scholarly journals Characterization of geological boundaries using 1‐D wavelet transform on gravity data: Theory and application to the Himalayas

Geophysics ◽  
2001 ◽  
Vol 66 (4) ◽  
pp. 1116-1129 ◽  
Author(s):  
G. Martelet ◽  
P. Sailhac ◽  
F. Moreau ◽  
M. Diament
Keyword(s):  
Wavelet Transform ◽  
Gravity Data ◽  
Real Data ◽  
Source Analysis ◽  
Gravity Inversion ◽  
Analysis Tool ◽  
Geometric Constructions ◽  
Complex Wavelets ◽  
Inversion Procedure ◽  
Geological Boundaries

We investigate the use of the continuous wavelet transform for gravity inversion. The wavelet transform operator has recently been introduced in the domain of potential fields both as a filtering and a source‐analysis tool. Here we develop an inverse scheme in the wavelet domain, designed to recover the geometric characteristics of density heterogeneities described by simple‐shaped sources. The 1‐D analyzing wavelet we use associates the upward continuation operator and linear combinations of derivatives of any order. In the gravity case, we first demonstrate how to localize causative sources using simple geometric constructions. Both the upper part of the source and the whole source can be studied when considering low or high altitudes, respectively. The homogeneity degree of the source is deduced without prior information and allows us to infer its shape. Introducing complex wavelets, we derive analytically the scaling behavior of the wavelet coefficients for the dyke and the step sources. The modulus term is used in an inversion procedure to recover the thickness of the source. The phase term provides its dip. This analysis is performed on gravity data we measured along a profile across the Himalayas in Nepal. Good agreement of our results with well‐documented thrusting structures demonstrates the applicability of the method to real data. Also, deeper, less constrained structures are characterized.

A method for inversion of 1D vertical soundings of gravity anomalies

Geophysics ◽  
2018 ◽  
Vol 83 (2) ◽  
pp. G15-G23
Author(s):  
Andrea Vitale ◽  
Domenico Di Massa ◽  
Maurizio Fedi ◽  
Giovanni Florio
Keyword(s):  
Potential Field ◽  
Field Data ◽  
Gravity Data ◽  
Finite Size ◽  
Gravity Anomalies ◽  
Real Data ◽  
Gravity Inversion ◽  
Chain Process ◽  
Potential Field Data ◽  
Gamma Density

We have developed a method to interpret potential fields, which obtains 1D models by inverting vertical soundings of potential field data. The vertical soundings are built through upward continuation of potential field data, measured on either a profile or a surface. The method assumes a forward problem consisting of a volume partitioned in layers, each of them homogeneous and horizontally finite, but with the density changing versus depth. The continuation errors, increasing with the altitude, are automatically handled by determining the coefficients of a third-order polynomial function of the altitude. Due to the finite size of the source volume, we need a priori information about the total horizontal extent of the volume, which is estimated by boundary analysis and optimized by a Markov chain process. For each sounding, a 1D inverse problem is independently solved by a nonnegative least-squares algorithm. Merging of the several inverted models finally yields approximate 2D or 3D models that are, however, shown to generate a good fit to the measured data. The method is applied to synthetic models, producing good results for either perfect or continued data. Even for real data, i.e., the gravity data of a sedimentary basin in Nevada, the results are interesting, and they are consistent with previous interpretation, based on 3D gravity inversion constrained by two gamma-gamma density logs.

Compact gravity inversion

Geophysics ◽  
1983 ◽  
Vol 48 (6) ◽  
pp. 713-721 ◽  
Author(s):  
B. J. Last ◽  
K. Kubik
Keyword(s):  
Density Distribution ◽  
Gravity Data ◽  
Gravity Anomalies ◽  
Complete Separation ◽  
Gravity Inversion ◽  
Dimensional Model ◽  
Regular Array ◽  
Anomalous Density ◽  
Inversion Procedure ◽  
New Criterion

We present a new criterion for the inversion of gravity data. The principle employed is to minimize the volume of the causative body, which is equivalent to maximizing its compactness. The anomalous density distribution is obtained using an iterative technique which is numerically stable and rapidly convergent. The principle can also be adapted to include modeling of gravity anomalies by single‐density sources. The advantage of this approach is that desirable geologic characteristics are automatically incorporated into the model with a minimum of subjective judgments on the part of the interpreter. The treatment of noise in the data fits naturally into the formulation of the inversion procedure. The method is illustrated by the inversion of noise‐free and noisy data generated from a two‐dimensional model consisting of a regular array of identical rectangular blocks whose densities can be individually specified. In every case the algorithm successfully recovers the correct density distribution from the data. In the case of noise‐contaminated data, a complete separation of the noise from the signal is achieved. The practical effectiveness of the method is demonstrated by the inversion of published gravity data. The results obtained are compared with existing models and with available drilling information.

