Improved amplitude preservation for prestack depth migration by inverse scattering theory

A prestack reverse time-migration image is not properly scaled with increasing depth. The main reason for the image being unscaled is the geometric spreading of the wavefield arising during the back-propagation of the measured data and the generation of the forward-modelled wavefields. This unscaled image can be enhanced by multiplying the inverse of the approximate Hessian appearing in the Gauss–Newton optimization technique. However, since the approximate Hessian is usually too expensive to compute for the general geological model, it can be used only for the simple background velocity model.We show that the pseudo-Hessian matrix can be used as a substitute for the approximate Hessian to enhance the faint images appearing at a later time in the 2D prestack reverse time-migration sections. We can construct the pseudo-Hessian matrix using the forward-modelled wavefields (which are used as virtual sources in the reverse time migration), by exploiting the uncorrelated structure of the forward-modelled wavefields and the impulse response function for the estimated diagonal of the approximate Hessian. Although it is also impossible to calculate directly the inverse of the pseudo-Hessian, when using the reciprocal of the pseudo-Hessian we can easily obtain the inverse of the pseudo-Hessian. As examples supporting our assertion, we present the results obtained by applying our method to 2D synthetic and real data collected on the Korean continental shelf.     

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.     

地震反演成像中的Hessian算子研究

总结了牛顿类地震反演方法中Hessian算子的作用,对其在地震反演成像中的数学物理含义进行了分析.Hessian算子是误差泛函对模型参数的二阶导数,反映了误差泛函对模型变化的二次型特征.分析声波方程下的Hessian算子的格林函数表达形式,发现其表达了整个观测系统和子波频带等因素对地震数据空间到模型空间投影过程的影响.提出了两种分别适用于最小二乘偏移和全波形反演的Hessian算子简化格式.平面波Hessian算子应用于最小二乘偏移能够得到相对保真的成像结果,改善了地震偏移成像的精度.地下偏移距Hessian算子应用于全波形反演能够加快反演迭代的计算效率.最后,对Hessian算子在地震反演成像中的价值进行了讨论和评价.     

2D Laplace-Domain Waveform Inversion of Field Data Using a Power Objective Function

The wavefield in the Laplace domain has a very small amplitude except only near the source point. In order to deal with this characteristic, the logarithmic objective function has been used in many Laplace domain inversion studies. The Laplace-domain waveform inversion using the logarithmic objective function has fewer local minima than the time- or frequency domain inversion. Recently, the power objective function was suggested as an alternative to the logarithmic objective function in the Laplace domain. Since amplitudes of wavefields are very small generally, a power <1 amplifies the wavefields especially at large offset. Therefore, the power objective function can enhance the Laplace-domain inversion results. In previous studies about synthetic datasets, it is confirmed that the inversion using a power objective function shows a similar result when compared with the inversion using a logarithmic objective function. In this paper, we apply an inversion algorithm using a power objective function to field datasets. We perform the waveform inversion using the power objective function and compare the result obtained by the logarithmic objective function. The Gulf of Mexico dataset is used for the comparison. When we use a power objective function in the inversion algorithm, it is important to choose the appropriate exponent. By testing the various exponents, we can select the range of the exponent from 5 × 10^?3 to 5 × 10^?8 in the Gulf of Mexico dataset. The results obtained from the power objective function with appropriate exponent are very similar to the results of the logarithmic objective function. Even though we do not get better results than the conventional method, we can confirm the possibility of applying the power objective function for field data. In addition, the power objective function shows good results in spite of little difference in the amplitude of the wavefield. Based on these results, we can expect that the power objective function will produce good results from the data with a small amplitude difference. Also, it can partially be utilized at the sections where the amplitude difference is very small.     

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.     

Comparison of waveform inversion, part 1: conventional wavefield vs logarithmic wavefield

This is the first in a series of three papers focused on using variants of a logarithmic objective function approach to full waveform inversion. In this article, we investigate waveform inversion using full logarithmic principles and compare the results with the conventional least squares approach. We demonstrate theoretically that logarithmic inversion is computational similar to the conventional method in the sense that it uses exactly the same back‐propagation technology as used in least‐squares inversion. In the sense that it produces better results for each of three numerical examples, we conclude that logarithmic inversion is also more robust. We argue that a major reason for the inherent robustness is the fact that the logarithmic approach produces a natural scaling of the amplitude of the residual wavefield by the amplitude of the modelled wavefield that tends to stabilize the computations and consequently improve the final result. We claim that any superiority of the logarithmic inversion is based on the fact that it tends to be tomographic in the early stage of the inversion and more dependent on amplitude differences in the latter stages.     

