Noniterative gravity inversion method with variable density contrast

1994 ◽  
Author(s):  
Guspí Fernando
Keyword(s):  
Variable Density ◽  
Density Contrast ◽  
Gravity Inversion ◽  
Inversion Method

Gravity inversion using open, reject, and “shape‐of‐anomaly” fill criteria

Geophysics ◽  
1986 ◽  
Vol 51 (4) ◽  
pp. 988-994 ◽  
Author(s):  
R. M. René
Keyword(s):  
Center Of Mass ◽  
Initial Density ◽  
Model Space ◽  
Constant Factor ◽  
Density Contrast ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Inverse Models ◽  
Seed Method ◽  
The Given

A gravity inversion method is developed by iteratively applying open, reject, and fill (O-R-F) criteria within a model space comprising a great many rectangular prisms. Each prism is assigned a density contrast. The modeling procedure consists of filling some prisms while leaving others empty. Only one element is filled for each pass. Generally, elements are added only to the periphery of the growing model. Models can be allowed to grow in any combination of directions, or in all directions. By application of a “shape‐of‐anomaly” fill criterion, the model rapidly attains a form which yields gravity approximating the given gravity scaled down by some constant factor. As the model continues to grow, this scale factor approaches unity. The method readily yields inverse models comprising several thousand individual prisms. Examples presented here give applications to 2-D problems. The method is readily applicable to [Formula: see text] and 3-D problems as well. Overhanging elements are obtained by appropriate use of model constraints. Initial density models are not required but they are allowed. An “expanding seed” method is explained which efficiently generates sets of inverse models by using dense models to initiate development of less dense models. The method is applied to inversion of several synthetic gravity profiles from known density models. A density model is also derived from gravity across the Troodos massif in Cyprus. Using a density contrast of [Formula: see text], the resultant model extends from the surface to a depth of 20.6 km and has a center of mass distribution displaced approximately 7 km to the northeast of the anomaly peak.

Adaptive learning 3D gravity inversion for salt-body imaging

Geophysics ◽  
2011 ◽  
Vol 76 (3) ◽  
pp. I49-I57 ◽  
Author(s):  
Fernando J. S. Silva Dias ◽  
Valéria C. F. Barbosa ◽  
João B. C. Silva
Keyword(s):  
Adaptive Learning ◽  
Learning Strategy ◽  
Gravity Data ◽  
Density Contrast ◽  
Piecewise Constant Function ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Outer Loop ◽  
Bottom Depth ◽  
Geometric Elements

We have developed an iterative scheme for inverting gravity data produced by salt bodies with density contrasts relative to the sediments varying from positive to negative, crossing, in this way, the nil zone. Our inversion method estimates a 3D density-contrast distribution, through a piecewise constant function defined on a user-specified grid of cells. It consists of two nested iterative loops. The outer loop uses an adaptive learning strategy that starts with a coarse grid of cells, a set of first-guess geometric elements (axes and points) and the corresponding assigned density contrasts. From the second iteration on, this strategy refines the grid and automatically creates a new set of geometric elements (points only) and associated density contrasts. Each geometric element operates as the first-guess skeletal outline of a section of the salt body to be imaged. The inner loop estimates the 3D density-contrast distribution for the grid of cells and for the set of geometric elements defined in the outer loop. The outer loop allows for easy incorporation of prior geologic information about the lithologic units and automatic evolution of the prior information. The inner loop forces the estimated density contrast of each cell to be close either to a null or to a non-null prespecified value. The iteration stops when the geometries of the estimated salt bodies are invariant along successive iterations. We apply our method to synthetic gravity data produced by a homogeneous salt body embedded in heterogeneous sediments. We tested two geologic hypotheses about the real gravity data from Galveston Island salt dome, USA. In the first, the estimated salt body attains a maximum bottom depth of 5 km, whereas in the second hypothesis, it is shallower and discloses an overhang. Both solutions fit the data and are feasible geologically, so both hypotheses are acceptable.

Sensitivity analysis of gravity gradient inversion of the Moho depth—a case example for the Amazonian Craton

2020 ◽  
Vol 221 (3) ◽  
pp. 1896-1912
Author(s):  
Peter Haas ◽  
Jörg Ebbing ◽  
Wolfgang Szwillus
Keyword(s):  
Variable Density ◽  
Density Contrast ◽  
Moho Depth ◽  
Gravity Gradient ◽  
Gravity Inversion ◽  
Vertical Gravity Gradient ◽  
Novel Approach ◽  
Amazonian Craton ◽  
Fold Belts ◽  
Vertical Gravity

SUMMARY We present a novel approach for linearized gravity inversion to estimate the Moho depth, which allows the use of any gravitational component instead of the vertical gravity component only. The inverse problem is solved with the Gauss–Newton algorithm and the gravitational field of the undulating Moho depth is calculated with tesseroids. Hereby, the density contrast can be laterally variable by using information from seismological regionalization. Our approach is illustrated with a synthetic example, which we use to explore different regularization parameters. The vertical gravity gradient gzz provides the most reasonable results with appropriate parameters. As a case example, we invert for the Moho depth of the Amazonian Craton and its surroundings. The results are constrained by estimates from active seismic measurements. Our new Moho depth model correlates to tectonic domains and is in agreement with previous models. The estimated density contrasts of the tectonic domains agree well with the lithospheric architecture and show with 300–450 kg m–3 lower density contrasts for continental domains, whereas the oceans reveal a density contrast of 450–500 kg m–3. The wider range of estimated density contrast for the continent reflects uncertainties in Precambrian Fold Belts that arise from its small gravity signal. Our results demonstrate that a variable density contrast at the Moho depth is a valuable enhancement for gravity inversion.

