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Abstract

Summary

Inversion of 1-D post-stack seismic data results in acoustic impedance that can be used to make more precise structural and stratigraphic interpretations than can be made from seismic data alone. In this paper we show the application of Fitness-Distance-Ratio (FDR) based Particle Swarm Optimization (PSO) for the stochastic inversion of 1-D post-stack seismic data. The performance of FDR-PSO has also been compared with standard PSO for both noise free and noise corrupted data sets. For both the inversion the search space is same. The comparison illustrates that the FDR-PSO has a much better convergence than PSO. The obtained parameters for FDR-PSO is much closer to the true model. Further the sensitivity analysis shows that the FDR –PSO is robust and the results does not change significantly with the change in search space.

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/content/papers/10.3997/2214-4609.201412466
2015-06-01
2024-03-28
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References

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