多主频波场的时间阻尼全波形反演

低频成分缺失和地下速度强烈变化会导致严重的周期跳现象,是地震数据全波形反演的难题.通过对地震数据加时间阻尼和时间积分降主频处理,提出了一种可有效去除周期跳现象的多主频波场时间阻尼全波形反演方法.由浅到深的速度不准确会造成波形走时失配和走时失配的累积.浅部速度的准确反演可有效地减小深部波形走时失配与周期跳现象.对地震数据施加时间阻尼得到时间阻尼数据,利用不同阻尼值的时间阻尼地震数据实现由浅到深的全波形反演.低主频波场的周期跳现象相对高主频波场的要弱.对地震波场进行不同阶的时间积分以得到不同主频的波场,把低主频波场的全波形反演结果作为高主频波场全波形反演的初始模型.应用缺失4 Hz以下频谱成分的二维盐丘模型合成数据验证所提出的全波形反演方法的正确性和有效性,数值试验结果显示多主频波场的时间阻尼全波形反演方法对缺失低频成分地震数据和地下速度强烈变化具有很好的适应性.

     

不依赖子波、基于包络的FWI初始模型建立方法研究

地震全波形反演(FWI)从理论走向实际面临着诸多难题,其中之一就是需要一个较高精度的初始模型,另一个难题就是需要一个较为精确的震源子波,初始模型和震源子波的准确程度严重影响着全波形反演的最终结果.为此,本文提出了不依赖子波、基于包络的FWI初始模型建立的方法,建立了相应的目标函数,推导出了反演的梯度,给出了伴随震源的表达式,理论上分析了不依赖子波FWI的可行性.在数值试验中,讨论了参考道的选取方式,通过分析归一化目标函数收敛速率,认为近偏移距参考道优于远偏移距参考道,在地震数据含干扰噪音时,平均道作为参考道要优于最小偏移距参考道.通过包络、包络对数、包络平方三种目标函数反演结果的比较,发现包络对数目标函数对深层的反演效果最好.通过不同子波的试验进一步验证了本方法的正确性.     

3D acoustic waveform inversion in the Laplace domain using an iterative solver

In this paper we propose a 3D acoustic full waveform inversion algorithm in the Laplace domain. The partial differential equation for the 3D acoustic wave equation in the Laplace domain is reformulated as a linear system of algebraic equations using the finite element method and the resulting linear system is solved by a preconditioned conjugate gradient method. The numerical solutions obtained by our modelling algorithm are verified through a comparison with the corresponding analytical solutions and the appropriate dispersion analysis. In the Laplace‐domain waveform inversion, the logarithm of the Laplace transformed wavefields mainly contains long‐wavelength information about the underlying velocity model. As a result, the algorithm smoothes a small‐scale structure but roughly identifies large‐scale features within a certain depth determined by the range of offsets and Laplace damping constants employed. Our algorithm thus provides a useful complementary process to time‐ or frequency‐domain waveform inversion, which cannot recover a large‐scale structure when low‐frequency signals are weak or absent. The algorithm is demonstrated on a synthetic example: the SEG/EAGE 3D salt‐dome model. The numerical test is limited to a Laplace‐domain synthetic data set for the inversion. In order to verify the usefulness of the inverted velocity model, we perform the 3D reverse time migration. The migration results show that our inversion results can be used as an initial model for the subsequent high‐resolution waveform inversion. Further studies are needed to perform the inversion using time‐domain synthetic data with noise or real data, thereby investigating robustness to noise.     

不依赖源子波的跨孔雷达时间域波形反演

波形反演是近年来较热门的反演方法,其分辨率可以达到亚波长级别.在波形反演的实际应用中,源子波的估计十分重要.传统方法使用反褶积来估计源子波并随着反演过程更新,该方法在合成数据波形反演中效果较好,但在实际数据反演过程中存在一系列的问题.由于实际数据信噪比较低,在源子波估计过程中需要大量的人为干涉,且结果并不一定可靠.本文使用一种基于褶积波场的新型目标函数,令反演过程不再依赖源子波.详细推导了针对跨孔雷达波形反演的梯度及步长公式,实现介电常数和电导率的同步反演.针对一个合成数据模型同时反演介电常数和电导率,结果表明该方法能够反演出亚波长尺寸异常体的形状和位置.接着,将该方法应用到两组实际数据中,并与基于估计源子波的时间域波形反演结果进行比较.结果表明不依赖源子波的时间域波形反演结果分辨率更高,也更准确.     

