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Abstract

Summary

Amplitude Variation with Offset (AVO) inversion provides estimates of the P-wave velocity, S-wave velocity and density of the stratified medium. A global optimization technique was selected for the inversion due to the multi-parametric behavior of the AVO inversions which are strongly affected by the initial estimate of the model rock properties. An analysis to verify the dependency between P-wave, S-wave velocity and density in the recovered parameters was also performed using empirical relations as constraints. In inversion schemes, the forward modelling is often the most time consuming process. To reduce computation time, we have implemented a genetic algorithm and a table-based ray-theory algorithm to allow us to implement a large amount of models in the global search. Our results show that the genetic algorithm was capable to recover the physical parameters with good agreement for the examples using the empirical constraints, but was also capable of converging to solutions which were far from the correct answer, but were good answers to explain the observed dataset. The forward modelling algorithm has shown excellent performance to be used in global optimization schemes allowing the use of a large number of members in the population of the genetic algorithm.

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/content/papers/10.3997/2214-4609.201600847
2016-05-30
2024-04-25

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References

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Global Optimization for AVO Inversion - A Genetic Algorithm Using a Table-based Ray-theory Algorithm
Conference Proceedings 2016, 1 (2016); https://doi.org/10.3997/2214-4609.201600847
/content/papers/10.3997/2214-4609.201600847
/content/papers/10.3997/2214-4609.201600847
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