地震波场反演的BG－逆散射方法

本文讨论利用三维反射地震数据进行波场反演的一种方法，旨在取得高分辨率的地球模型．这种方法用Ｂａｃｋｕｓ－Ｇｉｌｂｅｒｔ的理论构造波动方程非线性反问题的逐次线性化迭代格式，用逆散射原理导出泛函的Ｆｒｅｃｈｅｔ导数，并用最佳折衷准则求解线性化后的方程组．根据迭代过程中不断提高分辨率的思想和减少计算成本的原则，设计了可供实用的反演算法流程．     

地震波场反演的BG－逆散射方法

本文讨论利用三维反射地震数据进行波场反演的一种方法,旨在取得高分辨率的地球模型．这种方法用Ｂａｃｋｕｓ－Ｇｉｌｂｅｒｔ的理论构造波动方程非线性反问题的逐次线性化迭代格式,用逆散射原理导出泛函的Ｆｒｅｃｈｅｔ导数,并用最佳折衷准则求解线性化后的方程组．根据迭代过程中不断提高分辨率的思想和减少计算成本的原则,设计了可供实用的反演算法流程．     

地震波场反演的BG－逆散射方法

本文讨论利用三维反射地震数据进行波场反演的一种方法，旨在取得高分辨率的地球模型．这种方法用Ｂａｃｋｕｓ－Ｇｉｌｂｅｒｔ的理论构造波动方程非线性反问题的逐次线性化迭代格式，用逆散射原理导出泛函的Ｆｒｅｃｈｅｔ导数，并用最佳折衷准则求解线性化后的方程组．根据迭代过程中不断提高分辨率的思想和减少计算成本的原则，设计了可供实用的反演算法流程．     

参考波速线性变化时的声波方程逆散射反演

声波方程的逆散射反演乃是求解双曲型偏微分方程系数项反问题的一种解析方法,一般利用Born近似把这一非线性反问题线性化,并给出了恒参考波速介质中反问题解的解析表达式.由于Born近似假定波速扰动为一级无穷小,因此,在大多数情况下,恒参考波速介质模型的反问题的解无法得以应用.本文研究介质参考波速沿某个方向线性变化时的声散射理论,导出了声波方程逆散射问题解的解析表达式,从而既可使Born近似的假定在大多数情况下能得以满足,又可利用快速Fourier变换快速实现介质波速扰动的反演成象.     

参考波速线性变化时的声波方程逆散射反演

声波方程的逆散射反演乃是求解双曲型偏微分方程系数项反问题的一种解析方法,一般利用Born近似把这一非线性反问题线性化,并给出了恒参考波速介质中反问题解的解析表达式.由于Born近似假定波速扰动为一级无穷小,因此,在大多数情况下,恒参考波速介质模型的反问题的解无法得以应用.本文研究介质参考波速沿某个方向线性变化时的声散射理论,导出了声波方程逆散射问题解的解析表达式,从而既可使Born近似的假定在大多数情况下能得以满足,又可利用快速Fourier变换快速实现介质波速扰动的反演成象.     

测井声波时差反演重构技术研究及应用

利用测井声波时差、自然电位和伽玛重构声波时差,分析了以上3种曲线结果对地质体响应方面的机制差异,给出了这些曲线的深度相对移动校正的方法。研究了多条测井曲线去噪的协方差矩阵特征向量滤波方法。在此基础上,利用小波多尺度分解技术进行声波时差曲线重构。在分析这3种测井曲线不同尺度小波分解结果的信号和噪音特点后,利用相邻分解尺度相关滤波技术,对各种曲线的小尺度(高频)分解结果进行滤波处理。为保证重构声波曲线的真实性,深入分析了多曲线、多尺度分解结果的冗余性(相关性)问题;利用特征值技术,对高频多尺度分解分量进行了非相关(正交)分析,最后实现了声波时差曲线的重构,并对重构结果与钻井岩心录井资料进行了对比验证,重构后的声波曲线在区分砂、泥岩性分辨率方面具有明显的提高     

层状介质的声波波动方程反演

基于广义反射透射系数矩阵正演方法 ,讨论了层状介质的声波波动方程反问题 .推导出波数频率域中的雅可比矩阵的解析表达式 ,其计算在正演过程中求出 .采用最小二方法可得到层介质参数 .数值结果表明反演方法的正确有效性 .     

