褶积模型

  • 网络convolution model
褶积模型褶积模型
  1. 沃尔什(Walsh)函数法叠后相对层速度反演是以叠后地震道的褶积模型为基础的。

    Poststack relative interval velocity inversion using Walsh function is based on the convolution model of poststack seismic traces .

  2. 本文中,基于多分量矢量褶积模型,我们导出了一个针对多源多分量数据的地表层算法。应用计算反射系数的Zoeppritz方程,实施海底多波多分量数据的弹性参数的多尺度AVO反演。

    A surface layer correction algorithm for multisource and multicomponent VSP data has been developed on the basis of multicomponent vector convolution model . We adopt Zoeppritz equation to carry out multiscale AVO inversion of elastic parameters on multi-wave seismic data under seabed .

  3. 地震褶积模型在地震记录反演中被广泛采用。

    Seismic convolution model is widely used to model seismic records .

  4. 褶积模型参数估计的递归算法及其收敛性

    A Recursive Arithmetic and Its Convergence on Convolutional Model-Parameters

  5. 新的褶积模型较常见的地震记录褶积模型增加了一个延迟误差量。

    The new convolution model has one delay error term more than conventional one .

  6. 含透射衰减的地震反射信号褶积模型在波阻抗反演中的应用

    Seismic convolution model with transmission attenuation coefficient

  7. 新的地震记录褶积模型

    A new seismic convolution model

  8. 另一方面重点研究了褶积模型地震波场数值模拟方法。

    On the other hand we focused on the convolution model for numerical simulation of seismic wave method .

  9. 设计了几组典型模型,用褶积模型制作合成地震记录,然后分别计算它们的瞬时谱属性。

    Several typical models were designed to get their seismic synthetic data and their instantaneous attributes were extracted individually .

  10. 我们仍然利用褶积模型理论,作为研究转换波正、反演问题基本理论。

    We can also regard the convolution model theory as the basic theory for studying the forward and inversion problem .

  11. 利用褶积模型制作人工合成地震记录,进而标定层位是地震资料解释的基础工作。

    It is basic work for seismic data interpretation by using convolution model for making synthetic seismogram and then marking event .

  12. 地震资料解释经常用到正演模型,常规的褶积模型不能模拟地震波的动力学特征。

    Forward modeling is often used in explaining of seismic data , because conventional convolution model can 't simulate the features of the dynamics of elastic wave .

  13. 采用含透射衰减的褶积模型做正演运算,能够校正地层透射对波阻抗反演结果的影响,尤其能够消除地层的屏蔽现象。

    Seismic data processing practices demonstrate that the seismic convolution model can be used to correct transmission attenuation component by means of impedance inversion , with the merit of avoiding the screen effect of strata .

  14. 简单的褶积模型和复杂的有限差分模型资料处理结果表明,本文提出的方法可以有效地分离一次波和多次波。

    The method has been applied to several synthetic datasets generated by simple convolution and finite-difference model ( FDM ) technique , and the results show that our method can separate primary wave and multiple wave effectively .

  15. 第二、根据基于控制点二维封闭结构地质体模型建立的策略,掌握了褶积模型正演方法并进行复杂的波场数值试验,并和其他方法比较,其成像效果很理想。

    Secondly , two dimension closed structure geological models were created on the base of control points . methods of deconvolution and forward modeling is performed and the numerical experiments for complex wave field had been done .

  16. 地震资料在测井资料约束下可以进行反演,以求取地下波阻抗,主要有两种方法:基于褶积模型的波阻抗反演方法和基于波动方程的波阻抗反演方法;

    Under control of well logging data , there are two important methods to get wave impedance from seismic data inversion : wave impedance inversion method based on convolution model and wave impedance inversion method based on wave equation .

  17. 根据层序地层学原理,分析了高分辨率地震资料的特点,并据此提出了一个地震层序模型,以代替地震褶积模型,用以评价地震分辨率的可靠性。

    Based on the principle of sequence stratigraphy , through analyzing the features of high resolution seis - mic data , a seismic sequence model is proposed to substitute the seismic convolution model , so as to evaluate the reliability of seismic resolution .

  18. 该方法以地震记录和子波作为输入,结合地震记录的褶积模型构造线性方程,通过求解线性方程得到消除气泡效应的地震记录。

    This method is based on the convolution model of seismic data , the seismic data and the wavelet is the input , form a linear equation by the seismic data and the wavelet , the debubbling record can be by solving the linear equation .

  19. 本文针对合成地震记录制作和使用中存在的问题,系统地分析了合成地震记录和地震剖面的相关性因素,指出从声波测井曲线和褶积模型两方面改进合成地震记录的质量。

    In view of the problems encountered in synthesizing seismograms and their application , this paper systematically analyzes the factors which are in control of the resemblance between synthetic seismograms and field data and suggests to improve synthetic seismograms ' quality using sonic log and convolution models .