Improving waveform inversion using modified interferometric imaging condition

Similar to the reverse-time migration, full waveform inversion in the time domain is a memory-intensive processing method. The computational storage size for waveform inversion mainly depends on the model size and time recording length. In general, 3D and 4D data volumes need to be saved for 2D and 3D waveform inversion gradient calculations, respectively. Even the boundary region wavefield-saving strategy creates a huge storage demand. Using the last two slices of the wavefield to reconstruct wavefields at other moments through the random boundary, avoids the need to store a large number of wavefields; however, traditional random boundary method is less effective at low frequencies. In this study, we follow a new random boundary designed to regenerate random velocity anomalies in the boundary region for each shot of each iteration. The results obtained using the random boundary condition in less illuminated areas are more seriously affected by random scattering than other areas due to the lack of coverage. In this paper, we have replaced direct correlation for computing the waveform inversion gradient by modified interferometric imaging, which enhances the continuity of the imaging path and reduces noise interference. The new imaging condition is a weighted average of extended imaging gathers can be directly used in the gradient computation. In this process, we have not changed the objective function, and the role of the imaging condition is similar to regularization. The window size for the modified interferometric imaging condition-based waveform inversion plays an important role in this process. The numerical examples show that the proposed method significantly enhances waveform inversion performance.     

Comparison of waveform inversion, part 3: amplitude approach

In the second paper of this three part series, we studied the case of conventional and logarithmic phase‐only approaches to full‐waveform inversion. Here, we concentrate on deriving amplitude‐only approaches for both conventional‐ and logarithmic‐based methods. We define two amplitude‐only objective functions by simply assuming that the phase of the modelled wavefield is equal to that of the observed wavefield. We do this for both the conventional least‐squares approach and the logarithmic approach of Shin and Min. We show that these functions can be optimized using the same reverse‐time propagation algorithm of the full conventional methodology. Although the residuals in this case are not really residual wavefields, they can both be considered and utilized in that sense. In contrast to the case for our phase‐only algorithms, we show through numerical tests that the conventional amplitude‐only inversion is better than the logarithmic method.     

基于频域衰减的时域全波形反演

时域全波形反演由于采用了全频段信息,因此在迭代过程中不同波长的信息不能由低到高的逐步重建,极易陷入局部极小值.本文通过分频段的方式,对地震数据做正反傅里叶变换,利用频域指数衰减的方法逐级分离出地震数据中的高频成分,在时域上实现由低频向高频的波形反演,从而降低了反演的非线性,使不同波长的信息得到稳步恢复.同时,在高频成分衰减的过程中,后至波的能量也被削弱,由此也降低了深层反射在初始反演过程中的干扰.整个反演仅增加对数据做正反傅里叶变换过程,相较于混合域反演,无需提取全部波场的相应频率成分.在计算效率方面,利用GPU进行加速,并采用CUDA自带函数库中cufft来提高计算效率.通过对Marmousi模型测试,验证了所述方法的有效性.     

Target-level waveform inversion: a prospective application of the convolution-type representation for the acoustic wavefield

Nowadays, full-waveform inversion, based on fitting the measured surface data with modelled data, has become the preferred approach to recover detailed physical parameters from the subsurface. However, its application is computationally expensive for large inversion domains. Furthermore, when the subsurface has a complex geological setting, the inversion process requires an appropriate pre-conditioning scheme to retrieve the medium parameters for the desired target area in a reliable manner. One way of dealing with both aspects is by waveform inversion schemes in a target-oriented fashion. Therefore, we propose a prospective application of the convolution-type representation for the acoustic wavefield in the frequency–space domain formulated as a target-oriented waveform inversion method. Our approach aims at matching the observed and modelled upgoing wavefields at a target depth level in the subsurface, where the seismic wavefields, generated by sources distributed above this level, are available. The forward modelling is performed by combining the convolution-type representation for the acoustic wavefield with solving the two-way acoustic wave-equation in the frequency–space domain for the target area. We evaluate the effectiveness of our inversion method by comparing it with the full-domain full-waveform inversion process through some numerical examples using synthetic data from a horizontal well acquisition geometry, where the sources are located at the surface and the receivers are located along a horizontal well at the target level. Our proposed inversion method requires less computational effort and, for this particular acquisition, it has proven to provide more accurate estimates of the target zone below a complex overburden compared to both full-domain full-waveform inversion process and local full-waveform inversion after applying interferometry by multidimensional deconvolution to get local-impulse responses.     

