Large-scale 3D inversion of potential field data

被引:70
作者
Cuma, Martin [1 ,2 ]
Wilson, Glenn A. [2 ]
Zhdanov, Michael S. [2 ,3 ]
机构
[1] Univ Utah, Ctr High Performance Comp, Salt Lake City, UT 84112 USA
[2] TechnoImaging, Salt Lake City, UT 84107 USA
[3] Univ Utah, Dept Geol & Geophys, Salt Lake City, UT 84112 USA
关键词
Footprint; Inversion; Parallelization; GRAVITY GRADIENT TENSOR; 3-D INVERSION;
D O I
10.1111/j.1365-2478.2011.01052.x
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Inversion of gravity and/or magnetic data attempts to recover the density and/or magnetic susceptibility distribution in a 3D earth model for subsequent geological interpretation. This is a challenging problem for a number of reasons. First, airborne gravity and magnetic surveys are characterized by very large data volumes. Second, the 3D modelling of data from large-scale surveys is a computationally challenging problem. Third, gravity and magnetic data are finite and noisy and their inversion is ill posed so regularization must be introduced for the recovery of the most geologically plausible solutions from an infinite number of mathematically equivalent solutions. These difficulties and how they can be addressed in terms of large-scale 3D potential field inversion are discussed in this paper. Since potential fields are linear, they lend themselves to full parallelization with near-linear scaling on modern parallel computers. Moreover, we exploit the fact that an instruments sensitivity (or footprint) is considerably smaller than the survey area. As multiple footprints superimpose themselves over the same 3D earth model, the sensitivity matrix for the entire earth model is constructed. We use the re-weighted regularized conjugate gradient method for minimizing the objective functional and incorporate a wide variety of regularization options. We demonstrate our approach with the 3D inversion of 1743 line km of FALCON gravity gradiometry and magnetic data acquired over the Timmins district in Ontario, Canada. Our results are shown to be in good agreement with independent interpretations of the same data.
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页码:1186 / 1199
页数:14
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