A numerical study on non-linear AVO inversion using chaotic quantum particle swarm optimization
Sun, S.Z. and Liu, L., 2014. A Numerical study on non-linear AVO inversion using chaotic quantum particle swarm optimization. Journal of Seismic Exploration, 23: 379-392. Particle swarm optimization (PSO) is a common method for a non-linear system used in AVO inversion, which is much more advantageous than traditional linear inversion, due to independence of initial model establishment and wavelet estimation, etc. However, the method is prone to fall into local optimum. And it is so easy to be affected by noise interference that fails to tackle the issues of reservoir and fluids in most cases. Based on the method above, a new non-linear AVO inversion method is proposed in this paper, with the employment of chaotic quantum particle swarm optimization (CQPSO) to solve non-linear problems. By comparison with conventional PSO, CQPSO shows more efficient capability, including shorter computation time, higher efficiency for convergence, and global search capability, etc. Due to these characteristics, CQPSO inversion could be used to extract elastic properties directly from the synthetic seismogram, and provide more precise results, especially for density gradients. After the testing with model data and seismic data, the results of CQPSO inversion are all coincident with well data on reservoir properties and fluid content. These coincidences mean confirmed feasibility and effectiveness of the new inversion method.
- Bing, P.P, Cao, S.Y. and Lu, J.T., 2012. Non-linear AVO inversion based on support vector
- machine. Chin. J. Geophys., 55: 1025-1032 (in Chinese).
- Chen, J., 2007. Study of Three-term AVO Inversion Method. Ph.D. Thesis, China Univ. of
- Petroleum, Dongying (in Chinese).
- Fang, W., Sun, J., Xie, Z. and Xu, W., 2010. Convergence analysis of quantum-behaved particle
- swarm optimization algorithm and study on its control parameter. Acta Phys. Sin., 59:
- 3686-3693 (in Chinese).
- Gidlow, P.M., Smith, G.C. and Vail, P.J., 1992. Hydrocarbon detection using fluid factor traces.
- Joint SEG/EAEG Summer Res. Worksh., Technical Program and Abstr.: 78-89.
- Han., J., Sun, Z., Zhang, X., Zhang, Y., Chen, J., Pan, Y., Liu, X. and Zhao, H., 2013.
- Integrated identification for complex reservoir based on pure P-wave data and post-stack
- data. Expanded Abstr., 83rd Ann. Internat. SEG Mtg., Houston.
- Kennedy, J. and Eberhart, R., 1995. Particle swarm optimization. Proc. IEEE Internat. Conf. on
- Neural Networks, Perth, Australia: 1942-1948.
- Kuzma, H.A. and Rector, J.W., 2004. Non-linear AVO inversion using support vector machines.
- Expanded Abstr., 74th Ann. Internat. SEG Mtg., Denver.
- Lu, H., 2006. A new optimization algorithm based on chaos. Zhejiang Univ. Science A, 7: 539-542.
- Peng, Z., Li, Y., Wei, W., He, Z. and Li, D., 2008. Nonlinear AVO inversion using particle filter.
- Chin. J. Geophys., 51: 1218-1225 (in Chinese).
- Pratt, R.G., Shin, C.S., Hicks, G.J., 1998. Gauss-Newton and full Newton method in
- frequency-space seismic waveform inversion. Geophys. J. Int., 133: 341-362.
- Shan, L., Qiang, H., Li, J. and Wang, Z., 2005. Chaotic optimization algorithm based on Tent
- map. Control and Decision, 20: 179-182 (in Chinese).
- Sun. J., Xu. W.B. and Feng, B., 2004. A global search strategy of quantum-behaved particle swarm
- optimization. Proc. IEEE Conf. on Cybernetics and Intelligent Systems, Singapore: 111-116.
- Tarantola, A., 1984. Inversion of seismic reflection data in the acoustic approximation. Geophysics,
- 49: 1259-1266.
- Tavazoei, M.S. and Haeri, M., 2007. An optimization algorithm based on chaotic behavior and
- fractal nature. J. Computat. Appl. Mathemat., 206: 1070-1081.
- Wang, S., 2005. Elastic properties of gas-bearing strata and seismic response. Oil Gas Geol., 26:
- 730-735 (in Chinese).
- Wang, J., 2007. Lecture on non-linear inverse methods in geophysics. (I): Introduction to
- geophysical inverse problems. Chin. J. Engin. Geophys., 4: 1-3 (in Chinese).
- Yan, Z., Gu, H. and Zhao, X., 2009. Non-linear AVO inversion based on ant colony algorithm.
- OGP, 44: 700-702 (in Chinese).
- Yang, P. and Yin, X., 2008. Non-linear quadratic programming Bayesian prestack inversion. Chin.
- J. Geophys., 51: 1876-1882 (in Chinese).
- NON-LINEAR AVO INVERSION 391