Simultaneous 3D depth-to-basement and density-contrast estimates using gravity data and depth control at few points

Geophysics ◽  
2010 ◽  
Vol 75 (3) ◽  
pp. I21-I28 ◽  
Author(s):  
Cristiano M. Martins ◽  
Valeria C. Barbosa ◽  
João B. Silva
Keyword(s):  
Gravity Data ◽  
Synthetic Data ◽  
Structural Features ◽  
Density Contrast ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Contrast Variation ◽  
Parabolic Law ◽  
Depth Control ◽  
Basement Depth

We have developed a gravity-inversion method for simultaneously estimating the 3D basement relief of a sedimentary basin and the parameters defining a presumed parabolic decay of the density contrast with depth in a sedimentary pack, assuming prior knowledge about the basement depth at a few points. The sedimentary pack is approximated by a grid of 3D vertical prisms juxtaposed in both horizontal directions of a right-handed coordinate system. The prisms’ thicknesses represent the depths to the basement and are the parameters to be estimated from the gravity data. To estimate the parameters defining the parabolic decay of the density contrast with depth and to produce stable depth-to-basement estimates, we imposed smoothness on the basement depths and proximity between estimated and known depths at boreholes. We applied our method to synthetic data from a simulated complex 3D basement relief with two sedimentary sections having distinct parabolic laws describing the density-contrast variation with depth. The results provide good estimates of the true parameters of the parabolic law of density-contrast decay with depth and of the basement relief. Inverting the gravity data from the onshore and part of the shallow offshore Almada Basin on Brazil’s northeastern coast shows good correlation with known structural features.

3D gravity inversion through an adaptive-learning procedure

Geophysics ◽  
2009 ◽  
Vol 74 (3) ◽  
pp. I9-I21 ◽  
Author(s):  
Fernando J. Silva Dias ◽  
Valéria C. Barbosa ◽  
João B. Silva
Keyword(s):  
Adaptive Learning ◽  
Measurement Errors ◽  
Gravity Anomalies ◽  
Density Contrast ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Target Density ◽  
Geometric Element ◽  
Geometric Elements ◽  
Interpretation Model

We have developed a gravity inversion method to estimate a 3D density-contrast distribution producing strongly interfering gravity anomalies. The interpretation model consists of a grid of 3D vertical, juxtaposed prisms in the horizontal and vertical directions. Iteratively, our approach estimates the 3D density-contrast distribution that fits the observed anomaly within the measurement errors and favors compact gravity sources closest to prespecified geometric elements such as axes and points. This method retrieves the geometry of multiple gravity sources whose density contrasts (positive and negative values) are prescribed by the interpreter through the geometric element. At the first iteration, we set an initial interpretation model and specify the first-guess geometric elements and their target density contrasts. Each geometric element operates as the first-guess skeletal outline of the entire homogeneous gravity source or any of its homogeneous parts to be reconstructed. From the second iteration on, our method automatically redefines a new set of geometric elements, the associated target density contrasts, and a new interpretation model whose number of prisms increases with the iteration. The iteration stops when the geometries of the estimated sources are invariant along successive iterations. Tests on synthetic data from geometrically complex bodies and on field data collected over a mafic-ultramafic body and a volcanogenic sedimentary sequence located in the Tocantins Province, Brazil, confirmed the potential of our method in producing a sharp image of multiple and adjacent bodies.

Three‐dimensional Fourier gravity inversion with arbitrary density contrast

Geophysics ◽  
1992 ◽  
Vol 57 (1) ◽  
pp. 131-135 ◽  
Author(s):  
F. Guspí
Keyword(s):  
Frequency Domain ◽  
Three Dimensional ◽  
Gravity Anomalies ◽  
Sedimentary Basins ◽  
Variable Density ◽  
Density Contrast ◽  
Gravity Inversion ◽  
Linear Quadratic ◽  
Space Domain ◽  
Depth Functions

The use of variable‐density contrasts in gravity inversion has gained increasing importance in recent years due to the necessity of constructing more realistic models of geophysical structures such as sedimentary basins. Linear, quadratic, and exponential variations, either in the space or in the frequency domain, are the basis of several methods. See, among others, the papers by Granser (1987), Chai and Hinze (1988), Reamer and Ferguson (1989), and Rao et al. (1990). Guspí (1990) used polynomial density‐depth functions for inverting gravity anomalies into 2-D polygons in the space domain.

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