Seismic structure inversion of refraction and reflection waves by progressive model development method

我们发展了一种用于二维折射实验的反演方法，即渐进模型发展法(PMDM Ver.1)，它允许通过从一维(1-D)模型到伪二维模型，然后再到二维模型(Sato和Kennett，2000)的顺序来逐步改善速度结构。这项研究修改了PMDM版本1，使其能够使用后期阶段，如反射。首先，我们将挑选的数据分组，这些数据的相位似乎是相同的。然后，我们利用只用初至数据计算的速度结构模型(PMDM Ver.1的结果)，用最小二乘法估计每组最可能的相位。这将由计算机自动识别所拾取数据的阶段。只有数据采集和分组需要目视检查。由于是按组进行相位识别，识别的可靠性高于对每个拾取数据进行的相位识别，如果仅由初至数据计算的速度结构模型与真实结构相差不小，则上述方法存在一定的误识相的可能性。为了避免这种情况，我们估计了具有较高误识率的组的最佳2个阶段。然后，我们计算每个阶段的二维反演。这一修改增加了计算量。当有N个基团具有2个相时，相的组合是2到第N个。我们使用上述方法(PMDM版本2)进行了数值模拟。结果表明，各层低层边界的分辨率和各层低层的速度都有很大提高。即使我们使用一个不好的初始模型，使用正确的相位进行反演的结果也成为最好的估计模型。我们还对一个实际数据进行了分析。

We developed an inversion method for 2-D refraction experiments, Progressive model development method (PMDM ver.1), that allows progressive improvement of velocity structure through a sequence from one-dimensional (1-D) models to pseudo 2-D models, and then 2-D models (Sato and Kennett, 2000). This study modified PMDM ver.1 to be able to use later phases such as reflection. First, we make groups of picked data whose phase seems to be same. Then we conduct the least square method to estimate the most probable phase for each group using the velocity structure model calculated only with the first arrival data (the result of PMDM ver.1). This identifies phases of picked data by computer automatically. Only data picking and grouping need visual inspection. Because of phase identification for groups, the reliability of the identification is higher than phase identification for each picked datum.If the difference between the velocity structure model calculated only with the first arrival data and the true structure is not small, the above method has some probability to make mis-identification of phases. To avoid this, we estimate the best 2 phases for groups that have high probability of mis-identification. Then we calculate 2-D inversion for each phase. This modification increases the amount of computation. When there are N groups that take 2 phases, combination of phases is 2 to the N-th. However, this modification makes the method more robust.We conducted a numerical simulation using the above method (PMDM ver.2). The results show that the resolution of lower layer boundaries and velocities of lower parts of each layer are much improved. Even if we use a bad initial model, the result of the inversion using correct phases becomes the best estimated model. We also conducted the method for a real data.