复杂介质小波多尺度井间地震层析成像方法研究

复杂介质井间地震层析成像是一个很复杂的非线性反 演问题，常规的线性化反演方法无法得到好的解. 采用基于图形的弯曲射线追踪方法， 并将小波多尺度思想引入到井间层析成像，提出了小波多尺度井间地震层析成像方法，很好 地解决了非线性成像的难题，提高了图像的质量和分辨率. 物理模型实验结果表明， 该方法适合于复杂介质成像，并具有良好的实用性和效果.     

起伏地形下的高精度反射波走时层析成像方法

全球造山带及中国大陆中西部普遍具有强烈起伏的地形条件.复杂地形条件下的地壳结构成像问题像一面旗帜引领了当前矿产资源勘探和地球动力学研究的一个重要方向.深地震测深记录中反射波的有效探测深度可达全地壳乃至上地幔顶部,而初至波通常仅能探测上地壳浅部.为克服和弥补初至波探测深度的不足,本文基于前人对复杂地形条件下初至波成像的已有研究成果,采用数学变换手段将笛卡尔坐标系的不规则模型映射到曲线坐标系的规则模型,并将快速扫描方法与分区多步技术相结合,发展了反射波走时计算和射线追踪的方法.进而利用反射波走时反演,实现起伏地形下高精度的速度结构成像,从而为起伏地形下利用反射波数据高精度重建全地壳速度结构提供了一种全新方案.数值算例从正演计算精度、反演中初始模型依赖性、反演精度、纵横向分辨率以及抗噪性等方面验证了算法的正确性和可靠性.     

基于高维连续小波变换的地震资料不连续性检测方法研究

断层等不连续性结构的检测在地震勘探中具有重要的意义.本文简单介绍了高维连续小波变换的基本理论,包括:高维连续小波变换的定义、高维小波变换系数的切片以及快速实现方法等,利用典型的合成信号说明了高维连续小波变换具有更好的方向选择性(相比于常用的高维张量积小波变换),将高维连续小波变换引入地震资料不连续性检测,并提出了利用小尺度高维连续小波变换系数检测地震资料不连续性的方法,同时给出了方法的实现流程.合成信号以及实际三维地震数据处理效果验证了本文所提方法的有效性.     

叠前地震数据特征波场分解、偏移成像与层析反演

本文提出了一套叠前地震数据稀疏表达(特征波场合成)、深度偏移成像和层析成像的处理流程.不同于传统的变换域中的数据稀疏表达理论,本文利用局部平面波的传播方向(慢度矢量),在中心炮检点处同时进行波束合成,从而将地震数据投影到局部平面波域(高维空间)中.由于波束合成后的地震数据描述了局部平面波的方向特征,因此称之为特征波场.然而波束合成算法需要估计局部平面波的慢度矢量.当地震数据受噪声干扰时,难以在常规τ-p谱中自动估计局部平面波的射线参数(慢度矢量).本文提出了基于反演理论的特征波场合成方法,可以同时反演局部平面波及其传播方向,从而提高特征波合成的自动化程度并保持方法的稳健性.通过特征波场合成,可以将地震数据分解为单独的震相(波形).这样的数据可以直接用来成像及反演.在局部平面波域中,由于局部平面波的入射与出射射线参数已知,传统的Kirchhoff叠前深度偏移(PSDM)和高斯束/控制束PSDM可以实现从"沿等时面的画弧"到"向反射点(段)的直接投影"的转变,叠前偏移的效率以及成像质量可以同时提高.此外,特征波场与地下反射点(段)的一对一映射关系使得叠前深度偏移与层析成像融为一体,可以极大地提高速度反演的效率.数值试验证明了特征波场合成、叠前深度成像以及层析反演的有效性.     