微分方程反演声阻抗剖面

本文就一维波动方程反问题用折叠反演方法和ＣＤＰ道集数据对地层声阻抗进行反演,制做了声阻抗剖面．为物探解释提供新技术．     

微分方程反演声阻抗剖面

本文就一维波动方程反问题用折叠反演方法和ＣＤＰ道集数据对地层声阻抗进行反演，制做了声阻抗剖面．为物探解释提供新技术．     

TWO-DIMENSIONAL SCATTERING OF P,SV AND RAYLEIGH WAVES: PRELIMINARY RESULTS FOR THE VALLEY OF MEXICO

A direct boundary element method for calculating the two-dimensional scattering of seismic waves from irregular topographies and buried valleys due to incident P-, SV- and Rayleigh waves is employed to model a section of the Mexico City Valley. The method has been formulated with isoparametric quadratic boundary elements and contains, with respect to previous works in the field, some improvements that are briefly presented. Because the Mexico City Valley is relatively flat and shallow and the contrast of S-waves between the clays and the basement rock is very high, it is believed that the one-dimensional theory is enough to explain the amplification patterns. Although this is true for most sites, results from recent accelerometric data suggest that two- and three-dimensional models are needed to explain the amplification behaviour at some places. In this work, two accelerometric sites have been chosen: Site 84 to probe that the one-dimensional model works well for most sites, and Site TB, as an example of irregular response. The two-dimensional method presented here was used to model a section of the valley where site TB is located, showing that this method yields results closer to the observations than the one-dimensional approach. © 1997 John Wiley & Sons, Ltd.     

DECOMPOSITION AND INVERSION OF SEISMIC DATA–AN INSTANTANEOUS SLOWNESS APPROACH*

Interpretation techniques are presented that aim at the estimation of seismic velocities. The application of localized slant stacks, weighted by coherency, produces a decomposition of multichannel seismic data into single trace instantaneous slowness p(x, t) components. Colour displays support the interpretation of seismic data relevant to the near surface velocity structure. Since p(x, t) is directly related to stacking velocities and the depth of reflection, or bottoming points, in the subsurface, this data transformation provides a powerful tool for the inversion of reflection and refraction data.     

MULTI-OFFSET ACOUSTIC INVERSION OF A LATERALLY INVARIANT MEDIUM: APPLICATION TO REAL DATA1

The aim of seismic inversion methods is to obtain quantitative information on the subsurface properties from seismic measurements. However, the potential accuracy of such methods depends strongly on the physical correctness of the mathematical equations used to model the propagation of the seismic waves. In general, the most accurate models involve the full non-linear acoustic or elastic wave equations. Inversion algorithms based on these equations are very CPU intensive. The application of such an algorithm on a real marine CMP gather is demonstrated. The earth model is assumed to be laterally invariant and only acoustic wave phenomena are modelled. A complete acoustic earth model (P-wave velocity and reflectivity as functions of vertical traveltime) is estimated. The inversion algorithm assumes that the seismic waves propagate in 2D. Therefore, an exact method for transforming the real data from 3D to 2D is derived and applied to the data. The time function of the source is estimated from a vertical far-field signature and its applicability is demonstrated by comparing synthetic and real water-bottom reflections. The source scaling factor is chosen such that the false reflection coefficient due to the first water-bottom multiple disappears from the inversion result. In order to speed up the convergence of the algorithm, the following inversion strategy is adopted: an initial smooth velocity model (macromodel) is obtained by applying Dix's equation to the result of a classical velocity analysis, followed by a smoothing operation. The initial reflectivity model is then computed using Gardner's empirical relationship between densities and velocities. In a first inversion step, reflectivity is estimated from small-offset data, keeping the velocity model fixed. In a second step, the initial smooth velocity model, and possibly the reflectivity model, is refined by using larger-offset data. This strategy is very efficient. In the first step, only ten iterations with a quasi-Newton algorithm are necessary in order to obtain an excellent convergence. The data window was 0–2.8 s, the maximum offset was 250 m, and the residual energy after the first inversion step was only 5% of the energy of the observed data. When the earth model estimated in the first inversion step is used to model data at moderate offsets (900 m, time window 0.0–1.1 s), the data fit is very good. In the second step, only a small improvement in the data fit could be obtained, and the convergence was slow. This is probably due to the strong non-linearity of the inversion problem with respect to the velocity model. Nevertheless, the final residual energy for the moderate offsets was only 11%. The estimated model was compared to sonic and density logs obtained from a nearby well. The comparison indicated that the present algorithm can be used to estimate normal incidence reflectivity from real data with good accuracy, provided that absorption phenomena play a minor role in the depth interval considered. If details in the velocity model are required, large offsets and an elastic inversion algorithm should be used.     

