https://github.com/hbueno/eage2016-avo
Code for "Global optimization for AVO inversion: a genetic algorithm using a table-based ray-theory algorithm" presented at the 78th EAGE Conference and Exhibition 2016.
https://github.com/hbueno/eage2016-avo
avo density genetic-algorithm global-optimization seismic velocity
Last synced: 5 months ago
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Code for "Global optimization for AVO inversion: a genetic algorithm using a table-based ray-theory algorithm" presented at the 78th EAGE Conference and Exhibition 2016.
- Host: GitHub
- URL: https://github.com/hbueno/eage2016-avo
- Owner: hbueno
- Created: 2017-04-06T20:03:59.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2017-04-07T18:26:02.000Z (about 9 years ago)
- Last Synced: 2025-05-31T03:34:16.339Z (about 1 year ago)
- Topics: avo, density, genetic-algorithm, global-optimization, seismic, velocity
- Language: PostScript
- Homepage: http://dx.doi.org/10.3997/2214-4609.201600847
- Size: 1.28 MB
- Stars: 7
- Watchers: 2
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
Abstract submitted to the [78th EAGE Conference & Exhibition 2016](http://www.eage.org/event/index.php?eventid=1391).
Dates: 30 May - 2 June 2016.
Location: Reed Messe Wien, Vienna, Austria.
Deadline to submit the expanded abstract: 15 of January 2016.
Published expanded abstract:
[DOI: 10.3997/2214-4609.201600847](http://dx.doi.org/10.3997/2214-4609.201600847)
Citation:
> Ferreira, W. C., F. Hilterman, L. A. Diogo, H. B. Santos, J. Schleicher, and A.
> Novais, 2016, Global optimization for AVO inversion: a genetic algorithm using
> a table-based ray-theory algorithm: Presented at the 78th EAGE Conference and
> Exhibition 2016, EAGE Publications, doi: 10.3997/2214-4609.201600847.
# Global optimization for AVO inversion: a genetic algorithm using a table-based ray-theory algorithm
**Authors**:
[Wanderson C. Ferreira](http://lattes.cnpq.br/0795723887788274),
[Fred Hilterman](http://www.uh.edu/nsm/earth-atmospheric/people/faculty/fred-hilterman/),
[Liliana A. Diogo](http://lattes.cnpq.br/6272957939885857),
[Henrique B. Santos](http://lattes.cnpq.br/4062685231290581),
[Joerg Schleicher](http://lattes.cnpq.br/0373061112091020) and
[Amélia Novais](http://lattes.cnpq.br/4767998352165705)
**keywords:** AVO; inversion problem; P-wave; S-wave; velocity; density;
## Summary
Amplitude Variation with Offset (AVO) inversion provides estimates of the
P-wave velocity, S-wave velocity and density of a stratified medium. Global
optimization is desirable for the inversion to account for the multi-parametric
behaviour of the AVO inversion which is strongly affected by the initial
estimates of the model rock properties. We carried out an analysis to verify
the dependency between P-wave, S-wave velocity and density in the recovered
parameters using empirical relations as constraints. In inversion schemes, the
forward modelling is often the most time consuming pro- cess. To reduce
computation time, we have implemented a genetic algorithm using a table-based
ray-theory algorithm to allow for a large amount of models in the global
search. Our results show that the genetic algorithm was capable of recovering
the physical parameters with good agreement for examples using the empirical
constraints. However, it sometimes converged to solutions which were far from
the correct answer, but were good models to explain the observed dataset. The
forward modelling algorithm has shown excellent performance to be used in
global optimization schemes, because it allows the use of a large number of
members in the population of the genetic algorithm.
### Topics
Session: AVO-AVA - Theory I