混合粒子群算法在地震波阻抗反演中的应用

为提高地震波阻抗反演的精度，提出了一种结合了混沌和遗传思想的混合粒子群算法。算法在搜索初期，加入了混沌思想，使算法具有了遍历性。在粒子更新过程中，又加入了选择、交叉、变异思想，增强了粒子之间的联系和粒子的多样性，使算法收敛速度更快，更容易跳出局部极值。针对模型对该算法进行了测试与对比，测试结果表明，该算法在反演精度上明显优于传统粒子群算法; 对算法的抗噪性进行了分析，在模型中加入15%噪声时，虽有一定误差，但符合度依然较好，表明本算法具有一定的抗噪声能力; 最后将算法用于实际地震资料，得到了良好的效果，表明本算法具有一定的实用价值。

Hybrid Particle Swarm Optimization and Its Application in Seismic Wave Impedance Inversion#br#

In order to improve the precision of seismic wave impedance inversion，a hybrid particle swarm optimization is proposed． This algorithm have the chaotic and genetic ideas． Chaos is introduced at the beginning of the search，making the algorithm have the ergodic property． Selection，crossover and mutation are introduced at the process of particle update and its convergent speed is faster and easy to jump out of local extremum． The algorithm is tested by model and is contrasted with ordinary particle swarm optimization． The result shows that the algorithm is better than the traditional particle swarm optimization． For the model with 15% noise，although has some errors，the coincidence degree is still good． The result shows that the algorithm has anti-noise ability． Finally，the algorithm is applied to the actual seismic data and it also has a good effect，the result shows that the algorithm has practicability．