A NUMERICAL STUDY ON NON-LINEAR AVO INVERSION USING CHAOTIC QUANTUM PARTICLE SWARM OPTIMIZATION

作者：Sun, Sam Zandong^*; Liu, Lifeng

来源：Journal of Seismic Exploration, 2014, 23(4): 379-392.

• non-linear inversion
• particle swarm optimization
• global search capability
• chaotic mapping
• reflection coefficient of density

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.

• 出版日期2014-9
• 单位中国石油大学（北京）