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.

Gravity anomalies of three-dimensional bodies with a variable density contrast

1989 ◽  
Vol 130 (4) ◽  
pp. 711-719 ◽  
Author(s):  
I. V. Radhakrishna Murthy ◽  
P. Rama Rao ◽  
P. Ramakrishna
Keyword(s):  
Three Dimensional ◽  
Gravity Anomalies ◽  
Variable Density ◽  
Density Contrast

scholarly journals Application of particle swarm optimization for gravity inversion of 2.5-D sedimentary basins using variable density contrast

2017 ◽  
Vol 6 (1) ◽  
pp. 193-198 ◽  
Author(s):  
Kunal Kishore Singh ◽  
Upendra Kumar Singh
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Gravity Anomalies ◽  
Sedimentary Basins ◽  
Pso Algorithm ◽  
Density Contrast ◽  
Gravity Inversion ◽  
Western Anatolia ◽  
Swarm Optimization

Abstract. Particle swarm optimization (PSO) is a global optimization technique that works similarly to swarms of birds searching for food. A MATLAB code in the PSO algorithm has been developed to estimate the depth to the bottom of a 2.5-D sedimentary basin and coefficients of regional background from observed gravity anomalies. The density contrast within the source is assumed to vary parabolically with depth. Initially, the PSO algorithm is applied on synthetic data with and without some Gaussian noise, and its validity is tested by calculating the depth of the Gediz Graben, western Anatolia, and the Godavari sub-basin, India. The Gediz Graben consists of Neogen sediments, and the metamorphic complex forms the basement of the graben. A thick uninterrupted sequence of Permian–Triassic and partly Jurassic and Cretaceous sediments forms the Godavari sub-basin. The PSO results are better correlated with results obtained by the Marquardt method and borehole information.

Gravity inversion of an interface above which the density contrast varies exponentially with depth

Geophysics ◽  
1988 ◽  
Vol 53 (6) ◽  
pp. 837-845 ◽  
Author(s):  
Yufu Chai ◽  
William J. Hinze
Keyword(s):  
Los Angeles ◽  
Seismic Data ◽  
Gravity Anomalies ◽  
Sampling Technique ◽  
Sedimentary Basins ◽  
Density Contrast ◽  
Gravity Inversion ◽  
Los Angeles Basin ◽  
Deviation Equation ◽  
Basement Surface

Mapping of an interface above which the density contrast varies exponentially with depth, as is common at the basement surface of sedimentary basins, is efficiently achieved by a theoretically precise gravity method which can be applied to either profile data or twodimensional data. The contrast in mass above the interface is modeled by an array of vertical rectangular prisms with density contrasts varying exponentially with depth. Gravity anomalies due to the prisms are calculated in the wavenumber domain and then converted to the space domain. The precision of the inverse numerical Fourier transform in this procedure is significantly increased by a shift‐sampling technique based on the discrete Fourier deviation equation. Depth to the interface is determined by iterative adjustment of the vertical extent of the prisms in accordance with observed gravity anomaly data. The basement surface of the Los Angeles basin, California, calculated by this method, closely duplicates the published configuration based on drillhole data and seismic data.

scholarly journals Application of particle swarm optimization for gravity inversion of 2.5-D sedimentary basins using variable density contrast

2016 ◽  
Author(s):  
Kunal Kishore Singh ◽  
Upendra Kumar Singh
Keyword(s):  
Particle Swarm Optimization ◽  
Optimization Technique ◽  
Particle Swarm ◽  
Gravity Anomalies ◽  
Sedimentary Basins ◽  
Pso Algorithm ◽  
Density Contrast ◽  
Gravity Inversion ◽  
Western Anatolia ◽  
Swarm Optimization

Abstract. Particle swarm optimization (PSO) is a global optimization technique that works similarly to swarms of birds searching for food. A Matlab code in PSO algorithm is developed to estimate the depth to the bottom of a 2.5-D sedimentary basin and coefficients of regional background from observed gravity anomalies. The density contrast within the source is assumed to be varying parabolically with depth. Initially, the PSO algorithm is applied on synthetic data with and without some Gaussian noise and its validity is tested by calculating the depth of the Gediz Graben, Western Anatolia and Godavari sub-basin, India. The Gediz Graben consists of Neogen sediments and the metamorphic complex forms the basement of the Graben. A thick uninterrupted sequence of Permian-Triassic and partly Jurassic and Cretaceous sediments forms the Godavari sub-basin. The PSO results are better than the results obtained by Marquardt method and the results are well correlated with borehole information.

Gravity inversion of basement relief and estimation of density contrast variation with depth

Geophysics ◽  
2006 ◽  
Vol 71 (5) ◽  
pp. J51-J58 ◽  
Author(s):  
João B. Silva ◽  
Denis C. Costa ◽  
Valéria C. Barbosa
Keyword(s):  
Gravity Anomaly ◽  
Surface Density ◽  
Prior Information ◽  
Bouguer Anomaly ◽  
Gravity Anomalies ◽  
Sedimentary Basins ◽  
Density Contrast ◽  
Gravity Inversion ◽  
Contrast Variation ◽  
Interpretation Model

We present a method to estimate the basement relief as well as the density contrast at the surface and the hyperbolic decaying factor of the density contrast with depth, assuming that the gravity anomaly and the depth to the basement at a few points are known. In both cases, the interpretation model is a set of vertical rectangular 2D prisms whose thicknesses are parameters to be estimated and that represent the depth to the interface separating sediments and basement. The solutions to both problems are stable because of the incorporation of additional prior information about the smoothness of the estimated relief and the depth to the basement at a few locations, presumably provided by boreholes. The method was tested with synthetic gravity anomalies produced by simulated sedimentary basins with smooth relief, providing not only well-resolved estimated relief, but also good estimates for the density contrasts at the surface and for the decaying factors of the density contrast with depth. The method was applied to the Bouguer anomaly from Recôncavo Basin, estimating the surface density contrast and the decaying factor of the density contrast with depth as [Formula: see text] and [Formula: see text], respectively.

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