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A fast imaging method for airborne gravity gradient data based on tensor invariants

  • Gravity exploration methods
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Abstract

Airborne gravity gradient data contain additional short-wavelength information about the buried geological bodies. This study develops a fast interpretation method based on the gravity gradient data for the sources’ spatial location and physical property parameters. This study analyzes the advantages of the source parameter inversion method based on tensor invariants. It proposes a normalized fast-imaging method based on tensor invariants to quickly estimate the spatial location parameters of sources through the local maximum value position of the imaging results. First, the tensor invariant characteristics and the imaging method’s effect in a simple model are analyzed using a theoretical model. Second, to analyze the imaging method’s application eff ect in complex model conditions, the method’s applicability is quantitatively analyzed using the data added with noise, superimposed anomalies of adjacent sources, and anomalies of deep and shallow geological bodies. The theoretical model’s simulation results show that the model’s imaging results in this study have satisfactory performance on the spatial position estimation of the sources. Finally, the method is applied to the gravity anomaly data corresponding to the Humble salt dome. The imaging results can effectively estimate the distribution of the salt dome’s horizontal and depths, verifying the practicability of the method.

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Acknowledgments

This work was supported by National Key R&D Program of China (No. 2020YFE0201300), Natural Science Foundation of Jilin Province (No. 20210508033RQ), and Fundamental Research Funds for the Central Universities and Geological Survey Project (No. DD20190129). The authors also express their gratitude to the reviewers for their constructive comments. We also would like to thank the reviewers and editors for their valuable comments on this article.

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Authors and Affiliations

  1. College of Geo-exploration Science and Technology, Jilin University, Changchun, 130026, China

    Shuai Zhou, Yue Wei, Yan-gang Wu, Jian Jiao, Peng-yu Lu & Dan-dan Jiang

Authors
  1. Shuai Zhou
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  2. Yue Wei
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  3. Yan-gang Wu
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  4. Jian Jiao
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  5. Peng-yu Lu
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  6. Dan-dan Jiang
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Corresponding author

Correspondence to Jian Jiao.

Additional information

Zhou Shuai, associate professor, received a PhD degree from Jilin University, China, in 2017. He engaged in the processing and interpretation of gravity and magnetic data.

Jiao Jian, associate professor, received a PhD degree from Jilin University, China, in 2012. He engaged in the theory and application of airborne geophysics.

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Zhou, S., Wei, Y., Wu, Yg. et al. A fast imaging method for airborne gravity gradient data based on tensor invariants. Appl. Geophys. 19, 284–293 (2022). https://doi.org/10.1007/s11770-022-0971-1

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  • DOI: https://doi.org/10.1007/s11770-022-0971-1

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