离散小波变换与重力异常多重分解

小波变换多尺度分析是位场分解的有益工具.离散二维小波变换产生的低阶小波细节具有尺度不变的特征,它们不随小波变换的总阶数改变,而总阶数的增加仅增加高阶小波细节的个数和改变最后的高阶逼近.因此,用小波变换分解重力异常时,可根据地质目的来组合小波细节,从而实现有地质意义的异常分解.实验表明,用小波变换分解的重力异常小波细节,同样起到功率谱分解的作用,用分解之后的小波细节功率谱可以精确确定场源的埋深.中国大陆科学钻探场地的重力异常分解给出局部异常分解的典型例子.     

联合小波变换与偏振分析自动拾取微地震P波到时

对微地震P波到时的自动拾取是微地震信号分析和数据处理的主要目标之一。基于小波变换的多尺度分析思想,对微地震信号进行小波处理后的小波系数代替原始信号,应用包含在小波变换系数中的信号偏振信息,提出了联合小波变换与偏振分析自动拾取微地震信号P波到时的方法。通过对嘉阳煤矿监测的实际微地震数据进行小波变换,用多尺度小波分解的各个尺度单支重构信号构成协方差矩阵,求解不同尺度协方差矩阵的最大特征值和次大特征值求取P波到时定位函数,实现P波到时的自动拾取,取得了满意的结果.     

地震波形多尺度反演的一点讨论

基于在反演过程中对初始模型依赖性强、易陷入局部极值等问题,本文引入小波分析,提出多尺度地震波形反演方法,从而将参数反演问题转化到小波域中重要系数优化问题。利用多尺度之间的内在联系及小波域中重要系数的稀疏性,有将改进了局部极值、计算量等问题。并对几种多尺度反演策略进行了比较讨论。基于波动方程正演及褶积模型的两种反演方法的数值实便结果显示了本方法良好的效果。     

海洋拖缆地震资料初至波走时层析反演

初至波走时层析反演技术作为建立近地表速度模型的重要手段,是解决陆地资料复杂静校正问题的关键技术。而折射波广泛发育的海洋地震资料,对折射波信息的关注与运用并没有得到广泛的重视。本文首次将层析反演方法应用于海洋拖缆地震数据的近海底速度模型的建立。本文方法与陆地资料层析反演的主要区别在于:①在震源信号的最小相位化处理后进行初至时间的拾取,避免了混合相位子波初至拾取不准带来的误差;②以海水深度与海水速度作为反演约束条件,减小了迭代误差。实测二维资料的层析反演结果表明,本文方法可反演出较为精确的海洋地层速度结构。      

Borehole radar velocity inversion using cokriging and cosimulation

A new radar velocity tomography method is presented based on slowness covariance modeling and cokriging of the slowness field using only measured travel time data. The proposed approach is compared to the classical LSQR algorithm using various synthetic models and a real data set. In each case, the proposed method provides comparable to or better results than LSQR. One advantage of this approach is that it is self-regularized and requires less a priori information. The covariance model also allows stochastic imaging of slowness fields by geostatistical simulations. Stable characteristics and uncertain features of the inverted models can then be easily identified.     

基于改进反射系数近似方程的纵横波阻抗同步反演

基于地震波反射系数近似公式的叠前反演是油气勘探的重要工具.本文在已有研究的基础上,推导了一个改进的射线参数域地震纵波反射系数近似方程.该方程建立了地震纵波反射系数与纵波阻抗和横波阻抗的非线性关系,在中、小角度的范围内较现有的反射系数线性近似公式精度更高.另外,由于该方程仅包含纵波和横波阻抗反射系数项,因此基于新方程的反演能够有效地降低同步反演纵波速度、横波速度、密度三个参数的不适定性.在此基础上,结合广义线性反演法(GLI)理论和贝叶斯理论,相应地发展了一种叠前地震同步反演方法.模型测试和实际资料的应用表明,基于新方程的反演方法能够利用有限角度(偏移距)的数据稳定地反演纵波和横波阻抗,由于在反演过程中,不需要假设纵横波速度为常数,因此该方法还能有效地提高反演结果的精度.     

