2016
DOI: 10.1016/j.jappgeo.2015.11.003
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The horizontal boundary and top depth estimates of buried source using gravity data and their applications

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Cited by 9 publications
(5 citation statements)
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“…The segments are characterized by wavenumber intervals which directly relate to the average depth to the top of the source. The steepest segment corresponding to low wavenumber values reflects deeper or regional sources (Chen, Mou, & Meng, 2016). The high-frequency segment, normally at the tail end of the slope, is related to noise from data processing and is normally disregarded during interpretation.…”
Section: Spectral Analysismentioning
confidence: 99%
“…The segments are characterized by wavenumber intervals which directly relate to the average depth to the top of the source. The steepest segment corresponding to low wavenumber values reflects deeper or regional sources (Chen, Mou, & Meng, 2016). The high-frequency segment, normally at the tail end of the slope, is related to noise from data processing and is normally disregarded during interpretation.…”
Section: Spectral Analysismentioning
confidence: 99%
“…First, the power spectrum of the gravity data was computed and plotted with respect to the wavenumber (Fig. 11) and then the depth attributed to regional component was identified (Chavez 1987;Chen et al 2016;Guo et al 2013). Afterwards, the upward continuation to the height of 8 km was performed and the regional and residual gravity anomalies were formed, Fig.…”
Section: Gravity Datamentioning
confidence: 99%
“…These structures can be seen by using magnetic and gravitational anomalies along with other mathematical ltering techniques. For instance, the de nition of density/susceptibility interfaces (sourcedepths) using lters like upward continuation (Kebede et al, 2020), tilt depth (Chen et al, 2016;Salem et al, 2007), power spectral analysis (Likkason et al, 2013), 2D Werner deconvolution (Ku a Sharp, 1995; Mammo, 2012), and 3D Euler deconvolution (Mammo, 2010, Mammo, 2012Keating and Pilkington, 2004), power spectral analysis (Likkason et al, 2013;Mickus et al, 2007Tiberi et al, 2005, 2D Werner Deconvolution (Ku an Sharp, 1995; Mammo, 2012), 2D forward modeling, 3D structural model. The source depth estimation techniques stated above are just a few of the many available techniques.…”
Section: Introductionmentioning
confidence: 99%