基于遗传算法的多模式表面波联合反演研究

Joint inversion of multimode surface waves by genetic algorithms

传统的表面波反演主要是利用基阶瑞雷波,当地质结构简单且基阶波具有较高的信噪比时,该方法一般能获得较好的地质解释。然而,当地层中出现速度倒转等复杂地质结构时,高模式表面波将变得极为发育,高阶波在高频段将包含更多的能量,当这种低速层出现时,仅利用基阶波反演将很容易得出错误的地质解释。为此,本文成功地将遗传算法引入到多模式表面波联合反演中来,并通过某高速公路路基典型实例演示了充分利用多模式表面波联合反演不仅可使反演过程稳定,而且还能提高横波速度的反演精度和计算结果的可靠性。

A simple geologic structure can be deduced when only inverting the fundamental surface wave data. However, considering that higher modes possess significant amounts of energy at higher frequencies and the contribution of higher modes tends to become more significant especially in the presence of a low velocity layer, only by combining the fundamental and higher-mode surface waves, can a final desired model be accurately obtained. A joint inversion of multimode surface waves is successfully implemented by genetic algorithms in this paper. Inversion results of field data demonstrate that the inversion process can be stabilized; the ambiguity can be reduced, as well as the accuracy and resolution of the S-wave velocity model can be improved when simultaneously inverting the fundamental and higher mode data.