地震数据的反射波动方程最小二乘偏移

基于反射波动方程,本文提出了一种估计地下反射率分布的地震数据最小二乘偏移方法.高频近似下,非齐次的一次反射波动方程的源项是由反射率与入射波场的时间一阶导数相互作用产生的.根据反射波动方程,利用线性最小二乘反演方法由地震反射数据重建出地下产生反射波的反射源,再结合波场正演计算出的地下入射波场,得到地下反射率分布的估计.在地下反射源的线性最小二乘反演重建中,我们采用迭代求解方法,并以地震波的检波器单向地下照明强度作为最小二乘优化问题中Hessian矩阵的近似.

     

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.

     

The use of low frequencies in a full‐waveform inversion and impedance inversion land seismic case study

Velocity model building and impedance inversion generally suffer from a lack of intermediate wavenumber content in seismic data. Intermediate wavenumbers may be retrieved directly from seismic data sets if enough low frequencies are recorded. Over the past years, improvements in acquisition have allowed us to obtain seismic data with a broader frequency spectrum. To illustrate the benefits of broadband acquisition, notably the recording of low frequencies, we discuss the inversion of land seismic data acquired in Inner Mongolia, China. This data set contains frequencies from 1.5–80 Hz. We show that the velocity estimate based on an acoustic full‐waveform inversion approach is superior to one obtained from reflection traveltime inversion because after full‐waveform inversion the background velocity conforms to geology. We also illustrate the added value of low frequencies in an impedance estimate.     

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.     

Exact elastic impedance tensor for isotropic media

The existing expressions of elastic impedance,as the generalized form of acoustic impedance,represent the resistance of subsurface media to seismic waves of non-normal incidence,and thus include information on the shear-wave velocity.In this sense,conventional elastic impedance is an attribute of the seismic reflection and not an intrinsic physical property of the subsurface media.The derivation of these expressions shares the approximations made for reflectivity,such as weak impedance contrast andisotropic or weakly anisotropic media,which limits the accuracy of reflectivity reconstruction and seismic inversion.In this paper,we derive exact elastic impedance tensors of seismic P-and S-waves for isotropic media based on the stress-velocity law.Each componentof the impedance tensor represents a unique mechanical property of the medium.Approximations of P-wave elastic impedance tensor components are discussed for seismic inversion and interpretation.Application to synthetic data and real data shows the accuracy and robust interpretation capability of the derived elastic impedance in lithology characterizations.     

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.

     

3D simultaneous joint PP‐PS prestack seismic inversion at Schiehallion field,United Kingdom Continental Shelf

A workflow for simultaneous joint PP‐PS prestack inversion of data from the Schiehallion field on the United Kingdom Continental Shelf is presented and discussed. The main challenge, describing reasonable PS to PP data registration before any prestack or joint PP‐PS inversion, was overcome thanks to a two‐stage process addressing the signal envelope, then working directly on the seismic data to estimate appropriate time‐variant time‐shift volumes. We evaluated the benefits of including PS along with PP prestack seismic data in a joint inversion process to improve the estimated elastic property quality and also to enable estimation of density compared with other prestack and post‐stack inversion approaches. While the estimated acoustic impedance exhibited a similar quality independent of the inversion used (PP post‐stack, PP prestack or joint PP‐PS prestack inversion) the shear impedance estimation was noticeably improved by the joint PP‐PS prestack inversion when compared to the PP prestack inversion. Finally, the density estimated from joint PP and PS prestack data demonstrated an overall good quality, even where not well‐controlled. The main outcome of this study was that despite several data‐related limitations, inverting jointly correctly processed PP and PS data sets brought extra value for reservoir delineation as opposed to PP‐only or post‐stack inversion.     

