共查询到18条相似文献，搜索用时 234 毫秒
1.
本文提出了一种新的基于正交多项式变换来压制动校正后CMP道集上随机噪声的方法,将地震资料经过正交多项式变换,建立正交多项式系数谱,该谱描述了地震资料在正交多项式域的能量分布,可以较好地分离有效波和随机噪声,相对于固定阶次的基于正交多项式变换压制噪声的方法,所提出的方法根据能量随阶次变化的规律,自适应确定表达有效信号的正交多项式阶次,既提高了信号和噪声的分离效果,又有效地保护了地震信号中的AVO信息,对人工合成数据和实际资料的处理结果表明了所提出方法的有效性. 相似文献
2.
水平叠加虽然在很大程度上压制了噪声,提高了地震剖面的信噪比,但CMP遭集上还存在不少不是一次波的规则干扰和随机噪声,不利于叠前资料的岩性反演和叠后资料的波阻抗反演.本文提出了基于改进的正交多项式变换压制地震资料中随机噪声的方法,其优势在于:通过对不同时间信号的奇异值分解,确定有效信号正交多项式系数谱的阶数;再利用小波变换,改善有效信号和噪声在低阶上的混叠.文中给出了具体处理的过程,数据试验和实际资料的处理结果表明该方法不仅能有效地压制噪声,而且还能较好地保护地震数据中AVO变化特征. 相似文献
3.
提出一种基于Radon 变换和正交多项式变换的多方向正交多项式变换压制多次波方法.抛物Radon变换对不同曲率方向的同相轴叠加,根据速度差异区分一次波和多次波,但Radon反变换会损伤振幅特性,不利于AVO分析.多方向正交多项式变换在Radon变换(某一曲率方向的零阶特性)的基础上,利用正交多项式变换进一步分析同相轴的高阶多项式分布特性,用正交多项式谱表征同相轴AVO特性;根据一次波和多次波速度差异和同相轴能量分布特征实现多次波压制.该方法的优点是仅用一个曲率参数就可描述同相轴剩余时差参数,提高了一次波和多次波的剩余时差分辨率.实验结果表明,该方法可以有效压制多次波并保留一次波AVO特性. 相似文献
4.
5.
地震波场模拟方法研究对于与波动现象有关的地震学问题的重要性是不言而喻的.就目前现有的各种正演算法来说,精度较高的算法（如有限元法、谱元法、高阶有限差分法等）,其计算速度较慢;计算速度较快的算法（如低阶有限差分法、付氏伪谱法等）计算精度却比较低.为了兼顾地震波场模拟的精度与速度,本文推出了一种快速的、高精度地震波场模拟方法（基于Forsyte广义正交多项式的褶积微分算子法）,该方法是以计算数学中的Forsyte广义正交多项式插值函数为基础,构建一个新的褶积微分算子,并将该算子引入到地震波动方程的一阶速度-应力方程的空间微分运算中去,采用时间交错网格有限差分算子替代普通的差分算子以匹配高精度的褶积微分算子,从而构造一种全新的地震波场数值模拟方法.该方法同时具有广义正交多项式方法的高精度和短算子低阶有限差分算法的高速度.通过对算子长度的调节及算子系数的优化,可同时兼顾波场解的全局信息与局部信息.复杂非均匀介质模型中的波场数值模拟实验证实了该方法的可行性及优越性. 相似文献
6.
海水与空气间的强波阻抗界面使得海洋地震数据普遍发育自由表面相关多次波,多次波信息的利用是提高海洋地震资料成像品质的新突破点.近年来发展了一系列多次波成像方法,干涉假象是制约其应用推广的关键问题之一.为了避免假象影响,本文提出了不同阶次自由表面相关多次波预测与成像方法,首先,修改了传统SRME(表面相关多次波衰减)方法中的边界条件,通过多次波升阶次与匹配相减的方法预测出不同阶次自由表面相关多次波;其次,基于单程波偏移算子和"面炮"偏移策略,以一次反射波或第(N-1)阶自由表面相关多次波为下行波场正向延拓,以第1阶多次或第N阶多次波为上行波场逆向延拓,并在每一层互相关成像得到第1阶或N阶多次波单独成像.本方法避免了低阶多次波和高阶多次波产生的相关假象,且相对于全波算子的偏移方法具有较高的计算效率,增强了多次波成像方法的实用性.单层模型和三层模型测试验证了本方法的正确性,并在我国某深海探区实际资料处理中得到了成功应用.相对于传统一次波成像,分阶次多次波成像具有更高的照明均衡度、垂向分辨率和信噪比.本研究表明,海洋多次波成像是一次波成像的有力补充,对于稳定海底沉积的深海地区,具有一定的应用前景. 相似文献
7.
反馈迭代法多次波衰减分为预测和相减两个步骤.在匹配相减过程中,当多次波和一次波同相轴不满足正交性,以及去除多次波后的地震记录不满足能量最小的情况下,最小二乘自适应匹配滤波方法不能获得正确的匹配,因此多次波的衰减产生误差.针对这两个问题,本文提出了基于1范数最小的均衡多道自适应匹配滤波法.该方法通过在空间方向上对地震记录进行均衡,避免了多次波和一次波同相轴正交的假设条件.同时利用了1范数对于大异常值保持稳健的特点,因此可以有效地解决去除多次波后的地震记录能量最小的问题.通过对模型数据和野外实际数据的多次波压制结果显示,该方法可以有效、准确地衰减多次波. 相似文献
8.