声波方程逆散射反演的近似方法

我们在文献[1]里研究了介质参考波速沿某个方向线性变化时的三维声散射理论,导出了声波方程逆散射反演问题解的解析表达式.考虑到应用时的实际条件,本文根据上述反演方法导出2.5维模型的声波方程逆散射反演的波速扰动计算公式,给出该方法在“高频”近似条件下的波速扰动反演计算公式,从而使我们提出的“参考波速线性变化时的声波方程逆散射反演”理论更接近实际应用条件.本文给出的这些反演公式仍然具有原方法的优点,即不但可以使Born近似的假定在大多数情况下能得以满足,而且可以利用快速Fourier变换来快速实现介质波速扰动的反演成象.     

声波方程逆散射反演的近似方法

我们在文献[1]里研究了介质参考波速沿某个方向线性变化时的三维声散射理论,导出了声波方程逆散射反演问题解的解析表达式.考虑到应用时的实际条件,本文根据上述反演方法导出2.5维模型的声波方程逆散射反演的波速扰动计算公式,给出该方法在“高频”近似条件下的波速扰动反演计算公式,从而使我们提出的“参考波速线性变化时的声波方程逆散射反演”理论更接近实际应用条件.本文给出的这些反演公式仍然具有原方法的优点,即不但可以使Born近似的假定在大多数情况下能得以满足,而且可以利用快速Fourier变换来快速实现介质波速扰动的反演成象.     

声波方程逆散射反演的近似方法

我们在文献[1]里研究了介质参考波速沿某个方向线性变化时的三维声散射理论,导出了声波方程逆散射反演问题解的解析表达式.考虑到应用时的实际条件,本文根据上述反演方法导出2.5维模型的声波方程逆散射反演的波速扰动计算公式,给出该方法在“高频”近似条件下的波速扰动反演计算公式,从而使我们提出的“参考波速线性变化时的声波方程逆散射反演”理论更接近实际应用条件.本文给出的这些反演公式仍然具有原方法的优点,即不但可以使Born近似的假定在大多数情况下能得以满足,而且可以利用快速Fourier变换来快速实现介质波速扰动的反演成象.     

声波方程频率域有限元参数反演

推导出频率域有限元声波正演方程,为了消除边界反射,将Clayton-Engquist旁轴波动方程吸收边界条件引入频率域,并对有限元刚度矩阵和质量矩阵进行压缩存储,利用广义共轭梯度法求解有限元方程获得正演解.在此基础上,推导出在某一频率下波场数据残差δU与单元物性参数修改量δλ之间关系的Jacobi矩阵,反演方法允许利用地面二维炮集全波场资料与给出初始模型参数的正演值的差值δU,迭代求得δλ.由于计算机内存的限制,方法计算不允许有过多数目的未知数个数,因此还提出了对同一介质物性单元的Jacobi矩阵元素进行压缩组装的措施,从而使反演的未知量个数减少,结合采用共轭梯度迭代法,使得只需利用有效波频段的少数一些频率即可进行迭代反演.正演和反演理论模型的数值模拟结果表明方法是有效的.     

声波方程频率域有限元参数反演

推导出频率域有限元声波正演方程,为了消除边界反射,将Clayton-Engquist旁轴波动方程吸收边界条件引入频率域,并对有限元刚度矩阵和质量矩阵进行压缩存储,利用广义共轭梯度法求解有限元方程获得正演解.在此基础上,推导出在某一频率下波场数据残差δU与单元物性参数修改量δλ之间关系的Jacobi矩阵,反演方法允许利用地面二维炮集全波场资料与给出初始模型参数的正演值的差值δU,迭代求得δλ.由于计算机内存的限制,方法计算不允许有过多数目的未知数个数,因此还提出了对同一介质物性单元的Jacobi矩阵元素进行压缩组装的措施,从而使反演的未知量个数减少,结合采用共轭梯度迭代法,使得只需利用有效波频段的少数一些频率即可进行迭代反演.正演和反演理论模型的数值模拟结果表明方法是有效的.     

