Experiences with the use of mass-density maps in residual gravity forward modelling

Sierra Negra volcano, the most voluminous shield volcano in the Galápagos archipelago and one of the largest basaltic calderas in the world, erupted on October 22, 2005 after more than [Formula: see text] of quiescence. GPS and satellite radar interferometry (InSAR) monitoring of the deformation of the caldera floor in the months prior to the eruption documented extraordinary inflation rates [Formula: see text]. The total amount of uplift recorded since monitoring began in 1992 approached [Formula: see text] at the center of the caldera over the eight days of the eruption the caldera floor deflated a maximum of 5 m and subsquently renewed its inflation, but at a decelerating rate. To gain insight into the nature of the subsurface mass/density changes associated with the deformation, gravity measurements performed in 2005, 2006, and 2007 are compared to previous measurements from 2001-2002 when the volcano underwent a period of minor deflation and magma withdrawal.The residual gravity decrease between 2001-2002 and 2005 is among the largest ever recorded atan active volcano (−950 μGal) and suggests that inflation was accompanied by a relative density decrease in the magmatic system. Forward modeling of the residual gravity data in 4D (from 2002 to 2005) gives an estimate of the amount of vesiculation in the shallow sill required to explain the observed gravity variations. Geochemical constraints from melt inclusion and satellite remote-sensing data allow us to estimate the pre-eruptive gas content of the magma and place constraints on the thickness of the gas-rich sill necessary to produce the gravity anomalies observed. Results suggest that reasonable sill thicknesses [Formula: see text] and bubble contents (10–50 volume %) can explain the large decrease in residual gravity prior to eruption. Following the eruption (2006 and 2007), the deformation and gravity patterns suggest re-equilibration of the pressure regime in the shallow magma system via a renewed influx of relatively gas-poor magma into the shallow parts of the system.

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Cap integration in spectral gravity forward modelling: near- and far-zone gravity effects via Molodensky’s truncation coefficients

Journal of Geodesy ◽

10.1007/s00190-018-1139-x ◽

2018 ◽

Vol 93 (1) ◽

pp. 65-83 ◽

Cited By ~ 6

Author(s):

Blažej Bucha ◽

Christian Hirt ◽

Michael Kuhn

Keyword(s):

Forward Modelling ◽

Gravity Forward Modelling ◽

Gravity Effects

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Spatial distribution of hydrocarbon reservoirs in the West Korea Bay Basin in the northern part of the Yellow Sea, estimated by 3-D gravity forward modelling

Geophysical Journal International ◽

10.1093/gji/ggw369 ◽

2016 ◽

Vol 208 (1) ◽

pp. 75-85 ◽

Cited By ~ 2

Author(s):

Sungchan Choi ◽

In-Chang Ryu ◽

H.-J. Götze ◽

Y. Chae

Keyword(s):

Spatial Distribution ◽

Yellow Sea ◽

Hydrocarbon Reservoirs ◽

The Yellow Sea ◽

Forward Modelling ◽

The West ◽

Gravity Forward Modelling

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Characterization of geothermally relevant structures at the top of crystalline basement in Switzerland by filters and gravity forward modelling

Geophysical Journal International ◽

10.1093/gji/ggu255 ◽

2014 ◽

Vol 199 (1) ◽

pp. 226-241 ◽

Cited By ~ 9

Author(s):

Yassine Abdelfettah ◽

Eva Schill ◽

Pascal Kuhn

Keyword(s):

Crystalline Basement ◽

Forward Modelling ◽

Gravity Forward Modelling

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A spectral-domain approach for gravity forward modelling of 2D bodies

Journal of Geodesy ◽

10.1007/s00190-019-01308-z ◽

2019 ◽

Vol 93 (10) ◽

pp. 2123-2144

Author(s):

Cheng Chen ◽

Shaofeng Bian ◽

Houpu Li

Keyword(s):

Spectral Domain ◽

Forward Modelling ◽

Spectral Domain Approach ◽

Gravity Forward Modelling

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The tree-canopy effect in gravity forward modelling

Geophysical Journal International ◽

10.1093/gji/ggz264 ◽

2019 ◽

Vol 219 (1) ◽

pp. 271-289 ◽

Cited By ~ 2

Author(s):

Meng Yang ◽

Christian Hirt ◽

Moritz Rexer ◽

Roland Pail ◽

Dai Yamazaki

Keyword(s):

