2017
DOI: 10.1016/j.jsames.2017.02.005
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Basement structures over Rio Grande Rise from gravity inversion

Abstract: The basement depth in the Rio Grande Rise (RGR), South Atlantic, is estimated from combining gravity data obtained from satellite altimetry, marine surveys, bathymetry, sediment thickness and crustal thickness information. We formulate a crustal model of the region by inverse gravity modeling. The effect of the sediment layer is evaluated using the global sediment thickness model of National Oceanic and Atmospheric Administration (NOAA) and fitting the sediment compaction model to observed density values from … Show more

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Cited by 21 publications
(17 citation statements)
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“…The modeling of the Te is made by a best fit of the flexure Moho with an independent Moho. For this paper, we use the model obtained by Constantino et al (2017) and remapped for the study area ( Fig. 3).…”
Section: Estimation Of Moho From Gravity Inversionmentioning
confidence: 99%
See 4 more Smart Citations
“…The modeling of the Te is made by a best fit of the flexure Moho with an independent Moho. For this paper, we use the model obtained by Constantino et al (2017) and remapped for the study area ( Fig. 3).…”
Section: Estimation Of Moho From Gravity Inversionmentioning
confidence: 99%
“…3. Moho from Gravity inversion (Constantino et al, 2017), superposed on the basement topography. RGR e Rio Grande Rise; Seamounts and Guyots (yellow with red contours); The São Paulo Ridge (SPR) and the Vema Aborted Ridge (VAR) are also represented.…”
Section: Flexural Modelingmentioning
confidence: 99%
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