3D joint inversion of gravity-gradient and borehole gravity data
Meixia Geng 1 Qingjie Yang 2 4 Danian Huang 31 Institute of Geophysics and Geomatics, China University of Geosciences, Wuhan 430074, China.
2 Chinese Academy of Sciences, Institute of Geodesy and Geophysics, Center for Computational and Exploration Geophysics, Wuhan 430077, China.
3 College of GeoExploration Science and Technology, Jilin University, Changchun, Jilin 130026, China.
4 Corresponding author. Email: yqj@whigg.ac.cn
Exploration Geophysics 48(2) 151-165 https://doi.org/10.1071/EG15023
Submitted: 11 March 2015 Accepted: 1 November 2015 Published: 22 December 2015
Abstract
Borehole gravity is increasingly used in mineral exploration due to the advent of slim-hole gravimeters. Given the full-tensor gradiometry data available nowadays, joint inversion of surface and borehole data is a logical next step. Here, we base our inversions on cokriging, which is a geostatistical method of estimation where the error variance is minimised by applying cross-correlation between several variables. In this study, the density estimates are derived using gravity-gradient data, borehole gravity and known densities along the borehole as a secondary variable and the density as the primary variable. Cokriging is non-iterative and therefore is computationally efficient. In addition, cokriging inversion provides estimates of the error variance for each model, which allows direct assessment of the inverse model. Examples are shown involving data from a single borehole, from multiple boreholes, and combinations of borehole gravity and gravity-gradient data. The results clearly show that the depth resolution of gravity-gradient inversion can be improved significantly by including borehole data in addition to gravity-gradient data. However, the resolution of borehole data falls off rapidly as the distance between the borehole and the feature of interest increases. In the case where the borehole is far away from the target of interest, the inverted result can be improved by incorporating gravity-gradient data, especially all five independent components for inversion.
Key words: 3D, borehole gravity data, cokriging, gravity-gradient data, joint inversion.
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