1887

Abstract

Summary

Seismic AVO inversion for elastic parameters jointly with litho-fluid categories from migrated seismic data is now an established technique. Compared to conventional techniques based on adding smooth background models to impedance inversions, it has several advantages, including the ability to constrain elastic parameters to welllog-data distributions, and ability to directly predict fluids. These methods rely on the migrated amplitudes being inverted being faithfully scaled to reflectivity, and are vulnerable to the presence of non--primary seismic energy which is not modelled by conventional Born-style imaging, such as mode conversions or multiples. In any deconvolutional style inversion such wave energy adds to the noise rather than the signal. We show that it is possible to perform joint elastic/facies inversion on raw shot records, using a full-wave modelling operation in the likelihood of a hierarchical Bayesian inversion, with optimisation performed using the expectation-maximisation algorithm. Such full wave techniques can in principle model all wave modes, and should theoretically have higher S/N ratios than their AVO equivalents. Illustrative examples in high--contrast lithologies using joint acoustic/facies full wave inversion show that cleaner inversions are produced in this regime compared to convolutional methods based on traditional imaging.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.201902265
2019-09-02
2020-08-12
Loading full text...

Full text loading...

References

  1. Fjeldstad, T. and Grana, D.
    [2018] Joint probabilistic petrophysics-seismic inversion based on Gaussian mixture and Markov chain prior models. Geophysics, 83(1), R31-R42.
    [Google Scholar]
  2. Gunning, J. and Sams, M.
    [2018] Joint facies and rock properties Bayesian amplitude-versus-offset inversion using Markov random fields. Geophysical Prospecting, 66(5), 904–919.
    [Google Scholar]
  3. Symes, W.W.
    [2009] The seismic reflection inverse problem. Inverse Problems, 25.
    [Google Scholar]
  4. Ulvmoen, M. and Omre, H.
    [2010] Improved resolution in Bayesian lithology/fluid inversion from prestack seismic data and well observations: Part 1 — Methodology. Geophysics, 75(2), R21-R35.
    [Google Scholar]
  5. Virieux, J. and Operto, S.
    [2009] An overview of full-waveform inversion in exploration geophysics. Geophysics, 74(6), WCC1-WCC26.
    [Google Scholar]
  6. Wainwright, M.J. and Jordan, M.I.
    [2008] Graphical Models, Exponential Families, and Variational Inference. Found. Trends Mach. Learn., 1, 1–305.
    [Google Scholar]
http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.201902265
Loading
/content/papers/10.3997/2214-4609.201902265
Loading

Data & Media loading...

This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error