南海深水多次波成像 总被引：1，自引：0，他引：1
南海海域水深可达5 km,是我国未来油气勘探最有前景的区域.南海海域地震资料含有各种类型多次波,在地震成像前需将多次波去除.然而与传统的一次反射波偏移比较,多次波携带更多的地下结构信息,多次波偏移可提供更好的地下成像.本文提出了一种修改传统逆时偏移的方法,利用多次波进行成像.该方法用包含一次波和多次波的记录代替震源子波,用预测多次波代替一次反射波作为输入数据.在逆时偏移处理流程中,将地表多次波记录沿时间延拓到各个深度层,通过互相关成像条件将包含一次波和多次波的地震记录沿时间延拓到相同深度层.将多次波偏移结果与一次波偏移结果的差应用目标函数进行匹配,弥补一次波偏移的不足.对Sigsbee2B数据做数值测试的结果表明与传统一次反射波偏移相比,该方法可以得到范围更大、均衡性更好的地下照明度.将该方法应用到南海深水实际资料成像,获得了南海深水地震资料多次波成像剖面.偏移结果表明,多次波成像可以弥补反射波照明的不足,由此说明多次波偏移是未来的一个重要研究方向. 相似文献
9.
提出了一种用于水平成层场地地震反应分析的时域高阶显式算法. 首先,将覆盖土层和基岩划分为若干个切比雪夫谱单元,在模型底部设置多次透射人工边界;其次,以切比雪夫正交多项式构建高阶单元位移模式,通过高斯?洛巴托积分严格导出对角形式的切比雪夫谱单元集中质量矩阵,结合中心差分时域逐步积分格式,建立了高效的集中质量切比雪夫谱元波动模拟方法;最后,利用日本Kik-net强震台网提供的不同类型场地上获得的实际地震观测记录检验了本文方法的有效性. 该方法避免了传统切比雪夫谱元法由于具有一致质量矩阵形式而造成的计算效率不高的问题。数值结果表明,本文方法能够较好地预测Ⅰ1,Ⅱ和Ⅳ类场地在较弱地震和中等强度地震作用下的地面运动特征,每个波长内仅需布置少量单元即可取得较高精度的计算结果。 相似文献
10.
《地球物理学进展》2017,(2)
陆架浅水区是我国海洋油气勘探的主战场.对于陆架浅水区地震资料,自由表面多次波为主要的多次波类型.浅水区自由表面多次波能量强、周期短、阶次高,近偏移距处直达波和海底反射难以区分的特点使得基于反馈迭代的自由表面多次波压制方法或是基于多次波周期性的预测反褶积方法应用效果不佳.本文将自由表面多次波分为水层(海面和海底间)多次波和非水层多次波.对于水层多次波,使用确定性水层多次波压制方法,该方法能够适应浅水区较差的近偏移距插值结果.阐述了方法原理及实现过程.在水层多次波压制后切除海底,使用传统的反馈迭代多次波压制方法来压制非水层自由表面多次波.来自东海陆架盆地的实际数据处理结果表明这一处理思路能较好地压制自由表面多次波,有助于提升陆架浅水区地震资料的成像质量. 相似文献
11.
Inversion for S-wave velocities from the amplitude variation with offset of P-wave data is far from being a standard routine in the seismic processing sequence. However, the need for tracking the amplitude versus offset (AVO) occurs in several situations, for example in order to estimate the zero-offset amplitude, to reveal areas with particular AVO characteristics, or to compress the AVO so that it is more easily obtainable at a later stage of the seismic processing. Furthermore, weak reflections can occasionally, due to the effect of the angle-dependent reflectivity, have a polarity-shift with offset, resulting in a very poor, or even vanishing, stack response. In such cases, the reflection event has to be represented by some other property than its mean amplitude or stack value. We outline how the AVO of seismic data may be extracted and classified by the use of orthogonal polynomials. The main advantage of this method compared to a general polynomial fit is that the AVO may be classified by a unique Spectrum of polynomial coefficients. This is in analogy to Fourier coefficients where the orthogonal basis is harmonic functions. The set of orthogonal polynomials is constructed entirely from the set of offset coordinates, and these polyno-mials are defined only on the offset window considered. Compared to a Fourier transform, this is a major advantage since there is no effect of a limited spatial bandwidth. The AVO of normal-moveout corrected data may be represented by a data gather where the orthogonal polynomial coefficients are given as time traces with each trace revealing a certain AVO characteristic. For instance, the stack is proportional to the zeroth-order coefficient, the mean gradient is given by the firstorder coefficient, while the second-order coefficient indicates whether the AVO increases and then decreases, or vice versa. 相似文献
12.
13.