Geostatistical traveltime tomography in elliptically anisotropic media

In geological materials, anisotropy may arise due to different mechanisms and can be found at different scales. Neglecting anisotropy in traveltime tomographic reconstruction leads to artefacts that can obscure important subsurface features. In this paper, a geostatistical tomography algorithm to invert cross‐hole traveltime data in elliptically anisotropic media is presented. The advantages of geostatistical tomography are that the solution is regularized by the covariance of the model parameters, that known model parameters can be used as constraints and fitted exactly or within a prescribed variance and that stochastic simulations can be performed to appraise the variability of the solution space. The benefits of the algorithm to image anisotropic media are illustrated by two examples using synthetic georadar data and real seismic data. The first example confirms suspected electromagnetic anisotropy in the vadose zone caused by relatively rapid water content variations with respect to wavelength at georadar frequencies. The second presents how sonic log data can be used to constrain the inversion of cross‐well seismic data and how geostatistical simulations can be used to infer parameter uncertainty. Results of both examples show that considering anisotropy yields a better fit to the data at high ray angles and reduces reconstruction artefacts.     

基于矩阵Toeplitz稀疏分解的相对波阻抗反演方法

针对利用地震道进行相对波阻抗反演中遇到的横向连续性难以保持、初始子波容错度差以及随机噪声干扰影响反演结果等问题,提出了一种基于矩阵Toeplitz稀疏分解的相对波阻抗反演方法.该方法将地震数据剖面的Toeplitz稀疏分解问题分解为两个子反演问题,其一以Toeplitz子波矩阵元素为待反演的参数,用Fused Lasso方法求解,可保证子波具有紧支集且是光滑的;其二以稀疏反射系数矩阵元素为待反演参数,用基于回溯的快速萎缩阈值迭代算法求解,大大降低了目标函数中参数选择的难度.通过交替迭代求解上述两个子反演问题可将地震数据剖面因式分解为一个Toeplitz子波矩阵和一个稀疏反射系数矩阵;然后由反射系数矩阵递推反演可以得到高分辨率的相对波阻抗剖面;利用测井资料加入低频分量后,也可得到高分辨率的绝对波阻抗剖面.Marmousi2模型生成的合成记录算例和实际地震资料算例均表明:本文方法可以从带限地震数据中有效地反演相对波阻抗,反演结果分辨率高并且能够很好地保持地震数据的横向连续性;即使在初始估计子波存在误差和地震数据被随机噪声污染的情况下也能取得较好的效果.     

Traveltime seismic tomography with adaptive wavelet parameterization

An algorithm for solving the inverse kinematic problem of traveltime seismic tomography is developed and tested. The algorithm is intended for imaging the three-dimensional (3D) velocity model composed of a layer underlain by a half-space. This algorithm considers the bottom boundary of the layer as a first-order seismic velocity discontinuity with unknown position that has to be determined in the inversion together with the velocity variations inside the overlying layer and the sub-interface boundary velocities. The inversion can be applied to the travel times of refracted, head and reflected waves. The main idea behind the algorithm is the adaptive parameterization of the medium by the sparse Haar wavelet series expansion. In order to throw off the poorly resolved coefficients of expansion, we suggest using two empirical local resolution measures: the number of seismic rays crossing the support of the corresponding wavelet support area and their angular coverage, i.e., the spread in the azimuths of these rays. The adequacy of these measures is tested by their comparison with the estimation of the diagonal elements of the resolution matrix on the synthetic examples. This comparison proved that the proposed measures can be successfully applied for statistical estimation of the resolution and for constructing the adaptive parameterization. It was shown also that the best results are achieved while using the number of rays normalized to the size of the wavelet support together with their angular coverage. An automated procedure for throwing off poorly resolved unknowns is developed. The parameters of this procedure can be tuned to provide the desired level of detail of the model to be reconstructed. The synthetic checkerboard testing proved the efficiency of the algorithm. The proposed algorithm can be applied to solve different types of problems, including regional seismic studies, as well as exploration and engineering seismology. The use of this algorithm is especially convenient when the medium is essentially three-dimensional and when the conventional seismic methods implying regular network measurements directly above the studied structure (such as the common depth point method) are inapplicable, e.g., in the seismic studies of the foundations of buildings and in rugged terrains.     

