1887
ASEG2003 - 16th Geophysical Conference
  • ISSN: 2202-0586
  • E-ISSN:

Abstract

Seismic waveform inversion involves estimation of elastic properties by iterative fitting of seismic reflection data with synthetic seismograms. Like many other geophysical techniques, the inversion is applied to common mid point gathers assuming locally one-dimensional plane layered earth model. The objective of this paper is two fold. First, we address the critical issues of robustness, stability and uncertainty in which both global and local optimization methods are developed. An adaptive regularization scheme is developed that is used both in local optimization using a truncated Gauss-Newton algorithm and a global optimization based on very fast simulated annealing (VFSA). The 'regularization weight' is analogous to 'model temperature' of VFSA. The VFSA and local algorithm are used to take advantage of the two approaches. We demonstrate that the adaptive regularization is essential to improve on stability and robustness. The algorithm is inherently parallel and we carry out computation in a cluster of personal computers where load balancing is done carefully. Second, we apply our techniques to two sets of data, one from the Gulf of Thailand and the other from offshore Oregon. We are able to obtain very clear indication of free gas zones from the impedance and Poisson's ratio maps. These are then transformed into maps of saturation and porosity using a rock-physics model for use in reservoir characterization.

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/content/journals/10.1071/ASEG2003ab156
2003-08-01
2026-01-14
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References

  1. Castagna, I, and M. M. Backus, 1993, Offset dependent reflectivity: Theory and Practice of AVO analysis, SEG publications.
  2. Engl, H. W., 1987, Discrepancy principles of Tikhonov regularization of illposed problems leading to optimal convergence rates: J. Optim. Theo. And Appl,, 52, 209-215.
  3. McAuley, A., 1985, Prestack inversion with plane layer point source modeling: Geophysics, 50, 77-89.
  4. Menke, W., 1984, Geophysical Data Analysis: Discrete Inverse Theory. Academic Press, Inc.
  5. Roy, I. G., 2001, A robust descent type algorithm for geophysical inversion through adaptive regularization, Applied Mathematical Modeling, 26, 619-634.
  6. Sen, M.K., and P.L. Stoffa, 1995, Global Optimization Methods in Geophysical Inversion, Elsevier Science Publishing Co.
  7. Tarantola, A., 1984, Inverse Problem Theory: Methods of Data fitting and model parameter estimation, Elsevier Science Publications.
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  • Article Type: Research Article
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