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.     

Multiscale full-waveform inversion based on shot subsampling

Conventional full-waveform inversion is computationally intensive because it considers all shots in each iteration. To tackle this, we establish the number of shots needed and propose multiscale inversion in the frequency domain while using only the shots that are positively correlated with frequency. When using low-frequency data, the method considers only a small number of shots and raw data. More shots are used with increasing frequency. The random-in-group subsampling method is used to rotate the shots between iterations and avoid the loss of shot information. By reducing the number of shots in the inversion, we decrease the computational cost. There is no crosstalk between shots, no noise addition, and no observational limits. Numerical modeling suggests that the proposed method reduces the computing time, is more robust to noise, and produces better velocity models when using data with noise.     

基于Born敏感核函数的VTI介质多参数全波形反演

本文基于VTI介质拟声波方程,利用散射积分原理,在Born近似下导出了速度与各向异性参数的敏感核函数,同时结合作者前期研究提出的矩阵分解算法实现了一种新的VTI介质多参数全波形反演方法.矩阵分解算法通过对核函数-向量乘进行具有明确物理含义的向量-标量乘分解累加运算实现目标函数一阶方向或二阶方向的直接求取,从而避免了庞大核函数矩阵与Hessian矩阵的存储,该方法同时可以大大降低常规全波形反演在计算二阶方向时的庞大计算量.为了克服不同参数对波场影响程度的不同,本文利用作者前期在VTI介质射线走时层析成像研究中提出的分步反演策略实现了多参数联合全波形反演.理论模型实验表明,本文提出的基于Born敏感核函数的各向异性矩阵分解全波形反演方法可以获得较好的多参数反演结果.     

Iterated extended Kalman filter method for time-lapse seismic full-waveform inversion

Time-lapse seismic data is useful for identifying fluid movement and pressure and saturation changes in a petroleum reservoir and for monitoring of CO₂ injection. The focus of this paper is estimation of time-lapse changes with uncertainty quantification using full-waveform inversion. The purpose of also estimating the uncertainty in the inverted parameters is to be able to use the inverted seismic data quantitatively for updating reservoir models with ensemble-based methods. We perform Bayesian inversion of seismic waveform data in the frequency domain by combining an iterated extended Kalman filter with an explicit representation of the sensitivity matrix in terms of Green functions (acoustic approximation). Using this method, we test different strategies for inversion of the time-lapse seismic data with uncertainty. We compare the results from a sequential strategy (making a prior from the monitor survey using the inverted baseline survey) with a double difference strategy (inverting the difference between the monitor and baseline data). We apply the methods to a subset of the Marmousi2 P-velocity model. Both strategies performed well and relatively good estimates of the monitor velocities and the time-lapse differences were obtained. For the estimated time-lapse differences, the double difference strategy gave the lowest errors.     

Characterization of a carbonate reservoir using elastic full-waveform inversion of vertical seismic profile data

Two-dimensional elastic full waveform inversion was applied to two lines extracted from a spiral three-dimensional vertical seismic profile data acquired in an oilfield offshore, Abu Dhabi, in the United Arab Emirates. The lines were selected to be parallel and perpendicular to the plane defined by the deviated borehole. The purpose of the inversion was to derive high-resolution elastic properties of the subsurface. After pre-processing, the data were band-pass filtered with a minimum frequency of 3.5 Hz and a maximum frequency of 30 Hz. A sequential inversion approach was used to mitigate non-linearity. The pre-processing of the data consisted in the removal of bad traces, followed by amplitude and phase corrections. High-resolution P- and S-wave velocity models that show good correlations with the available sonic logs were obtained. The results of the inversion suggest that the oilfield consists of a stack of layers with varying lithology, porosity and possibly fluid content.     

