【摘要】 局部线性化的反演方法不仅在初始模型远离真值时收敛速度慢,而且往往易陷入局部极大值中,而遗传算法(GA)便能解决这一问题,它是一种全局搜索法。虽然它同模拟退火法一样利用转移概率进行搜索,但其收敛速度一般比模拟退火法快。本文引进了多个目标函数进行综合评价和灾变过程,用单道地震道对一维声波介质的速度和密度同时进行了反演,并反演了加噪地震道和含薄层介质模型,取得了满意的效果。更多还原

【Abstract】 Geophysical inversion problem is one of the typical problem which can be identified as a nonlinear optimization problem, and the most used objective function is nonlinearize and multiextreme. Methods based on local linearization not only converge slower when the initial model far from real model, but also always lost in local extreme values. The "Genetic Alogrithme" here we investigated can solve this problem, it is a global search algorithms, which did not lost in local extremes easily. It coverges faster than the "Monte Calo" method , although it uses the transition probability as the "Monte Calo" method does." Multi - objective - value comprehensive evaluation " and " Disaster " were investigated into the "GA" in this paper. With this advancement, we inversed the velocity and the density of 1 -D acoustic media using single seismic trace within the same time. And the trace with noise and the model consisted thin-layer were inversed successfully. It was proved that the "GA" was very effective to solve the inversion problem.更多还原