Abstract
We use the extrapolated Tikhonov regularization to deal with the ill-posed problem of 3D density inversion of gravity gradient data. The use of regularization parameters in the proposed method reduces the deviations between calculated and observed data. We also use the depth weighting function based on the eigenvector of gravity gradient tensor to eliminate undesired effects owing to the fast attenuation of the position function. Model data suggest that the extrapolated Tikhonov regularization in conjunction with the depth weighting function can effectively recover the 3D distribution of density anomalies. We conduct density inversion of gravity gradient data from the Australia Kauring test site and compare the inversion results with the published research results. The proposed inversion method can be used to obtain the 3D density distribution of underground anomalies.
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This work is supported by National major special equipment development (No. 2011YQ120045) and The National Natural Science Fund (No. 41074050 and 41304023).
Liu Jin-Zhao received his Ph.D. (2014) in Geodesy and Surveying Engineering from the Institute of Geodesy and Geophysics, China Academy of Science. His main research interests are in airborne gravity gradiometry.
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Liu, JZ., Liu, LT., Liang, XH. et al. 3D density inversion of gravity gradient data using the extrapolated Tikhonov regularization. Appl. Geophys. 12, 137–146 (2015). https://doi.org/10.1007/s11770-015-0491-2
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DOI: https://doi.org/10.1007/s11770-015-0491-2