Joint viscoacoustic waveform inversion with the separated upgoing and downgoing wavefields in zero-offset vertical seismic profile data

The attenuation of seismic waves propagating in reservoirs can be obtained accurately from the data analysis of vertical seismic profile in terms of the quality-factor Q. The common methods usually use the downgoing wavefields in vertical seismic profile data. However, the downgoing wavefields consist of more than 90% energy of the spectrum of the vertical seismic profile data, making it difficult to estimate the viscoacoustic parameters accurately. Thus, a joint viscoacoustic waveform inversion of velocity and quality-factor is proposed based on the multi-objective functions and analysis of the difference between the results inverted from the separated upgoing and downgoing wavefields. A simple separating step is accomplished by the reflectivity method to obtain the individual wavefields in vertical seismic profile data, and then a joint inversion is carried out to make full use of the information of the individual wavefields and improve the convergence of viscoacoustic full-waveform inversion. The sensitivity analysis of the different wavefields to the velocity and quality-factor shows that the upgoing and downgoing wavefields contribute differently to the viscoacoustic parameters. A numerical example validates our method can improve the accuracy of viscoacoustic parameters compared with the direct inversion using full wavefield and the separate inversion using upgoing or downgoing wavefield. The application on real field data indicates our method can recover a reliable viscoacoustic model, which helps reservoir appraisal.     

基于弹性波全波形反演的主被动源多分量混采地震数据速度建模

在常规地震采集中,被动源地震波场往往被视为噪声而去除,这就造成了部分有用信息的丢失.在目标区进行主动源和被动源弹性波地震数据的多分量混合采集,并对两种数据进行联合应用,使其在照明和频带上优势互补,能显著提高成像和反演的质量.本文针对两种不同类型的主被动源混采地震数据,分别提出了相应的联合全波形反演方法.首先,针对主动源与瞬态被动源弹性波混采地震数据,为充分利用被动源对深部照明的优势,同时有效压制被动震源点附近的成像异常值,提出了基于动态随机组合的弹性波被动源照明补偿反演策略.然后,针对低频缺失主动源与背景噪声型被动源弹性波混采地震数据,为充分利用被动源波场携带的低频信息,并避免对被动源的定位和子波估计,提出了基于地震干涉与不依赖子波算法的弹性波主被动源串联反演策略.最后,分别将两种方法在Marmousi模型上进行反演测试.结果说明,综合利用主动源和被动源弹性波混采地震数据,不仅能增强深部弹性参数反演效果,还能更好地构建弹性参数模型的宏观结构,并有助于缓解常规弹性波全波形反演的跳周问题.

     

Comparison of Frequency-Selection Strategies for 2D Frequency-Domain Acoustic Waveform Inversion

Several frequency-selection strategies have been used to obtain global minimum solutions in waveform inversion. One strategy, called the discretization method, is to discretize frequencies with a large sampling interval to minimize redundancy in wavenumber information. Another method, the grouping method, groups frequencies with redundancy in wavenumber information. The grouping method can be carried out in two ways. With the first method, the minimum frequency is fixed and the maximum frequency is gradually extended upward (i.e., the overlap-grouping method). Under the second method, frequencies are not overlapped across the groups and waveform inversion proceeds from lower to higher frequency groups (i.e., the individual-grouping method). In this study, we compare these three frequency-selection strategies using both synthetic and real data examples based on logarithmic waveform inversion. Numerical examples for synthetic and real field data demonstrate that the three frequency-selection methods provide solutions closer to the global minimum compared to solutions resulting from simultaneously performed waveform inversion, and that the individual-grouping method yields slightly better resolution for the velocity models than the other methods, particularly for the deeper part. These results may imply that using either too small or too large data sets at every stage slightly deteriorates inversion results, and that grouping data in appropriately sized aggregations improves inversion results.     

