Poststack impedance inversion using improved particle swarm optimization
- Xiaofei Cui (Xi'an Jiaotong University)
- Document ID
- Society of Exploration Geophysicists
- 2016 SEG International Exposition and Annual Meeting, 16-21 October, Dallas, Texas
- Publication Date
- Document Type
- Conference Paper
- 2016. Society of Exploration Geophysicists
- Nonlinear, Impedance, High-resolution, Optimization, Inversion
- 0 in the last 30 days
- 25 since 2007
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Inversion for seismic impedance is an ill-posed and nonlinear problem. Hence inversion results are non-unique and unstable. Scholars have made great efforts in this research and recent years it has emerged more and more new non-linear inversion method with the application of the nonlinear inversion problems. Standard particle swarm optimization (PSO) is not appropriate when we use it for the post-stack impedance directly. So we come up with an improved particle swarm optimization to alleviate these problems for the post-stack impedance inversion. This improved particle swarm optimization is based on the swarm intelligence and probabilistic theory for global optimization. This paper applied this method in the observation data of post-stack impedance inversion. The results show that this improved particle swarm optimization algorithm is a global optimization algorithm with a better performance than standard PSO for post-stack impedance inversion. It is feasible and effective for impedance inversion problem.
Presentation Date: Monday, October 17, 2016
Start Time: 4:10:00 PM
Location: Lobby D/C
Presentation Type: POSTER
|File Size||1 MB||Number of Pages||5|
Boeringer,D. W., andD. H.Werner,2004,Particle swarm optimization versus genetic algorithms for phased array synthesis:IEEE Transactions on Antennas and Propagation,52,771–779,10.1109/TAP.2004.825102.
Hong,T., andM. K.Sen,2009,A new MCMC algorithm for seismic waveform inversion and corresponding uncertainty analysis:Geophysical Journal International,177,14–32,10.1111/j.1365-246X.2008.04052.x.
Huang,K.-Y.,K.-J.Chen,L.-C.Shen, andM.-C.Huang,2012,Multilayer perceptron learning with particle swarm optimization for well log data inversion: The 2012 International Joint Conference on Neural Networks (IJCNN), IEEE,1–6,10.1109/IJCNN.2012.6252707.
Kennedy,J., andR.Eberhart,1995,Particle swarm optimization:Proceedings of the IEEE International Conference on Neural Networks,4,1942–1948,10.1109/ICNN.1995.488968.
Poli,R.,J.Kennedy, andT.Blackwell,2007,Particle swarm optimization: An overview:Swarm Intelligence,1,33–57,10.1007/s11721-007-0002–0.
Sambridge,M.,1999,Geophysical inversion with a neighbourhood algorithm — II. Appraising the ensemble:Geophysical Journal International,138,727–746,10.1046/j.1365-246x.1999.00900.x.
Sen,M. K., andP. L.Stoffa,1991,Nonlinear one-dimensional seismic waveform inversion using simulated annealing:Geophysics,56,1624–1638,10.1190/1.1442973.
Wang,C., andZ.Li,2010,Inversion of wave impedance using improved simulated annealing genetic algorithm:2010 Third International Conference on Information and Computing, IEEE,121–124,10.1109/ICIC.2010.124.