Using orthogonal Legendre polynomials to parameterize global geophysical optimizations: Applications to seismic-petrophysical inversion and 1D elastic full-waveform inversion

We use Legendre polynomials to reparameterize geophysical inversions solved through a particle swarm optimization. The subsurface model is expanded into series of Legendre polynomials that are used as basis functions. In this framework, the unknown parameters become the series of expansion coefficients associated with each polynomial. The aim of this peculiar parameterization is threefold: efficiently decreasing the number of unknowns, inherently imposing a 1D spatial correlation to the recovered subsurface model and searching for maximally decoupled parameters. The proposed approach is applied to two highly non-linear geophysical optimization problems: seismic-petrophysical inversion and 1D elastic full-waveform inversion. In this work, with the aim to maintain the discussion at a simple level, we limit the attention to synthetic seismic data. This strategy allows us to draw general conclusions about the suitability of this peculiar parameterization for solving geophysical problems. The results demonstrate that the proposed approach ensures fast convergence rates together with accurate and stable final model predictions. In particular, the proposed parameterization reveals to be effective in reducing the ill conditioning of the optimization problem and in circumventing the so-called curse-of-dimensionality issue. We also demonstrate that the implemented algorithm greatly outperforms the outcomes of the more standard approach to global inversion in which each subsurface parameter is considered as an independent unknown.     

Comparison of acoustic and elastic full-waveform inversion of 2D towed-streamer data in the presence of salt

Over the last years, full-waveform inversion has become an important tool in the list of processing and imaging technologies available to the industry. For marine towed-streamer data, full-waveform inversion is typically applied using an acoustic approximation because S-waves do not propagate in water and elastic effects in recorded data are generally assumed to be small. We compare acoustic and elastic modelling and full-waveform inversion for a field data set acquired offshore Angola over sediments containing a salt body with significant topology. Forward modelling tests reveal that such geological structures lead to significant mode conversions at interfaces and, consequently, to significant relative amplitude differences when elastically and acoustically modelled traces are compared. Using an acoustic approach for modelling in full-waveform inversion therefore leads to problems matching the synthetic data with the field data, even for recorded pressure data and with trace normalization applied. Full-waveform inversion is unable to find consistent model updates. Applying elastic full-waveform inversion leads to more consistent and reliable model updates with less artefacts, at the expense of additional computation cost. Although two-dimensional marine towed-streamer data are least favourable for the application of full-waveform inversion compared to three-dimensional data or ocean-bottom data, it is recommended to check on the existence of elastic effects before deciding on the final processing and imaging approach.     

Gravity compression forward modeling and multiscale inversion based on wavelet transform

The main problems in three-dimensional gravity inversion are the non-uniqueness of the solutions and the high computational cost of large data sets. To minimize the high computational cost, we propose a new sorting method to reduce fluctuations and the high frequency of the sensitivity matrix prior to applying the wavelet transform. Consequently, the sparsity and compression ratio of the sensitivity matrix are improved as well as the accuracy of the forward modeling. Furthermore, memory storage requirements are reduced and the forward modeling is accelerated compared with uncompressed forward modeling. The forward modeling results suggest that the compression ratio of the sensitivity matrix can be more than 300. Furthermore, multiscale inversion based on the wavelet transform is applied to gravity inversion. By decomposing the gravity inversion into subproblems of different scales, the non-uniqueness and stability of the gravity inversion are improved as multiscale data are considered. Finally, we applied conventional focusing inversion and multiscale inversion on simulated and measured data to demonstrate the effectiveness of the proposed gravity inversion method.     

多尺度地震资料联合反演方法研究

常规三维地面地震反演不可避免的存在多解性和分辨率不高的缺陷,而油藏地球物理阶段丰富的多尺度地震资料为减小多解性、提高分辨率提供了可能.基于贝叶斯反演理论,通过联合概率分布建立新的似然函数,将三维地面地震、VSP和井间地震三种多尺度资料有机地融合在一起,完善了多尺度地震资料联合反演框架及反演流程.模型测试及实际资料处理表明,联合反演算法有效地引入了小尺度地震资料中的高频信息对大尺度资料进行约束,反演结果在保留大尺度地震资料特征的基础上提高了分辨率,降低了多解性,同时促进了多种地震资料之间的相互匹配.     