Velocity model building from seismic reflection data by full‐waveform inversion

Full‐waveform inversion is re‐emerging as a powerful data‐fitting procedure for quantitative seismic imaging of the subsurface from wide‐azimuth seismic data. This method is suitable to build high‐resolution velocity models provided that the targeted area is sampled by both diving waves and reflected waves. However, the conventional formulation of full‐waveform inversion prevents the reconstruction of the small wavenumber components of the velocity model when the subsurface is sampled by reflected waves only. This typically occurs as the depth becomes significant with respect to the length of the receiver array. This study first aims to highlight the limits of the conventional form of full‐waveform inversion when applied to seismic reflection data, through a simple canonical example of seismic imaging and to propose a new inversion workflow that overcomes these limitations. The governing idea is to decompose the subsurface model as a background part, which we seek to update and a singular part that corresponds to some prior knowledge of the reflectivity. Forcing this scale uncoupling in the full‐waveform inversion formalism brings out the transmitted wavepaths that connect the sources and receivers to the reflectors in the sensitivity kernel of the full‐waveform inversion, which is otherwise dominated by the migration impulse responses formed by the correlation of the downgoing direct wavefields coming from the shot and receiver positions. This transmission regime makes full‐waveform inversion amenable to the update of the long‐to‐intermediate wavelengths of the background model from the wide scattering‐angle information. However, we show that this prior knowledge of the reflectivity does not prevent the use of a suitable misfit measurement based on cross‐correlation, to avoid cycle‐skipping issues as well as a suitable inversion domain as the pseudo‐depth domain that allows us to preserve the invariant property of the zero‐offset time. This latter feature is useful to avoid updating the reflectivity information at each non‐linear iteration of the full‐waveform inversion, hence considerably reducing the computational cost of the entire workflow. Prior information of the reflectivity in the full‐waveform inversion formalism, a robust misfit function that prevents cycle‐skipping issues and a suitable inversion domain that preserves the seismic invariant are the three key ingredients that should ensure well‐posedness and computational efficiency of full‐waveform inversion algorithms for seismic reflection data.     

Laplace–Fourier-Domain Waveform Inversion for Fluid–Solid Media

Full waveform inversion algorithms are widely used in the construction of subsurface velocity models. In the following study, we propose a Laplace–Fourier-domain waveform inversion algorithm that uses both Laplace-domain and Fourier-domain wavefields to achieve the reconstruction of subsurface velocity models. Although research on the Laplace–Fourier-domain waveform inversion has been published recently that study is limited to fluid media. Because the geophysical targets of marine seismic exploration are usually located within solid media, waveform inversion that is approximated to acoustic media is limited to the treatment of properly identified submarine geophysical features. In this study, we propose a full waveform inversion algorithm for isotropic fluid–solid media with irregular submarine topography comparable to a real marine environment. From the fluid–solid system, we obtained P and S wave velocity models from the pressure data alone. We also suggested strategies for choosing complex frequency bands constructed of frequencies and Laplace coefficients to improve the resolution of the restored velocity structures. For verification, we applied our Laplace–Fourier-domain waveform inversion for fluid–solid media to synthetic data that were reconstructed for fluid–solid media. Through this inversion test, we successfully restored reasonable velocity structures. Furthermore, we successfully extended our algorithm to a field data set.     

Site characterization using Gauss–Newton inversion of 2-D full seismic waveform in the time domain

Site characterization for design of deep foundations is very crucial, as unanticipated site conditions still represent significant problems and disputes occur during construction. Traditional surface-based geophysical methods, which use wave velocity dispersion or first-arrival times, have been widely used recently to assess spatial variation; however they cannot well characterize reverse profiles or buried low-velocity zones. For better characterization of these challenging site conditions, a full waveform inversion based on Gauss–Newton method is presented. The inversion scheme is based on a finite-difference solution of the 2-D elastic wave equation in the time domain. The strength of this approach is the ability to generate all possible wave types of seismic wavefields that are then compared with observed data to infer complex subsurface properties. Virtual sources and reciprocity of wavefields are used for calculation of partial derivative wavefields to reduce computer time. Cross convolution between observed and estimated wavefields are also employed to allow the technique to be independent of the source signatures. The capability of the presented technique is tested with both synthetic and real experimental data sets. The inversion results from synthetic data show the ability of characterizing anomalies of low- and high-velocity zones, and the inversion results from real data are generally consistent with SPT N-value, including the identification of a buried low-velocity layer.