Born Inversion with a Stratified Reference Velocity.

Abstract

Carter and Frazer (1984), and Bleistein and Gray (1984), presented inversion algorithms which included the effect of a stratified reference velocity, c(z). Those papers did not address the question of obtaining accurate values of the reflection coefficient, this is the issue treated here. Thus, in the language of Bleistein, Cohen and Hagin (1984), the earlier algorithms provided structural inversions, the location of the subsurface layers, whereas the present algorithm also provides an accurate estimate off the reflectivity function, which depicts the reflectors and provides an estimate of the reflection strengths across the layers. Since we employ a perturbation assumption ('the Born Approximation' ), the constant reference speed inversion first described in Bleistein and Cohen (1979a) and reviewed in BCH, is often not adequate at depth. Although recursive use of the algorithm is possible and although the results can be significantly enhanced by suitable pre- or post-processing (e.g., see Hagin and Cohen (1984), extension of the perturbation method to a stratified reference profile is highly significant. It is far more likely that the actual velocity function can be well approximated by a stratified reference velocity than by a constant one, which in turn enhances the validity of the perturbation assumption and the inversion results.

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Document Details

Document Type
Technical Report
Publication Date
Dec 08, 1984
Accession Number
ADA149222

Entities

People

  • F. G. Hagin
  • J. K. Cohen

Organizations

  • Colorado School of Mines

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Boltzmann Equation
  • Born Approximations
  • Computations
  • Data Processing
  • Delta Functions
  • Differential Equations
  • Equations
  • Frequency
  • Integral Equations
  • Mathematical Analysis
  • Military Research
  • Reflectivity
  • Reflectors
  • Surface Properties
  • Wave Equations
  • Wave Phenomena

Readers

  • Finite Element Method (FEM) for solving Partial Differential Equations (PDEs)
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Spectroscopy.