深度域自适应加权多模态多任务学习声阻抗反演

以往基于深度学习的叠后地震声阻抗反演通常仅限于利用单道地震数据,当地震数据中存在较强噪声或地下介质横向变化较大时反演结果中会面临横向连续性差和层位区分不清晰的问题.本文提出了一种深度域自适应加权多模态多任务学习声阻抗反演方法,采用GPU加速运算,在阻抗剖面的估计过程中加入井位置附近的空间背景信息,并在数据输入端加入初始阻抗模型.构建的网络包括阻抗反演和地震数据重建两个任务,网络训练过程中采用自适应权重调整策略能够同时优化各自输出的损失,实现数据增强,缓解网络的过拟合,提高网络的泛化能力;相比于传统最小二乘阻抗反演方法,该方法反演速度更快.针对井数据偏少的情况,本文引入其他可用训练数据并采用联合学习策略改善反演结果.模型和实际数据测试表明该方法能够在含有噪声的地震数据和测井数据有限的情况下估计深度域声阻抗,反演结果的横向连续性得到了明显的改善.

     

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.     

子波相位不准对反演结果的影响(英文)

本文重点讨论在振幅谱估计准确的情况下,采用不同相位谱子波作为实际估计子波进行线性最小二乘反演,并对结果进行分析。除子波相位外,所有其它影响反演结果的因素均忽略。稀疏反射系数模型(块状波阻抗模型)反演结果表明:(1)使用不同相位谱子波进行反演,其反演结果合成的记录与原始记录都非常匹配,但反演的反射系数和声波阻抗结果与真实模型有差异;(2)反演结果的可靠程度主要与不同相位子波z变换的根的分布有关,当估计子波与真实子波Z变换的根的分布仅在单位圆附近有差异时,反演的反射系数和声波阻抗与真实模型很接近;(3)尽管反演前后地震记录都匹配了,并且评价反演结果好坏的柯西准则或改进柯西准则(反演参数没有进行自适应处理)已经达到了最优(最小),但反演结果与真实模型仍存在较大差异。最后,针对子波相位估计不准可能导致反演效果较差这个问题,我们提出采用求L1范数、丰度、变分、柯西准则(反演参数进行了自适应处理)或/和改进柯西准则(反演参数进行了自适应处理)的最优值或次优值作为评价准则的一种解决办法,理论上得到了好的效果。     

Spectral sparse Bayesian learning reflectivity inversion

A spectral sparse Bayesian learning reflectivity inversion method, combining spectral reflectivity inversion with sparse Bayesian learning, is presented in this paper. The method retrieves a sparse reflectivity series by sequentially adding, deleting or re‐estimating hyper‐parameters, without pre‐setting the number of non‐zero reflectivity spikes. The spikes with the largest amplitude are usually the first to be resolved. The method is tested on a series of data sets, including synthetic data, physical modelling data and field data sets. The results show that the method can identify thin beds below tuning thickness and highlight stratigraphic boundaries. Moreover, the reflectivity series, which is inverted trace‐by‐trace, preserves the lateral continuity of layers.     

利用基于子波估计的频谱校正方法提高Q值估计精度(英文)

用Q值刻画的地震衰减在地震信号处理和解释中具有很广泛的应用。利用反射地震资料进行Q值估计需要解决地震子波和反射系数序列耦合的问题。从反射地震资料中去除反射系数序列的影响,这个过程称为频谱校正。本文提出了一种基于子波估计的求取Q值的方法,进而设计了一个反Q滤波器。该方法利用反射地震资料的高阶统计量进行子波估计,并利用所估计子波实现频谱校正。我们利用合成数据实验给出了质心频移法与频谱比法这两种常用的Q值估计方法在不同参数设置下的性能。人工合成数据和实际数据处理表明,利用本文提出的方法进行频谱校正后,可以得到可靠的Q值估计。经过反Q滤波,地震数据的高频部分得到了有效地恢复。     

An application of the autoregressive extrapolation technique to enhance deconvolution results: a 2D marine data example

