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Joint inversion of two-dimensional magnetotelluric and surface wave dispersion data with cross-gradient constraints

机译:具有交叉梯度约束的二维磁音和表面波分散数据的联合反演

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Multiphysics imaging for data inversion is of growing importance in many branches of science and engineering. Cross-gradient constraint has been considered as a feasible way to reduce the non-uniqueness problem inherent in inversion process by finding geometrically consistent images from multigeophysical data. Based on OCCAM inversion algorithm, a direct inversion method of 2-D profile velocity structure with surface wave dispersion data is proposed. Then we jointly invert the profiles of magnetotelluric and surface wave dispersion data with cross-gradient constraints. Three synthetic models, including block homogeneous or heterogeneous models with consistent or inconsistent discontinuities in velocity and resistivity, are presented to gauge the performance of the joint inversion scheme. We find that owning to the complementary advantages of the two geophysical data sets, the models recovered with structure coupling constraints exhibit higher resolution in the classification of complex geologic units and settle some imaging problems caused by the separate inversion methods. Finally, a realistic velocity model from the NE Tibetan Plateau and its corresponding resistivity model calculated by empirical law are used to test the effectiveness of the joint inversion scheme in the real geological environment.
机译:用于数据反演的多职业成像在许多科学和工程分支中越来越重要。交叉梯度约束被认为是通过从多岛影片数据中查找几何一致性图像来减少反转过程中固有的非唯一性问题的可行方法。基于COMPAN反转算法,提出了一种具有表面波色散数据的2-D剖面速度结构的直接反演方法。然后,我们共同颠倒了用交叉梯度约束的磁音和表面波色散数据的谱。提出了三种合成模型,包括块均匀或异构模型,具有一致或不一致的速度和电阻率的不连续性,以衡量联合反演方案的性能。我们发现拥有两个地球物理数据集的互补优势,用结构耦合约束恢复的模型在复杂地质单位的分类中表现出更高的分辨率,并解决了由单独的反转方法引起的一些成像问题。最后,通过经验法计算的NEIBETAN高原及其相应的电阻率模型的现实速度模型用于测试实际地质环境中联合反演方案的有效性。

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