基于叠前弹性阻抗反演的古近系流体识别

对于地震-地质条件十分复杂的古近系地层,Gassmann流体因子相对常规岩石物理参数通常具有更好的油气检测能力.然而,在由叠前反演结果计算流体因子的过程中往往会引入新的中间误差.为此,首先基于饱和流体多孔弹性介质理论推导了 Zoeppritz方程的Russell近似表达式,该方程将纵波反射系数表示为流体因子f、剪切模量...     

基于弹性阻抗的储层物性参数预测方法

储层物性参数是储层描述的重要参数,常规的基于贝叶斯理论的储层物性参数反演方法大多是通过反演获得的弹性参数进一步转换而获得物性参数,本文提出一种基于弹性阻抗数据预测储层物性参数的反演方法.该方法主要通过建立可以表征弹性阻抗与储层物性参数之间关系的统计岩石物理模型,联合蒙特卡罗仿真模拟技术,在贝叶斯理论框架的指导下,应用期望最大化算法估计物性参数的后验概率分布,最终实现储层物性参数反演.经过模型测试和实际资料的处理,其结果表明本文提出的方法具有预测精度高,稳定性强,横向连续性好等优点.     

基于入射角的两项流体阻抗反演方法

本文在孔隙弹性介质理论的指导下,基于入射角AVO近似方程推导了包含Russell流体项的两项AVO近似方程和相应的弹性阻抗方程,通过分析可知其精度符合反演要求.在贝叶斯理论框架下,建立了包含正则化约束的弹性阻抗反演方法,在此基础上直接提取Russell流体项.该方法可在缺少大角度叠前地震资料的情况下进行叠前直接反演得到流体因子,减少传统方法带来的累积误差.模型试算表明,该方法具有较好的准确度和稳定性.实际工区应用取得了良好的效果,表明该方法有实用性.     

基于改进NAD方法的频率域声波逆时偏移

逆时偏移成像具有高分辨率的特点,在频率域实施能提升偏移成像效率.数值求解波动方程是逆时偏移成像的关键环节,数值算法的优劣直接决定着偏移过程的计算效率与成像结果的质量.本文在频率域近似解析离散化（NAD）方法的基础上通过优化网格差分模板系数构造改进NAD方法,保证数值离散精度的同时可缓解阻抗矩阵的病态程度,以此提高频率域正演模拟的计算效率并将该方法运用于频率域声波逆时偏移.通过分别对凹陷模型、Sigsbee2B模型以及Marmousi模型进行偏移成像且与四阶标准NAD方法和四阶普通有限差分方法进行比较,改进NAD方法在压制数值频散与提高成像效率方面的优势得到了充分体现.

     

基于反演的衰减补偿方法(英文)

提高地震资料分辨率的一个有效途径就是衰减补偿,通过对地震波的衰减和频散效应进行校正,提高地震资料的分辨率。常规衰减补偿方法都是基于波场延拓的反Q滤波方法。本文利用Futterman衰减模型,导出了一种衰减介质中合成地震记录的计算方法,在此基础上将衰减补偿问题归结为一个Fredholm积分方程反问题,利用反演方法来实现衰减补偿。针对衰减补偿问题的不稳定性,利用Tikhonov正则化方法提高反演过程的稳定性,数值模拟资料和实际资料处理结果验证了方法的有效性。     

混合范数下的最优化反演方法

在求解地球物理反问题时,通常根据最小二乘准则构造目标函数进行反演,并在实践中得到了广泛的应用.为进一步增强反演的稳健性及减少多解性,不损失反演结果的分辨率,本文提出了混合范数下的最优化反演方法,它根据数据和模型可能服从不同的概率分布,对数据空间和模型空间采用不同的范数来构造目标函数.在给出目标函数的基础上,导出了混合范数下的线性反演方程.由于该线性反演方程的复杂性,我们采用混合范数下迭代再加权共轭梯度法进行求解.最后,通过对模拟的电阻率数据进行反演,验证了本文计算方法是可行的.     