Interpreting a post‐stack seismic section is difficult due to the band‐limited nature of the seismic data even post deconvolution. Deconvolution is a process that is universally applied to extend the bandwidth of seismic data. However, deconvolution falls short of this task as low and high frequencies of the deconvolved data are either still missing or contaminated by noise. In this paper we use the autoregressive extrapolation technique to recover these missing frequencies, using the high signal‐to‐noise ratio (S/N) portions of the spectrum of deconvolved data. I introduce here an algorithm to extend the bandwidth of deconvolved data. This is achieved via an autoregressive extrapolation technique, which has been widely used to replace missing or corrupted samples of data in signal processing. This method is performed in the spectral domain. The spectral band to be extrapolated using autoregressive prediction filters is first selected from the part of the spectrum that has a high signal‐to‐noise ratio (S/N) and is then extended. As there can be more than one zone of good S/N in the spectrum, the results of prediction filter design and extrapolation from three different bands are averaged. When the spectrum of deconvolved data is extended in this way, the results show higher vertical resolution to a degree that the final seismic data closely resemble what is considered to be a reflectivity sequence of the layered medium. This helps to obtain acoustic impedance with inversion by stable integration. The results show that autoregressive spectral extrapolation highly increases vertical resolution and improves horizon tracking to determine continuities and faults. This increase in coherence ultimately yields a more interpretable seismic section.     

The origin and nature of seismic reflections of sharp-based shoreface deposits (upper Jurassic Siliciclastics, northern France)

In order to advance understanding of the relationship between geological properties and their physical expression in reflection images, this study has focused expertise in reflection geophysics, petrophysics and sedimentology on the same geological object, in this case a succession of Upper Jurassic sharp‐based shoreface deposits embedded in offshore marine shales in northern France. This integrated approach to determine firstly the origin and nature of seismic reflections (calibration) and secondly to provide a means of extracting geological information from seismic imagery (inverse calibration) was built on the following analytical steps. Firstly, detailed and extensive petrophysical analyses of outcrop (plug) samples, continuous core and sonic well logs, in combination with a quantification of mineralogical and textural properties, allowed a direct conversion of acoustic properties (impedance) into sedimentological properties, resulting in a quantitative physical sequence stratigraphic model. Secondly, the integration of scale‐dependent acoustic measurements, ranging from 0.01 m and 320 kHz on cores up to the wavelength of field seismic data was established using an averaging algorithm (an effective‐medium‐theory type) as an upscaling approach. This alternative to a VSP or check shot allows an optimized depth–time conversion and hence determination of the origin of the seismic reflections with previously unattainable accuracy. Finally, the shape and scale dependence of impedance contrasts were integrated into so‐called singularity parameters that directly link depositional changes with information from seismic reflections: depositional changes in the shallow‐water domain are generally characterized by step functions, whereas those in more distal depositional environments are represented by spiky functions. This approach allows the recognition of the associated reflection events and, vice versa, it provides a unique opportunity to extract the character of impedance changes, and thus changes in depositional environment, from seismic reflection records in general. This integrated and multiscale characterization of sharp‐based shoreface deposits calibrates the typical reflection patterns for such sedimentary units. These include continuous high‐amplitude smooth and flat tops, discontinuous sharp basal reflections with variable amplitude, and complex sigmoidal high‐amplitude reflections within the compound shoreface deposits. In addition, the results of this study, by detailing the effects of scale and frequency on impedance changes, improve the identification of similar deposits in subsurface seismic data and the extraction of maximum amounts of geological information beyond seismic resolution.     

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.     