多频段组合菲涅尔带走时层析成像方法研究

针对传统射线层析存在的种种局限性,菲涅尔带走时层析成像摒弃了传统的数学射线,考虑到地震信号具有一定的频带宽度,中央射线附近的介质对地震波的传播产生不同程度的影响。本文提出了多频段组合菲涅尔带走时层析成像方法。该方法以频率域波动方程Born和Rytov近似为基础,推导出建立在带限地震波理论基础上的波动方程 Rytov 近似走时敏感核函数,实现第一菲涅尔带约束下的波动方程走时层析反演方法。同时由于多个频段的引入,充分利用低频段和高频段的特有优势,从而兼顾菲涅尔带层析的计算效率与分辨率。模型试算结果证明了本方法的有效性和稳定性。     

Gabor‐frame‐based Gaussian packet migration

We present a Gaussian packet migration method based on Gabor frame decomposition and asymptotic propagation of Gaussian packets. A Gaussian packet has both Gaussian‐shaped time–frequency localization and space–direction localization. Its evolution can be obtained by ray tracing and dynamic ray tracing. In this paper, we first briefly review the concept of Gaussian packets. After discussing how initial parameters affect the shape of a Gaussian packet, we then propose two Gabor‐frame‐based Gaussian packet decomposition methods that can sparsely and accurately represent seismic data. One method is the dreamlet–Gaussian packet method. Dreamlets are physical wavelets defined on an observation plane and can represent seismic data efficiently in the local time–frequency space–wavenumber domain. After decomposition, dreamlet coefficients can be easily converted to the corresponding Gaussian packet coefficients. The other method is the Gabor‐frame Gaussian beam method. In this method, a local slant stack, which is widely used in Gaussian beam migration, is combined with the Gabor frame decomposition to obtain uniform sampled horizontal slowness for each local frequency. Based on these decomposition methods, we derive a poststack depth migration method through the summation of the backpropagated Gaussian packets and the application of the imaging condition. To demonstrate the Gaussian packet evolution and migration/imaging in complex models, we show several numerical examples. We first use the evolution of a single Gaussian packet in media with different complexities to show the accuracy of Gaussian packet propagation. Then we test the point source responses in smoothed varying velocity models to show the accuracy of Gaussian packet summation. Finally, using poststack synthetic data sets of a four‐layer model and the two‐dimensional SEG/EAGE model, we demonstrate the validity and accuracy of the migration method. Compared with the more accurate but more time‐consuming one‐way wave‐equation‐based migration, such as beamlet migration, the Gaussian packet method proposed in this paper can correctly image the major structures of the complex model, especially in subsalt areas, with much higher efficiency. This shows the application potential of Gaussian packet migration in complicated areas.     

Tomography and the Herglotz-Wiechert inverse formulation

In this paper, linearized tomography and the Herglotz-Wiechert inverse formulation are compared. Tomographic inversions for 2-D or 3-D velocity structure use line integrals along rays and can be written in terms of Radon transforms. For radially concentric structures, Radon transforms are shown to reduce to Abel transforms. Therefore, for straight ray paths, the Abel transform of travel-time is a tomographic algorithm specialized to a one-dimensional radially concentric medium. The Herglotz-Wiechert formulation uses seismic travel-time data to invert for one-dimensional earth structure and is derived using exact ray trajectories by applying an Abel transform. This is of historical interest since it would imply that a specialized tomographic-like algorithm has been used in seismology since the early part of the century (seeHerglotz, 1907;Wiechert, 1910). Numerical examples are performed comparing the Herglotz-Wiechert algorithm and linearized tomography along straight rays. Since the Herglotz-Wiechert algorithm is applicable under specific conditions, (the absence of low velocity zones) to non-straight ray paths, the association with tomography may prove to be useful in assessing the uniqueness of tomographic results generalized to curved ray geometries.     

