3D高阶抛物Radon变换在不规则地震数据保幅重建中的应用

3D地震数据不规则采样缺失重建是地震勘探数据处理流程中的重要问题.本文提出了一种基于具有保幅特性的非均匀高阶抛物Radon变换(NHOPRT)地震数据重建方法.在最小二乘反演方程中引入Delaunay三角网格剖分来计算空间不规则加权系数,从而获得最接近完整规则数据的高阶抛物Radon变换域系数.在用SVD求解反演方程过程中,利用高阶抛物Radon变换算子在频率域为指数函数,具有线性可分解特性,将二维空间的高阶抛物Radon变换算子分解为两个独立的一维空间变换算子,减小了变换算子的矩阵大小,从而很大程度地提高了计算效率.理论模型和实际地震数据重建测试证明了本文方法的有效性以及实用性.     

λ-f域加权抛物Radon变换地震数据重建方法研究

大多数地震处理技术都要求地震数据具备完整性和规则性,然而,由于诸多因素的影响,地震勘探所采集到的资料普遍存在数据缺失,需要对地震数据进行重建.本文在传统Radon变换重建的基础上提出一种λ-f域加权抛物Radon变换的地震数据重建方法.通过引入新变量λ,消除了Radon变换算子对频率的依赖,使得Radon变换算子及算子的逆只需计算一次,显著提高了计算效率.同时,在λ-f域抛物Radon变换迭代计算过程中引入变化的权系数,更好地实现了λ-f域的能量聚焦.理论模型及实际数据试算表明,文中方法对地震数据重建精度较高,单道对比吻合较好.     

快速3D抛物Radon变换地震数据保幅重建

为解决3D AVO地震数据快速保幅重建问题,在传统3D抛物Radon变换的基础上提出一种3D快速高阶抛物Radon变换方法.该方法将传统抛物Radon变换与正交多项式相结合,通过正交多项式系数描述地震数据AVO信息,确保重建后的地震数据具有良好保幅效果.同时,该方法引入新变量λ_x=q_xf和λ_y=q_yf,通过对q_xf和q_yf的整体采样,消除了3D高阶抛物Radon变换算子对频率的依赖,使变换算子的求逆过程仅需计算一次,大大节省计算时间.理论模型和实际地震资料的处理结果表明,该方法重建效率高,保幅效果良好.     

基于3D加权高阶抛物Radon变换远偏移距地震数据保幅重建

在深部地震勘探中,远偏移距数据缺失重建是非常重要的工作.利用抛物Radon变换方法重建时,经过部分动校正后的数据在近偏移距和中偏移距的同相轴近似于抛物型,但是处于远偏移距位置的同相轴偏离于抛物型,特别是浅层同相轴,会导致远偏移距缺失的数据重建效果不佳.本文基于高阶抛物Radon变换地震数据保幅重建理论,重点分析了不同偏移距以及缺失程度对重建效果的影响,提出根据数据缺失模型来确定迭代过程中加权系数的3D高阶抛物Radon变换重建方法.同时,在反演求解目标函数的最小二乘解时应用SVD方法来求解Radon域系数,得到高精度的求解结果.该方法在大道间距数据内插、远偏移距缺失数据重建中都取得满意的效果.     

3D高阶抛物Radon变换地震数据保幅重建

本文结合传统3D抛物Radon变换（PRT）和AVO数据正交多项式拟合,给出了3D高阶抛物Radon变换方法（HOPRT）.该变换增加了描述AVO数据变化的梯度信息和曲率信息,拓展了传统3D抛物Radon变换方法,使其在具有AVO特征的数据重建中具有更高的准确度,从而提高AVO分析的可靠性.文中给出了3D高阶抛物Radon变换进行地震数据保幅重建的流程.理论模型和实际地震资料的重建结果显示了本文方法的优点.     

反假频时延Radon变换多次波压制方法研究

多次波压制是地震数据处理的重要环节之一,而Radon变换方法以其优势被广泛应用于多次波处理环节中.本文提出利用时间延迟量Γ代替传统抛物Radon变换的曲率参数q,对地震记录同相轴进行积分运算.当使用时延Radon变换时,输入数据的道数作为重要参数直接影响Radon变换域的假频,而非传统抛物Radon变换空间方向的采样间隔.使用预条件算子通过重建间接增加输入数据的道数,消除Radon域的假频问题,提高成像精度,进而更好的实现多次波压制.利用本文方法对水平层状介质和复杂模型数据进行试算,结果表明,Radon域假频得到有效抑制,多次波压制效果明显.     

加权抛物Radon变换叠前地震数据重建

基于部分动校正（NMO）后反射同相轴在CMP道集上的抛物线走时近似，给出了加权抛物Radon变换叠前地震数据重建方法（WPRT）. WPRT通过在迭代过程中引入变化着的权系数，拓展和改进了传统抛物Radon变换方法，使其可同时完成不规则采样的规则化和空道及近偏移距道重建，且有更高的计算效率. 文中给出了应用WPRT进行近偏移距和中偏移距的空地震道重建及数据规则化的算法实现. 理论模型和实际地震资料的地震数据重建结果显示了本文算法的优点.     