COMPLETE INVERSION OF ZERO-OFFSET SEISMIC DATA*

The one-dimensional seismic inverse problem consists of recovering the acoustic impedance (or reflectivity function) as a function of traveltime from the reflection response of a horizontally layered medium excited by a plane-wave impulsive source. Most seismic sources behave like point sources, and the data must be corrected for geometrical spreading before the inversion procedure is applied. This correction is usually not exact because the geometrical spreading is different for primary and multiple reflections. An improved algorithm is proposed which takes the geometrical spreading from a point source into account. The zero-offset reflection response from a stack of homogeneous layers of variable thickness is used to compute the thickness, velocity and density of each layer. This is possible because the geometrical spreading contains additional information about the velocities.     

Post-stack impedance blocky inversion based on analytic solution of viscous acoustic wave equation

The conventional impedance inversion method ignores the attenuation effect, transmission loss and inter-layer multiple waves; the smooth-like regularization approach makes the corresponding impedance solution excessively smooth. Both fundamentally limit the resolution of impedance result and lead to the inadequate ability of boundary characterization. Therefore, a post-stack impedance blocky inversion method based on the analytic solution of viscous acoustic equation is proposed. Based on the derived recursive formula of reflections, the 1D viscous acoustic wave equation is solved analytically to obtain zero-offset full-wave field response. Applying chain rule, the analytical expression of the Fréchet derivative is derived for gradient-descent non-linear inversion. Combined with smooth constraints, the blocky constraints can be introduced into the Bayesian inference framework to obtain stable and well-defined inversion results. According to the above theory, we firstly use model data to analyse the influence of incompleteness of forward method on seismic response, and further verify the effectiveness of the proposed method. Then the Q-value sensitivity analysis of seismic trace is carried out to reduce the difficulty of Q-value estimation. Finally, the real data from Lower Congo Basin in West Africa indicate that the proposed approach provide the high-resolution and well-defined impedance result. As a supplement and development of linear impedance inversion method, the non-linear viscous inversion could recover more realistic and reliable impedance profiles.     

NON-LINEAR ESTIMATION OF REFLECTION COEFFICIENTS FROM SEISMIC DATA*

For years, reflection coefficients have been the main aim of traditional deconvolution methods for their significant informational content. A method to estimate seismic reflection coefficients has been derived by searching for their amplitude and their time positions without any other limitating assumption. The input data have to satisfy certain quality constraints like amplitude and almost zero phase noise—ghosts, reverberations, long period multiples, and diffracted waves should be rejected by traditional processing. The proposed algorithm minimizes a functional of the difference between the spectra of trace and reflectivity in the frequency domain. The estimation of reflection coefficients together with the consistent “wavelet’ is reached iteratively with a multidimensional Newton-Raphson technique. The residual error trace shows the behavior of the process. Several advantages are then obtainable from these reflection coefficients, like conversion to interval velocities with an optimum calibration either to the well logs or to the velocity analysis curves. The procedure can be applied for detailed stratigraphic interpretations or to improve the resolution of a conventional velocity analysis.     

Exploring some issues in acoustic full waveform inversion

The least‐squares error measures the difference between observed and modelled seismic data. Because it suffers from local minima, a good initial velocity model is required to avoid convergence to the wrong model when using a gradient‐based minimization method. If a data set mainly contains reflection events, it is difficult to update the velocity model with the least‐squares error because the minimization method easily ends up in the nearest local minimum without ever reaching the global minimum. Several authors observed that the model could be updated by diving waves, requiring a wide‐angle or large‐offset data set. This full waveform tomography is limited to a maximum depth. Here, we use a linear velocity model to obtain estimates for the maximum depth. In addition, we investigate how frequencies should be selected if the seismic data are modelled in the frequency domain. In the presence of noise, the condition to avoid local minima requires more frequencies than needed for sufficient spectral coverage. We also considered acoustic inversion of a synthetic marine data set created by an elastic time‐domain finite‐difference code. This allowed us to validate the estimates made for the linear velocity model. The acoustic approximation leads to a number of problems when using long‐offset data. Nevertheless, we obtained reasonable results. The use of a variable density in the acoustic inversion helped to match the data at the expense of accuracy in the inversion result for the density.     

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.