Abstract: 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．

Key words: seismic impedance inversion, particle swarm optimization, chaos algorithm, genetic algorithm