抛物Radon变换法近偏移距波场外推

本文给出了抛物Radon变换的基本原理,以及部分动校正后的CMP道集抛物线近似有效性的证明,基于带限正反最小平方抛物Radon变换的Levinson递推算法,对缺失的近偏移距地震波场进行叠前重建和外推.给出了抛物Radon变换法地震道重建外推的基本原理和叠前地震数据规则化的处理流程,另外对于Radon域均匀采样的情形,本文给出了均匀层状介质和Marmousi模型的近偏移距外推结果,计算结果验证了算法的稳定性和适用性.     

基于多路径Radon变换的地震数据噪声压制和波型分离方法研究

Radon变换是一种稀疏变换,被广泛应用于地震数据处理,其中线性Radon和抛物Radon最为常用.在实际地震数据中,直达波和面波的同相轴形态为线性,反射波为双曲型,单独使用线性Radon或抛物Radon变换时,不能确保所有同相轴在变换域的系数都是稀疏的,影响地震数据处理效果.本文提出的多路径Radon变换联合了线性R...     

混合域高分辨率抛物Radon变换及在衰减多次波中的应用

高分辨率Radon变换存在计算效率和分辨率不能兼得的困境.时间域算法可以获得很高的分辨率,但计算效率非常低;频率域算法具有良好计算效率,但分辨率不理想.为此发展了混合域高分辨率抛物Radon变换,即对频率域抛物Radon变换引入时变的稀疏权.本文给出了一种新的混合域高分辨率抛物Radon变换实现方法,并将该算法应用于叠前数据衰减多次波.文中给出了Radon变换和衰减多次波的流程.理论和实际数据算例表明本文方法既有较高的分辨率又有很高的计算效率.     

3D simultaneous seismic data reconstruction and noise suppression based on the curvelet transform

Seismic data contain random noise interference and are affected by irregular subsampling. Presently, most of the data reconstruction methods are carried out separately from noise suppression. Moreover, most data reconstruction methods are not ideal for noisy data. In this paper, we choose the multiscale and multidirectional 2D curvelet transform to perform simultaneous data reconstruction and noise suppression of 3D seismic data. We introduce the POCS algorithm, the exponentially decreasing square root threshold, and soft threshold operator to interpolate the data at each time slice. A weighing strategy was introduced to reduce the reconstructed data noise. A 3D simultaneous data reconstruction and noise suppression method based on the curvelet transform was proposed. When compared with data reconstruction followed by denoizing and the Fourier transform, the proposed method is more robust and effective. The proposed method has important implications for data acquisition in complex areas and reconstructing missing traces.     

Full waveform inversion and the truncated Newton method: quantitative imaging of complex subsurface structures

Full waveform inversion is a powerful tool for quantitative seismic imaging from wide‐azimuth seismic data. The method is based on the minimization of the misfit between observed and simulated data. This amounts to the solution of a large‐scale nonlinear minimization problem. The inverse Hessian operator plays a crucial role in this reconstruction process. Accounting accurately for the effect of this operator within the minimization scheme should correct for illumination deficits, restore the amplitude of the subsurface parameters, and help to remove artefacts generated by energetic multiple reflections. Conventional minimization methods (nonlinear conjugate gradient, quasi‐Newton methods) only roughly approximate the effect of this operator. In this study, we are interested in the truncated Newton minimization method. These methods are based on the computation of the model update through a matrix‐free conjugate gradient solution of the Newton linear system. We present a feasible implementation of this method for the full waveform inversion problem, based on a second‐order adjoint state formulation for the computation of Hessian‐vector products. We compare this method with conventional methods within the context of 2D acoustic frequency full waveform inversion for the reconstruction of P‐wave velocity models. Two test cases are investigated. The first is the synthetic BP 2004 model, representative of the Gulf of Mexico geology with high velocity contrasts associated with the presence of salt structures. The second is a 2D real data‐set from the Valhall oil field in North sea. Although, from a computational cost point of view, the truncated Newton method appears to be more expensive than conventional optimization algorithms, the results emphasize its increased robustness. A better reconstruction of the P‐wave velocity model is provided when energetic multiple reflections make it difficult to interpret the seismic data. A better trade‐off between regularization and resolution is obtained when noise contamination of the data requires one to regularize the solution of the inverse problem.     

Fourier reconstruction with sparse inversion

The problem of seismic data reconstruction is posed as an inverse problem where the objective is to obtain the Fourier coefficients that synthesize the signal. Once the coefficients have been found, they are used to reconstruct the data on a uniformly spaced grid. A non‐quadratic model weight function is included to stabilize the inversion and to provide the additional information required to interpolate through gaps. In the reconstruction of a non‐uniformly sampled trace, an image and a marine 3D VSP shot‐record, the method shows improved reconstruction in large gaps and is less sensitive to the spatial bandwidth used in the inversion compared to Fourier reconstruction without the non‐quadratic model weight function.     