基于贝叶斯理论的叠前多波联合反演弹性模量方法

AVO反演可以获得地层岩性和流体信息,而叠前反演问题都是高维的和非适定的,因此获得可靠稳定的解对叠前反演至关重要. 本文给出了一种基于贝叶斯理论的纵波和转换波联合反演密度比和模量比的方法. 鉴于剪切模量比、体积模量比可以更好地指示油气,基于岩石物理中速度比与模量比之间的关系,将此关系式代入Zoeppritz方程的近似形式Aki-Richards公式中,得到与模量比有关的反射系数近似公式. 联合纵波和转换波,利用最小二乘准则构建目标函数,最终反演出密度比、剪切模量比、体积模量比三个参数. 在反演过程中引入贝叶斯理论,假定先验信息服从高斯分布,待求参数服从改进的Cauchy分布,并去除待求参数之间的相关性. 利用模型数据和实际数据对本文方法进行测试,并与常规的单独利用纵波数据来反演方法进行比较,结果表明联合反演稳定性更好、精度更高、抗噪音能力更强,验证了本文方法的可行性和有效性.     

基于弹性波阻抗的拉梅参数反演与应用

(Connolly的弹性阻抗(EI)公式是纵、横波速度、密度和入射角的函数,应用该公式的常规反演方法只能直接得到纵、横波速度和密度的信息,而且不同角度的弹性阻抗在数值上差别很大,不在同一尺度上,无法进行对比。本文针对常规反演方法的缺点,提出了基于Gray的Zoeppritz近似方程的新的弹性阻抗公式,并对这个公式进行了标准化以实现不同角度的弹性阻抗在数值上的统一,最后用标准化后的公式进行了反演,利用拉梅参数与弹性阻抗问的线性关系可从反演得到的弹性阻抗数据体中直接提取得到拉梅参数。应用实例表明用这种方法提取得到的弹性参数更加稳定、准确,而且能很好地反映储层信息。这种新的方法是对以Connolly公式为基础的传统方法的改进。     

Lamé parameters inversion based on elastic impedance and its application

The Connolly (1999) elastic impedance (EI) equation is a function of P-wave velocity, S-wave velocity, density, and incidence angle. Conventional inversion methods based on this equation can only extract P-velocity, S-velocity, and density data directly and the elastic impedance at different incidence angles are not at the same scale, which makes comparison difficult. We propose a new elastic impedance equation based on the Gray et al. (1999) Zoeppritz approximation using Lamé parameters to address the conventional inversion method’s deficiencies. This equation has been normalized to unify the elastic impedance dimensions at different angles and used for inversion. Lamé parameters can be extracted directly from the elastic impedance data obtained from inversion using the linear relation between Lamé parameters and elastic impedance. The application example shows that the elastic parameters extracted using this new method are more stable and correct and can recover the reservoir information very well. The new method is an improvement on the conventional method based on Connolly’s equation. Wang Baoli graduated with a Bachelor’s degree in Prospecting Information and Engineering from the China University of Petroleum (East China) in 2004 and earned her Master’s degree from the department of Geophysical Prospecting and Information Technology in the China University of Petroleum ((East China) in 2006. She now studies for her PhD at the China University of Petroleum (East China). Her research interest is elastic impedance inversion.     

基于AVO反演的频变流体识别方法

研究表明流体引起衰减与频散往往表现为频变AVO现象.一些频散地震属性,例如纵波频散,已经证实为可靠的碳氢指示因子.为了更有效地识别流体,基于f-μ-ρ近似构建了新的流体因子Df,即频变流体项.该属性的反演首先需要连续小波变换(CWT)谱分解得到不同频带地震数据,通过去相关与先验约束来保证反演结果可靠性.模型试算证实了频变反射系数近似公式的精度可靠性,Df可以识别出强衰减介质所引起的频散现象.实际数据试算中,Df可以较好地识别储层孔隙流体,尤其对于气层,具有较好的指示效果.该流体因子将Gassmann流体项的高孔隙流体敏感性与叠前数据丰富的振幅频率信息相结合,反演效果与岩石物理认识相符.此研究有助于利用衰减频散现象借助AVO反演实现流体识别.