Tree Canopy ◽

Data Sets ◽

Forward Modelling ◽

Bare Ground ◽

Gravity Forward Modelling ◽

Digital Elevation ◽

Canopy Effect ◽

Elevation Model ◽

Validation Experiments

SUMMARY High resolution and accurate digital terrain models (DTMs) are frequently used as input data sets to define the topographic masses in gravity forward modelling, for example, for terrain corrections in the context of regional gravity modelling. However, over vegetated areas such as forests and scrublands, the radar- and image-based digital elevation models (DEMs) may contain a tree bias, and therefore do not represent the bare-ground surface. The presence of vegetation-induced signals in DEMs, denoted here the tree-canopy effect, will introduce errors in the gravity forward modelling. In this study, the role of the tree-canopy effect in gravity forward modelling calculations is numerically investigated. First, spectral forward modelling techniques were applied to analyse a global tree-canopy bias model with a horizontal resolution of 1 km x 1 km and to quantify its effect on global gravity forward modelling results. We demonstrate that tree-canopy signals in the DEM produce a positive bias in the topographic gravitational field over vegetated areas, with values ranging from 0 to ∼2.7 mGal for gravity disturbances. Second, the role of the tree-canopy effect in high-frequency gravity forward modelling is studied using well-known residual terrain modelling (RTM) techniques. As DEM data sets, we used the 3″ SRTM (Shuttle Radar Topography Mission Digital 9 m Elevation Database) V4.1 (containing vegetation biases) and the 3″ MERIT-DEM (Multi-Error-Removed Improved-Terrain Digital elevation model) as a representation of the bare-ground elevations. Using Tasmania and the Amazon rainforest regions as test areas with significant tree-canopy signals we show that the tree-height effect on RTM calculations is of high-frequency nature, with rather small signals which reach in extreme cases amplitudes of ∼1–2 mGal occurring at forest boundaries. Third, using ground gravity observations, validation experiments were performed over the Australian Alps, Tasmania and the Canadian Rocky Mountains. All validation experiments show that the bare-ground elevation model MERIT-DEM performs better than SRTM V4.1 in terms of reduction of the discrepancies between modelled and observed gravity values. As a general conclusion, bare-ground DEM models should be preferred in any gravity forward modelling application to avoid or reduce the tree-canopy effect.

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Cap integration in spectral gravity forward modelling up to the full gravity tensor

Journal of Geodesy ◽

10.1007/s00190-019-01277-3 ◽

2019 ◽

Vol 93 (9) ◽

pp. 1707-1737 ◽

Cited By ~ 2

Author(s):

Blažej Bucha ◽

Christian Hirt ◽

Michael Kuhn

Keyword(s):

Forward Modelling ◽

Gravity Forward Modelling

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TGF: A New MATLAB-based Software for Terrain-related Gravity Field Calculations

Remote Sensing ◽

10.3390/rs12071063 ◽

2020 ◽

Vol 12 (7) ◽

pp. 1063

Author(s):

Meng Yang ◽

Christian Hirt ◽

Roland Pail

Keyword(s):

Density Distribution ◽

Gravity Field ◽

Mass Density ◽

Computation Time ◽

Spherical Approximation ◽

Constant Density ◽

Forward Modelling ◽

Gravity Effects ◽

Residual Terrain Modelling ◽

Elevation Model

With knowledge of geometry and density-distribution of topography, the residual terrain modelling (RTM) technique has been broadly applied in geodesy and geophysics for the determination of the high-frequency gravity field signals. Depending on the size of investigation areas, challenges in computational efficiency are encountered when using an ultra-high-resolution digital elevation model (DEM) in the Newtonian integration. For efficient and accurate gravity forward modelling in the spatial domain, we developed a new MATLAB-based program called, terrain gravity field (TGF). Our new software is capable of calculating the gravity field generated by an arbitrary topographic mass-density distribution. Depending on the attenuation character of gravity field with distance, the adaptive algorithm divides the integration masses into four zones, and adaptively combines four types of geometries (i.e., polyhedron, prism, tesseroid and point-mass) and DEMs with different spatial resolutions. Compared to some publicly available algorithms depending on one type of geometric approximation, this enables accurate modelling of gravity field and greatly reduces the computation time. Besides, the TGF software allows to calculate ten independent gravity field functionals, supports two types of density inputs (constant density value and digital density map), and considers the curvature of the Earth by involving spherical approximation and ellipsoidal approximation. Further to this, the TGF software is also capable of delivering the gravity field of full-scale topographic gravity field implied by masses between the Earth’s surface and mean sea level. In this contribution, the TGF software is introduced to the geoscience community and its capabilities are explained. Results from internal and external numerical validation experiments of TGF confirmed its accuracy at the sub-mGal level. Based on TGF, the trade-off between accuracy and efficiency, values for the spatial resolution and extension of topography models are recommended. The TGF software has been extensively tested and recently been applied in the SRTM2gravity project to convert the global 3” SRTM topography to implied gravity effects at 28 billion computation points. This confirms the capability of TGF for dealing with large datasets. Together with this paper, the TGF software will be released in the public domain for free use in geodetic and geophysical forward modelling computations.

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