基于非均匀曲波变换的高精度地震数据重建

在野外数据采集过程中,空间非均匀采样下的地震道缺失现象经常出现,为了不影响后续资料处理,必须进行高精度数据重建.然而大多数常规方法只能对空间均匀采样下的地震缺失道进行重建,而对于非均匀采样的地震数据则无能为力.为此本文在以往多尺度多方向二维曲波变换的基础上,首先引入非均匀快速傅里叶变换,建立均匀曲波系数与空间非均匀采样下地震缺失道数据之间的规则化反演算子,在L1最小范数约束下,使用线性Bregman方法进行反演计算得到均匀曲波系数,最后再进行均匀快速离散曲波反变换,从而形成基于非均匀曲波变换的高精度地震数据重建方法.该方法不仅可以重建非均匀带假频的缺失数据,而且具有较强的抗噪声能力,同时也可以将非均匀网格数据归为到任意指定的均匀采样网格.理论与实际数据的处理表明了该方法重建效果远优于非均匀傅里叶变换方法,可以有效地指导复杂地区数据采集设计及重建.     

表驱动的二维非规则采样快速傅里叶变换

非规则采样快速傅里叶变换（NFFT）主要用于快速计算非规则采样数据的频谱及重建.该方法为非规则采样数据频谱重建技术的核心算法.在实现NFFT算法时,高速度和高精度计算是其应用的前提和关键.本文针对二维NFFT计算效率,应用表驱动思路进行改进,将Gauss褶积算子由矩形改进为椭圆以减少计算量,将e指数计算改进为乘法以加快计算速度,并建表解决NFFT算法在地震资料处理中的应用问题.本文同时给出了非规则采样地震数据NFFT谱重建方法.最后本文给出算例验证提出方法的计算速度和精度,和非规则采样地震资料重建结果.     

地震数据互相关驱动的多道反演方法

地震反演是储层定量描述和地震油气识别的关键技术,反演结果在复杂构造区域的横向连续性和保真性是影响地震资料定量解释精度的重要因素.基于此,本文发展了地震数据互相关驱动的多道反演方法.考虑地层反射系数与地震数据在结构上具有相似性的特点,基于地震数据互相关描述地层反射系数的结构特征,并将其作为多道地震反演的横向约束条件;此外,为改善地震数据本身横向连续性差对反演结果的影响,在目标泛函的惩罚项中引入局部优化算子,构建了一个易于求解的多道地震反演目标泛函.与常规多道地震反演方法相比,本文方法能够设计更合理、更符合实际情况的横向约束算子,提高反演结果的横向连续性,并且能有效降低地震资料质量对反演结果的影响.模型测试和实际应用验证了本方法的可靠性和稳定性.     

A fast joint seismic data reconstruction by sparsity‐promoting inversion

Seismic field data are often irregularly or coarsely sampled in space due to acquisition limits. However, complete and regular data need to be acquired in most conventional seismic processing and imaging algorithms. We have developed a fast joint curvelet‐domain seismic data reconstruction method by sparsity‐promoting inversion based on compressive sensing. We have made an attempt to seek a sparse representation of incomplete seismic data by curvelet coefficients and solve sparsity‐promoting problems through an iterative thresholding process to reconstruct the missing data. In conventional iterative thresholding algorithms, the updated reconstruction result of each iteration is obtained by adding the gradient to the previous result and thresholding it. The algorithm is stable and accurate but always requires sufficient iterations. The linearised Bregman method can accelerate the convergence by replacing the previous result with that before thresholding, thus promoting the effective coefficients added to the result. The method is faster than conventional one, but it can cause artefacts near the missing traces while reconstructing small‐amplitude coefficients because some coefficients in the unthresholded results wrongly represent the residual of the data. The key process in the joint curvelet‐domain reconstruction method is that we use both the previous results of the conventional method and the linearised Bregman method to stabilise the reconstruction quality and accelerate the recovery for a while. The acceleration rate is controlled through weighting to adjust the contribution of the acceleration term and the stable term. A fierce acceleration could be performed for the recovery of comparatively small gaps, whereas a mild acceleration is more appropriate when the incomplete data has a large gap of high‐amplitude events. Finally, we carry out a fast and stable recovery using the trade‐off algorithm. Synthetic and field data tests verified that the joint curvelet‐domain reconstruction method can effectively and quickly reconstruct seismic data with missing traces.     

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.     

基于逆算子估计的AVO反演方法研究

传统反演算法以优化算法为主,而基于逆算子估计的AVO反演算法则利用了直接求逆的思路.算法的关键在于寻找存在逆函数的子域,进而可以在子域内直接求逆,这种解决反问题的思路不同于一般的优化类算法所采用的直接搜索解的方式,具有更高的效率.AVO反演利用了振幅随着偏移距的变化特征,反演的精度受到地震资料质量的影响,通过加入L1范数约束以及合理的初始模型有助于提高反演的稳定性以及准确度.模型测算和实际应用表明,基于逆算子估计的AVO反演方法具有较高的精确程度和可靠性.