Abstract
In gravity gradient inversion, to choose an appropriate component combination is very important, that needs to understand the function of each component of gravity gradient in the inversion. In this paper, based on the previous research on the characteristics of gravity gradient components, we propose a reweighted inversion method to evaluate the influence of single gravity gradient component on the inversion resolution The proposed method only adopts the misfit function of the regularized equation and introduce a depth weighting function to overcome skin effect produced in gravity gradient inversion. A comparison between different inversion results was undertaken to verify the influence of the depth weighting function on the inversion result resolution. To avoid the premise of introducing prior information, we select the depth weighting function based on the sensitivity matrix. The inversion results using the single-prism model and the complex model show that the influence of different components on the resolution of inversion results is different in different directions, however, the inversion results based on two kind of models with adding different levels of random noise are basically consistent with the results of inversion without noises. Finally, the method was applied to real data from the Vinton salt dome, Louisiana, USA.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Barnes, G., and Lumley, J., 2011, Processing gravity gradient data: Geophysics, 76(2), 133–147.
Coker, M. O., Bhattacharya, J. P., and Marfurt, K. J., 2007, Fracture patterns within mudstones on the flanks of a salt dome: Syneresis or slumping?: Gulf Coast Association of Geological Societies, 57, 125–137.
Commer, M., 2011, Three-dimensional gravity modelling and focusing inversion using rectangular meshes: Geophysical Prospecting, 59(5), 966–979.
Ennen, C., 2012, Mapping gas-charged fault blocks around the Vinton Salt Dome, Louisiana using gravity gradiometry data: PhD Thesis, University of Houston, Houston.
Ennen, C., and Hall, S., 2011, Structural mapping of the Vinton salt dome, Louisiana, using gravity gradiometry data: 81th Annual International Meeting, SEG, Expanded Abstracts, 830–835.
Geng, M., Huang, D., Yang, Q., et al., 2014, 3D inversion of airborne gravity-gradiometry data using cokriging: Geophysics, 79(4), G37–G47.
Geng, M., Huang, D., Yu, P., et al., 2016, Three-dimensional constrained inversion of full tensor gradiometer data based on cokriging method: Chinese Journal of Geophysics, 59(5), 1849–1860.
Jordan, S. K., 1978, Moving-Base Gravity Gradiometer Surveys and Interpretation: Geophysics, 43(1), 94–101.
Li, Y., 2001, 3-D inversion of gravity gradiometer data: 71th Annual International Meeting, SEG, Expanded Abstracts, 1470–1473.
Li, Y., and Oldenburg, D. W., 1996, 3-D Inversion of Magnetic Data: Geophysics, 61(2), 394–408.
Li, Y., and Oldenburg, D. W., 1998, 3-D inversion of gravity data: Geophysics, 63(1), 109–119.
Martinez, C., Li, Y., Krahenbuhl, R., et al., 2013, 3D inversion of airborne gravity gradiometry data in mineral exploration: A case study in the Quadrilátero Ferrífero, Brazil: Geophysics, 78(1), B1–B11.
Mehanee, S., Golubev, N., and Zhdanov, M. S., 1998, Weighted regularized inversion of the magnetotelluric data: 68th Annual International Meeting, SEG, Expanded Abstracts
Oliveira, V. C., and Barbosa, V. C. F., 2013, 3-D radial gravity gradient inversion: Geophysical Journal International, 195(2), 883–902.
Pilkington, M., 2012, Analysis of gravity gradiometer inverse problems using optimal design measures: Geophysics, 77(2): 25–36.
Pilkington, M., 2014, Evaluating gravity gradient tensor components: Geophysics, 79(1), G1–G14.
Portniaguine, O. and Zhdanov, M. S. 1999, Focusing geophysical inversion images: Geophysics, 64(3), 874–887.
Portniaguine, O. Zhdanov, M S., 2002, 3-D magnetic inversion with data compression and image focusing: Geophysics, 67(5), 1532–1541.
Qin, P., and Huang, D., 2016, Integrated gravity and gravity gradient data focusing inversion: Chinese Journal of Geophysics, 59(6), 2203–2224.
Qin, P., Xiang, M., Liang, X., et al., 2019, A new method to integrate different gravity gradient components in reweighted regularized inversion with minimum support constraint: Geophysical Journal International, 217, 1387–1412.
Silva, J. B. C., Medeiros, W. E., and Barbosa, V. C. F., 2001, Potential-field inversion: Choosing the appropriate technique to solve a geologic problem: Geophysics, 66(2), 511–520.
Thompson, S. A., and Eichelberger, O. H., 1928, Vinton salt dome, Calcasieu Parish, Louisiana: Amer. Assoc. of Petrol. Geol. Bull., 385–394.
Zhdanov, M. S., and Ellis, R., Mukherjee, S., 2004, Three-dimensional regularized focusing inversion of gradient tensor component data: Geophysics, 69(4), 1–4.
Acknowledgement
The authors thank Bell Geospace Inc. for permission to use the real data from Vinton salt dome We would
Author information
Authors and Affiliations
Corresponding author
Additional information
This work was supported by the National Key R & D Program of China (Nos. 2016YFC0303002 and 2017YFC0601701) and China Geological Survey Program (No. DD20191007).
Cao Ju-Liang, Researcher, obtained his Bachelor’s degree in Measuring and Testing Technologies and Instruments from the National University of Defense Technology in 1997 and Doctor’s degree in Instrument Science and Technology from the National University of Defense Technology in 2004. From 2004 to 2007, he was a post-doctor at Control Theory and Control Science of the National University of Defense Technology. He is currently working at the College of Intelligence Science and Engineering of the National University of Defense Technology and is focusing on navigation technology, gravity measurement technology, photoelectrical signal processing technology, etc.
Qin Peng-Bo, Doctor, an engineer of the Guangzhou Marine Geological Survey, obtained his Bachelor’s degree in Geophysics from the Jilin University in 2011 and Doctor’s degree in Geophysics from the Jilin University in 2016. From August 2016 to August 2018, he worked at the Control Science and Engineer postdoctoral research station of the National University of Defense Technology. He is currently working at the Guangzhou Marine Geological Survey and is focusing on processing, integration, and inversion of the gravity data.
Hou Zhen-Long, Post-doctor, obtained his Bachelor’s degree in Geophysics from the Jilin University in 2011 and Ph.D. in Computer System and Architecture from the Jilin University in 2016. He is a post-doctor in the Northeastern University since 2016. His main research interests include gravity. magnetic exploration data processing and interpretation, and the parallel computing methods.
Rights and permissions
About this article
Cite this article
Cao, JL., Qin, PB. & Hou, ZL. Evaluating gravity gradient components based on a reweighted inversion method. Appl. Geophys. 16, 491–506 (2019). https://doi.org/10.1007/s11770-019-0785-y
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11770-019-0785-y