基于非稳态多项式拟合的地震噪声衰减方法研究(英文) 总被引：1，自引：0，他引：1
基于非稳态多项式拟合理论,针对地震数据中同相轴振幅变化这一特征,我们提出了一种地震噪声衰减的新方法。非稳态多项式拟合系数是时变的,通过整形正则化约束多项式拟和系数的光滑性,自适应的估计地震数据的相干分量。基于动校正后的共中心点道集(CMP)中地震信号的相干性,利用非稳态多项式拟合估计有效信号,从而衰减随机噪声。对于线性相干噪声,如地滚波,首先利用径向道变换(RadialTraceTransform,RTT)将地震数据变换到时间一视速度域,在时间—视速度域利用非稳态多项式拟合估计出相干噪声,然后减去相干噪声。该方法可以有效的估计振幅变化的相干分量,不需要相干分量振幅为常量的假设。模拟和实际资料处理结果表明,与传统的稳态多项式拟合和低切滤波相比,该方法可以更为有效的衰减地震噪声,同时保真了地震有效信号。 相似文献
14.
The compression of seismic signals which have propagated through a dispersive medium can be achieved by a frequency-domain transformation. This transformation is formally related to the dispersion characteristic of the medium and is independent of phase and group velocities. By defining a suitable cost-function to measure the degree of dispersion of a time- signal, an iterative technique can be employed to find that transformation which gives minimum dispersion. In this paper, we assume that the inverse of the dispersion characteristic can be adequately approximated by a finite polynomial in the region of maximum signal energy density. The coefficients of this polynomial are the parameters of dispersion of the medium. These parameters can be estimated both in the presence of noise and in the case of signals made up of multiple arrivals. The techniques developed in this paper are applied to seismic signals which have been recorded underground by a set of geophones designed to detect and map discontinuities in coal-seams. Results of dispersion estimation and signal compression are discussed for data collected in the Blackshale seam, Pye Hill Colliery, near Derby, in the United Kingdom. 相似文献
15.
传统CSEM一般只提取主频信号,或以谐波与主频的振幅比为依据提取部分低阶谐波信号,但缺乏判断标准,实际操作中存在很大的不确定性.本文基于小波变换和希尔伯特解析包络提出一种新的CSEM信号噪声评价方法,首先在时间域中基于混合基快速傅里叶变换获得原始信号准确功率谱;其次在频率域中根据CSEM频率位置相邻频率幅值进行频谱预处理,基于离散小波变换将预处理后的频谱分成低频部分和高频部分,基于希尔伯特变换识别高频部分的上包络线,并与低频部分重构得到频谱的整体上包络线;最后根据包络线与对应CSEM频率振幅的比值估计噪声的影响幅度,根据阈值筛选出高信噪比的主频和谐波信号.本方法不需增加野外工作量即可提取大量的频率信号,特别是高阶谐波信号,实现频率加密,提高CSEM的纵向分辨能力和能源利用率. 相似文献
16.
17.
In this paper, we discuss high‐resolution coherence functions for the estimation of the stacking parameters in seismic signal processing. We focus on the Multiple Signal Classification which uses the eigendecomposition of the seismic data to measure the coherence along stacking curves. This algorithm can outperform the traditional semblance in cases of close or interfering reflections, generating a sharper velocity spectrum. Our main contribution is to propose complexity‐reducing strategies for its implementation to make it a feasible alternative to semblance. First, we show how to compute the multiple signal classification spectrum based on the eigendecomposition of the temporal correlation matrix of the seismic data. This matrix has a lower order than the spatial correlation used by other methods, so computing its eigendecomposition is simpler. Then we show how to compute its coherence measure in terms of the signal subspace of seismic data. This further reduces the computational cost as we now have to compute fewer eigenvectors than those required by the noise subspace currently used in the literature. Furthermore, we show how these eigenvectors can be computed with the low‐complexity power method. As a result of these simplifications, we show that the complexity of computing the multiple signal classification velocity spectrum is only about three times greater than semblance. Also, we propose a new normalization function to deal with the high dynamic range of the velocity spectrum. Numerical examples with synthetic and real seismic data indicate that the proposed approach provides stacking parameters with better resolution than conventional semblance, at an affordable computational cost. 相似文献
18.
Oil and gas exploration gradually changes to the deep and complex areas. The quality of seismic data restricts the effective application of conventional time-frequency analysis technology, especially in the case of low signal-to-noise ratio. To address this problem, we propose a curvelet-based time-frequency analysis method, which is suitable for seismic data, and takes into account the lateral variation of seismic data. We first construct a kind of curvelet adapted to seismic data. By adjusting the rotation mode of the curvelet in the form of time skewing, the scale parameter can be directly related to the frequency of the seismic data. Therefore, the curvelet coefficients at different scales can reflect the time-frequency information of the seismic data. Then, the curvelet coefficients, which represent the dominant azimuthal pattern, are converted to the time-frequency domain. Since the curvelet transform is a kind of sparse representation for the signal, the screening process of the dominant coefficient masks most of the random noise, which enables the method to adapt for the low signal-to-noise ratio data. Results of synthetic and field data experiments using the proposed method demonstrate that it is a good approach to identify weak signals from strong noise in the time-frequency domain. 相似文献