INVERSION OF GRAVITY AND MAGNETIC DATA FOR THE LOWER SURFACE OF A 2.5 DIMENSIONAL SEDIMENTARY BASIN1

Gravity and magnetic data have been inverted to obtain the continuous lower surface of a 2.5 dimensional sedimentary basin. The non-linear problem is linearized and a solution is calculated through a recursive process until the predicted data matches the observed data. An average model is then calculated and a resolution analysis shows which features are uniquely determined. The results of individual inversion indicate that a final solution is initial model dependent but the average models are independent of the initial model except at the margins. The average model for the magnetic solutions have uniformly smaller spreads than the gravity solutions. The algorithms were applied to data from the Sanford Basin in North Carolina. The results indicate that the basin is asymmetrical in shape with a maximum depth of 3.2 km. Comparing these results with those obtained from a generalized linear inverse (GLI) algorithm indicate that the higher-frequency features determined from the GLI algorithm are not resolved.     

AN ALTERNATIVE STRATEGY FOR NON-LINEAR INVERSION OF SEISMIC WAVEFORMS1

A common example of a large-scale non-linear inverse problem is the inversion of seismic waveforms. Techniques used to solve this type of problem usually involve finding the minimum of some misfit function between observations and theoretical predictions. As the size of the problem increases, techniques requiring the inversion of large matrices become very cumbersome. Considerable storage and computational effort are required to perform the inversion and to avoid stability problems. Consequently methods which do not require any large-scale matrix inversion have proved to be very popular. Currently, descent type algorithms are in widespread use. Usually at each iteration a descent direction is derived from the gradient of the misfit function and an improvement is made to an existing model based on this, and perhaps previous descent directions. A common feature in nearly all geophysically relevant problems is the existence of separate parameter types in the inversion, i.e. unknowns of different dimension and character. However, this fundamental difference in parameter types is not reflected in the inversion algorithms used. Usually gradient methods either mix parameter types together and take little notice of the individual character or assume some knowledge of their relative importance within the inversion process. We propose a new strategy for the non-linear inversion of multi-offset reflection data. The paper is entirely theoretical and its aim is to show how a technique which has been applied in reflection tomography and to the inversion of arrival times for 3D structure, may be used in the waveform case. Specifically we show how to extend the algorithm presented by Tarantola to incorporate the subspace scheme. The proposed strategy involves no large-scale matrix inversion but pays particular attention to different parameter types in the inversion. We use the formulae of Tarantola to state the problem as one of optimization and derive the same descent vectors. The new technique splits the descent vector so that each part depends on a different parameter type, and proceeds to minimize the misfit function within the sub-space defined by these individual descent vectors. In this way, optimal use is made of the descent vector components, i.e. one finds the combination which produces the greatest reduction in the misfit function based on a local linearization of the problem within the subspace. This is not the case with other gradient methods. By solving a linearized problem in the chosen subspace, at each iteration one need only invert a small well-conditioned matrix (the projection of the full Hessian on to the subspace). The method is a hybrid between gradient and matrix inversion methods. The proposed algorithm requires the same gradient vectors to be determined as in the algorithm of Tarantola, although its primary aim is to make better use of those calculations in minimizing the objective function.     

NON-LINEAR AVO INVERSION FOR A STACK OF ANELASTIC LAYERS1

Parameters in a stack of homogeneous anelastic layers are estimated from seismic data, using the amplitude versus offset (AVO) variations and the travel-times. The unknown parameters in each layer are the layer thickness, the P-wave velocity, the S-wave velocity, the density and the quality factor. Dynamic ray tracing is used to solve the forward problem. Multiple reflections are included, but wave-mode conversions are not considered. The S-wave velocities are estimated from the PP reflection and transmission coefficients. The inverse problem is solved using a stabilized least-squares procedure. The Gauss-Newton approximation to the Hessian matrix is used, and the derivatives of the dynamic ray-tracing equation are calculated analytically for each iteration. A conventional velocity analysis, the common mid-point (CMP) stack and a set of CMP gathers are used to identify the number of layers and to establish initial estimates for the P-wave velocities and the layer thicknesses. The inversion is carried out globally for all parameters simultaneously or by a stepwise approach where a smaller number of parameters is considered in each step. We discuss several practical problems related to inversion of real data. The performance of the algorithm is tested on one synthetic and two real data sets. For the real data inversion, we explained up to 90% of the energy in the data. However, the reliability of the parameter estimates must at this stage be considered as uncertain.