Refinement of three-dimensional multilayer models of basins and crustal environments by inversion of gravity and magnetic data
Refinement of three-dimensional multilayer models of basins and crustal environments by inversion of gravity and magnetic data
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DOI：
10.1016/j.tecto.2004.10.010
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发表时间：
2005-03
期刊：
影响因子：
2.9
通讯作者：
L. Gallardo;M. A. Pérez-Flores;E. Gómez-Treviño
中科院分区：
文献类型：
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作者：
L. Gallardo;M. A. Pérez-Flores;E. Gómez-Treviño
重磁数据对深部结构的敏感性，以及区域数据集和高分辨率调查的广泛可获得性，使它们适合于确定详细的地下三维模型。然而，仅考虑重磁信息并不能很好地解决三维环境中的异质问题。为了解决这个问题，我们提出了一种在重磁数据和有意义的几何和物理约束的条件下对三维多层模型进行自动细化的技术。我们由一组矩形棱柱构建我们的模型，并旨在估计它们的底部深度，这定义了地质层。我们在数学上将精化的概念总结为一个目标函数，其中包括与数据的不匹配、与先验地质-地球物理模型的相似性以及地层起伏的平稳性。重要的是，我们的目标函数还包括防止地层叠加的不等约束，并将地表和井眼地质与多层深层模型相结合。目标函数用二次规划在稳定的迭代格式中求解。所得到的算法在合成数据上进行了测试，并应用于墨西哥下加利福尼亚州南部的地壳和沉积盆地环境。地质和几何约束对反演过程的同化产生了与地表地质相关的模型，并揭示了地下的三维特征。
The sensitivity of gravity and magnetic data to deep structures and the broad availability of regional data sets and surveys of high resolution make them suitable for determining detailed three-dimensional (3D) models of the subsurface. However, the sole consideration of gravity and magnetic information cannot properly resolve heterogeneous 3D environments. Advocated to solve this problem, we present an automated refinement technique for three-dimensional multilayer models as conditioned by gravity and magnetic data and by meaningful geometrical and physical constraints. We construct our model by an aggregate of rectangular prisms and aim to estimate their bottom depths, which define the geological layers. We summarize mathematically our concept of refinement in an objective function that includes the misfit to the data, the similitude to an a priori geological–geophysical model, and the smoothness of the relief of the layers. Importantly, our objective function also includes inequality constraints that prevent the superposition of layers and integrate the surface and borehole geology with the multilayer deep model. The objective function is solved using quadratic programming in a stable iterative scheme. The resulting algorithm is tested on synthetic data and applied to crustal and sedimentary basin environments from southern Baja California, Mexico. The assimilation of the geological and geometrical constraints to the inversion process produces models that correlate with the surface geology and reveal the three-dimensional features of the subsurface.