基于粒子群优化算法的波阻抗反演研究

波阻抗反演属于最优化问题，其目标函数可能包含多个在一定范围内连续的变量。传统的优化手段对某些函数存在难以优化，容易陷入局部解，收敛速度缓慢等问题。粒子群算法只考虑目标函数，对初始模型的依赖程度不高，可以随机地在全局域内进行搜索。通过分析粒子群算法的原理，提出了地震波阻抗反演粒子群算法的实现方法。详细地分析了粒子群算法的抗噪能力及算法中各参数对反演结果的影响，得出参数的最优组合。利用模型数据对该方法进行检测，在无噪情况下，反演结果与模型一致；在加入3%，10%和25%的噪声后，反演前后的相关系数分别为98.31%，93.27%和82.09%，证明了该方法的有效性。

Wave impedance inversion based on particle swarm optimization

Wave impedance inversion is indispensable in predicting reservoir properties.Wave impedance inversion is an optimization problem,and its objective function may include several continuous variables.In traditional optimization methods,the objective function is sometimes hard to solve.It is easy to fall into local extrema,and slow to converge.To cope with the problems,particle swarm optimization is developed.The method is weakly dependent on the initial model,and it searches randomly for the optimal solution in the global space.Based on an analysis of the principles of particle swarm algorithms,we put forward a seismic inversion method based on particle swarm optimization.We investigated in detail the effect of different parameters on inversion result,and an optimal combination of parameters was determined.We also discussed the noise resistance ability of the method,and tested it with model data.The inverted results coincide with noise-free theoretical data,and the correlation coefficient is 98.31%,93.27%,and 82.09% respectively when 3%,10%,or 25% noise is added to the original data.