基于初至波走时层析成像的Tikhonov正则化与梯度优化算法

初至波走时层析成像是利用地震初至波走时和其传播的射线路径来反演地下介质速度的技术.该问题本质上是一个不适定问题,需要使用正则化方法并辅之以适当的最优化技巧.本文从数值优化的角度介绍了初至波走时层析成像的反演原理,建立了Tikhonov正则化层析成像反演模型并提出求解极小化问题的加权修正步长的梯度下降算法.该方法可以从速度模型的可行域中迭代找到一个最优解.数值试验表明,该方法是可行和有应用前景的.     

Automatic cross-well tomography: an application of the differential semblance optimization to two real examples

An automatic tomography algorithm, based on differential semblance optimization (DSO), has been used to invert real cross-well seismic data for the background velocity. The method relies on the first-arrival transmitted waves. Given a background velocity model, the traveltimes between the sources and the receivers are computed, then semblance panels are created by back-propagating the data traces. If the velocity model is correct all the first-arrival transmitted waves will be aligned in the semblance panels. The DSO method consists of finding the background velocity by minimizing the L ₂-norm of the difference between adjacent back-propagated traces. Thanks to the good behaviour of this DSO cost function about the solution, a local (gradient) optimization can be performed. This provides a relatively fast algorithm when ray tracing and analytic computation of the gradient are used.
Unfortunately the method fails in the presence of caustics in the data. However, this difficulty can be circumvented by applying suitable masks to the data. This approach is first applied to a synthetic example then to two real data sets: the McElroy data set recorded in West Texas and the NIMR data set recorded in Oman. The results are quite encouraging and similar to those obtained with classical tomography.     

Crosshole ultrasonic tomography and its application to karst investigation

Crosshole ultrasonic tomography is referred to ray tracing by gilding method and image reconstruction by combining the successively linearized iteration with damping least-squares QR decomposition, with which the result has better precision than that with crosshole seismic tomography by using the same inversion method in engineering geological investigation. It has been proved in practice that the investigation with crosshole ultrasonic tomography can clearly show the location and shape of the abnormal geological unit with the volume more than 60 cm when the crosshole distance exceeds 30 m. The result of investigation has been confirmed by the drilling. The crosshole ultrasonic tomography method will be extensively used in the engineering geological investigation.     

Wave-equation migration velocity analysis. I. Theory

We present a migration velocity analysis (MVA) method based on wavefield extrapolation. Similarly to conventional MVA, our method aims at iteratively improving the quality of the migrated image, as measured by the flatness of angle‐domain common‐image gathers (ADCIGs) over the aperture‐angle axis. However, instead of inverting the depth errors measured in ADCIGs using ray‐based tomography, we invert ‘image perturbations’ using a linearized wave‐equation operator. This operator relates perturbations of the migrated image to perturbations of the migration velocity. We use prestack Stolt residual migration to define the image perturbations that maximize the focusing and flatness of ADCIGs. Our linearized operator relates slowness perturbations to image perturbations, based on a truncation of the Born scattering series to the first‐order term. To avoid divergence of the inversion procedure when the velocity perturbations are too large for Born linearization of the wave equation, we do not invert directly the image perturbations obtained by residual migration, but a linearized version of the image perturbations. The linearized image perturbations are computed by a linearized prestack residual migration operator applied to the background image. We use numerical examples to illustrate how the backprojection of the linearized image perturbations, i.e. the gradient of our objective function, is well behaved, even in cases when backprojection of the original image perturbations would mislead the inversion and take it in the wrong direction. We demonstrate with simple synthetic examples that our method converges even when the initial velocity model is far from correct. In a companion paper, we illustrate the full potential of our method for estimating velocity anomalies under complex salt bodies.