Interpretation of Potential Field Tensor Data Using the Tensor Local Wavenumber Method and Comparison with the Conventional Local Wavenumber Method

Ma, Guoqing; Du, Xiaobo; Li, Lili

doi:10.1002/cjg2.1733

Cited by 5 publications

(2 citation statements)

References 26 publications

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“…Oruç (2010aOruç ( , 2010b used the analytic signals of the magnetic tensor gradient and magnitude of vector components to compute the locations of the dipoles. Ma et al (2012) presented tensor local wavenumber method interpret the tensor gradient data. Oliveira and Barbosa (2013) presented radial density inversion method that uses the gravity gradient data to obtain the density distribution of the source.…”

Section: Introductionmentioning

confidence: 99%

Balanced gradient methods for the interpretation of gravity tensor gradient data

Lu¹,

2015

Journal of Applied Geophysics

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Section: Introductionmentioning

confidence: 99%

Balanced gradient methods for the interpretation of gravity tensor gradient data

Lu¹,

2015

Journal of Applied Geophysics

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“…

Gravity and gravity gradient data are critical for investigation in geoscience. In comparison, gravity data contain more low-frequency information about deep structures, while gravity gradient data contain more high-frequency information and are sensitive to density non-uniformity of shallow structures (Zhang et al, 2000;Beiki, 2010;Ma et al, 2012). Consequently, joint inversion using gravity and gravity gradient data could improve the reliability of the results and has been widely applied in recent years (e.g.,

…”

mentioning

confidence: 99%

Joint inversion of gravity and gravity gradient data using smoothed L0 norm regularization algorithm with sensitivity matrix compression

Niu,

Zhang,

Zhang

et al. 2023

Front. Earth Sci.

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Improving efficiency and accuracy are critical issues in geophysical inversion. In this study, a new algorithm is proposed for the joint inversion of gravity and gravity gradient data. Based on the regularization theory, the objective function is constructed using smoothed L0 norm (SL0), then the optimal solution is obtained by the non-linear conjugate gradient method. Numerical modeling shows that our algorithm is much more efficient than the conventional SL0 based on the sparse theory, especially when inverting large-scale data, and also has better anti-noise performance while preserving its advantage of high accuracy. Compressing the sensitivity matrices has further improved efficiency, and introducing the data weighting and the self-adaptive regularization parameter has improved the convergence rate of the inversion. Moreover, the impacts of the depth weighting, model weighting, and density constraint are also analyzed. Finally, our algorithm is applied to the gravity and gravity gradient measurements at the Vinton salt dome. The inverted distribution range, thickness, and geometry of the cap rock are in good agreement with previous studies based on geological data, drilling data, seismic data, etc., validating the feasibility of this algorithm in actual geological conditions.

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Alternative local wavenumber methods to estimate magnetic source parameters

2013

Exploration Geophysics

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Three alternative local wavenumber methods are proposed to estimate the depth and the nature (structural index) of the 2D magnetic source simultaneously using various combinations of different forms of the local wavenumbers to compute the source parameters without any prior information about the source. A clustering method is also provided to get more accurate results. The proposed local wavenumber methods are demonstrated on synthetic noise-free and noise-corrupted magnetic data, and they successfully estimate the location parameters and structural index of the causative sources. The actual application of the proposed methods is demonstrated on a magnetic anomaly from southern Illinois.

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Interpretation of Potential Field Tensor Data Using the Tensor Local Wavenumber Method and Comparison with the Conventional Local Wavenumber Method

Cited by 5 publications

References 26 publications

Balanced gradient methods for the interpretation of gravity tensor gradient data

Balanced gradient methods for the interpretation of gravity tensor gradient data

Joint inversion of gravity and gravity gradient data using smoothed L0 norm regularization algorithm with sensitivity matrix compression

Alternative local wavenumber methods to estimate magnetic source parameters

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