方法,本文提出并实现了基于L1-范数的地磁测深响应三维反演技术.在反演中,利用L1-范数度量数据预测误差,降低"飞点"数据的影响,将相关系数较小的C-响应估计也纳入反演数据中.三维正演模拟采用球坐标系下的交错网格有限差分法,反演采用有限内存拟牛顿法.文中利用指数概率密度分布函数构造非高斯噪声的合成数据,并采用棋盘模型对反演方法的可靠性进行了验证.之后,我们将本文提出的三维反演方法用于全球129个地磁观测台站的C-响应数据反演,结果表明在地幔转换带深部,中国东北地区为高导电异常,南欧和北非则均为高阻;夏威夷在900km以下为高导;菲律宾海及以东地区在转换带表现为明显的高阻,这些结果与前人研究结果一致.由于采用了更多的台站数据,我们的反演结果还发现一些新的异常:南美洲南端,转换带表现为明显的高导;澳大利亚东南部,地幔转换带深部,也存在一个明显的高导异常,这些异常分布和地震层析成像的低速区一致.因此,L1-范数三维反演能够充分利用全球C-响应数据信息,提高地磁测深对地球深部电性结构的分辨能力,更好的研究全球地幔电性结构.     

三维密度界面的正反演研究和应用

重力位场的界面反演是位场处理解释中的重要问题.本文将基于快速傅里叶变换的频率域界面反演方法Parker-Oldenburg公式推广到物性可随深度变化的三维情况,得出了密度可以横向、纵向任意变化的重力界面正反演公式.该方法在计算时可以合理地选取地面下某一深度作为基准面以减小界面起伏,使迭代易于收敛.理论模型试验表明该方法反演精度高,收敛速度快,在密度界面反演中具有广泛的实用价值.最后利用该方法反演华北地区莫霍面的深度,反演结果得到了地震测深数据的验证.     

Preconditioned non‐linear conjugate gradient method for frequency domain full‐waveform seismic inversion

We present preconditioned non‐linear conjugate gradient algorithms as alternatives to the Gauss‐Newton method for frequency domain full‐waveform seismic inversion. We designed two preconditioning operators. For the first preconditioner, we introduce the inverse of an approximate sparse Hessian matrix. The approximate Hessian matrix, which is highly sparse, is constructed by judiciously truncating the Gauss‐Newton Hessian matrix based on examining the auto‐correlation and cross‐correlation of the Jacobian matrix. As the second preconditioner, we employ the approximation of the inverse of the Gauss‐Newton Hessian matrix. This preconditioner is constructed by terminating the iteration process of the conjugate gradient least‐squares method, which is used for inverting the Hessian matrix before it converges. In our preconditioned non‐linear conjugate gradient algorithms, the step‐length along the search direction, which is a crucial factor for the convergence, is carefully chosen to maximize the reduction of the cost function after each iteration. The numerical simulation results show that by including a very limited number of non‐zero elements in the approximate Hessian, the first preconditioned non‐linear conjugate gradient algorithm is able to yield comparable inversion results to the Gauss‐Newton method while maintaining the efficiency of the un‐preconditioned non‐linear conjugate gradient method. The only extra cost is the computation of the inverse of the approximate sparse Hessian matrix, which is less expensive than the computation of a forward simulation of one source at one frequency of operation. The second preconditioned non‐linear conjugate gradient algorithm also significantly saves the computational expense in comparison with the Gauss‐Newton method while maintaining the Gauss‐Newton reconstruction quality. However, this second preconditioned non‐linear conjugate gradient algorithm is more expensive than the first one.     

Accurate estimation of acoustic impedance based on spectral inversion

Acoustic impedance is one of the best attributes for seismic interpretation and reservoir characterisation. We present an approach for estimating acoustic impedance accurately from a band‐limited and noisy seismic data. The approach is composed of two stages: inverting for reflectivity from seismic data and then estimating impedance from the reflectivity inverted in the first stage. For the first stage, we achieve a two‐step spectral inversion that locates the positions of reflection coefficients in the first step and determines the amplitudes of the reflection coefficients in the second step under the constraints of the positions located in the first step. For the second stage, we construct an iterative impedance estimation algorithm based on reflectivity. In each iteration, the iterative impedance estimation algorithm estimates the absolute acoustic impedance based on an initial acoustic impedance model that is given by summing the high‐frequency component of acoustic impedance estimated at the last iteration and a low‐frequency component determined in advance using other data. The known low‐frequency component is used to restrict the acoustic impedance variation tendency in each iteration. Examples using one‐ and two‐dimensional synthetic and field seismic data show that the approach is flexible and superior to the conventional spectral inversion and recursive inversion methods for generating more accurate acoustic impedance models.