Two-Dimensional Determinant Inversion Of Marine Magnetotelluric Data And A Field Example From The Gulf Of California, Mexico

GEOPHYSICS(2021)

引用 4|浏览15
暂无评分
摘要
Two-dimensional marine magnetotelluric (MT) observations are useful for offshore geologic studies, such as natural resource exploration, fault mapping, fluid estimation at subduction zones, and the delineation of the lithosphere-asthenosphere boundary beneath the seafloor. Earth structures are often assumed to be two dimensional, which allows MT data to be decomposed into a transverse electric (TE) mode and a transverse magnetic (TM) mode. The 2D assumption can effectively reduce acquisition and computational costs. However, offline 3D effects and other problems such as lack/ failure of the compass on instruments are often encountered, making it difficult to decompose data into the TE and TM modes. In these cases, 2D inversion may be misleading or may not provide an acceptable misfit to the marine MT observations. Thus, we have developed a 2D determinant inversion to the marine MT method to mitigate these difficulties, implemented in the MARE2DEM code, and we tested its utility using synthetic examples and a field example. In the synthetic examples, the determinant inversion demonstrates an ability to overcome 3D effects caused by 3D anomalies and bathymetry. With confidence from the synthetic tests, we interpreted real data acquired in the Gulf of California, Mexico, where not only is the bathymetry 3D in nature, but the external compasses failed to record the orientation. The field data can not only be fit to a reasonable misfit with a determinant inversion, but the resolved conductive zones also have a good correlation with known faults. A comparison between the resistivity model from the field data and a seismic reflection section shows that a previously interpreted fault, the Wagner Fault, should be shifted 5 km toward the southwest and made slightly steeper. Thus, the implementation of the determinant inversion may provide a new approach for using problematic 2D data.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要