Clustering and constrained inversion of seismic refraction and gravity data for overburden stripping: Application to uranium exploration in the Athabasca Basin, Canada

Geophysics ◽  
2020 ◽  
Vol 85 (4) ◽  
pp. B133-B146 ◽  
Author(s):  
Mehrdad Darijani ◽  
Colin G. Farquharson ◽  
Peter G. Lelièvre
Keyword(s):  
Gravity Data ◽  
Seismic Refraction ◽  
Real Data ◽  
Drill Hole ◽  
Gravity Inversion ◽  
Glacial Sediments ◽  
Athabasca Basin ◽  
Overburden Thickness ◽  
Uranium Exploration ◽  
Fuzzy C Means Clustering

Gravity signatures from features associated with the footprints of uranium deposits within the sandstones and basement of the Athabasca Basin are masked in the measured gravity by the contribution from glacial sediments (overburden), in particular by the variable thickness of the overburden. The 2D inversions of seismic refraction and gravity data are assessed as a means of reliably mapping overburden thickness, enabling the contribution to gravity from the overburden to be taken into account and density anomalies associated with deeper mineralization and alteration to be reconstructed through further inversion. Results show that independent inversion of seismic refraction data using the fuzzy c-means clustering method is able to determine the base of overburden well. Subsequent gravity inversion constrained by the overburden thickness reveals possible subtle density variations at depth, which could be associated with alteration in the sandstones associated with the uranium mineralization. Application of the seismic clustering inversion followed by constrained gravity inversion to both representative synthetic scenarios and real data from the Athabasca Basin, Canada, are considered. Drill-hole data show that the inversion results can predict the base of the overburden well, and there is an acceptable match between geologic information and possible alteration zones suggested by the inversions.

Integration of geophysical constraints for multilayer geometry refinements in 2.5D gravity inversion

Geophysics ◽  
2016 ◽  
Vol 81 (5) ◽  
pp. G95-G106 ◽  
Author(s):  
Jian Xing ◽  
Tianyao Hao ◽  
Ya Xu ◽  
Zhiwei Li
Keyword(s):  
Gravity Data ◽  
Inequality Constraints ◽  
Real Data ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Sharp Condition ◽  
Estimated Parameters ◽  
Multiple Interfaces ◽  
Variation Function ◽  
Different Depths

We have explored the feasibility of estimating depths of multiple interfaces from gravity data. The strata are simulated by an aggregate of 3D rectangular prisms whose bottom depths are parameters to be estimated. In the inversion process, we have integrated geophysical constraints including the borehole information and the sharp condition described by the total variation function. The iterative residual function is also introduced to adjust the weighting of the estimated parameters so that layers of different depths have nearly equal likelihood for deviation. The inversion is processed by minimizing the Tikhonov parametric functional by the reweighted regularized conjugate gradient method. Inequality constraints are adopted to deal with the coupling of the interfaces. Synthetic tests show that such integration is conducive to restoring the multilayer depth distribution. Real data applications in Mariana confirm that the inversion method is effective in complex geologic settings in practice. We have also evaluated several issues that specifically deserve attention for obtaining satisfactory results in multilayer gravity inversion.

Three-dimensional gravity inversion using graph theory to delineate the skeleton of homogeneous sources

Geophysics ◽  
2015 ◽  
Vol 80 (2) ◽  
pp. G53-G66 ◽  
Author(s):  
Rodrigo Bijani ◽  
Cosme F. Ponte-Neto ◽  
Dionisio U. Carlos ◽  
Fernando J. S. Silva Dias
Keyword(s):  
Genetic Algorithm ◽  
Graph Theory ◽  
Minimum Spanning Tree ◽  
Gravity Data ◽  
A Priori ◽  
Three Dimensional ◽  
Real Data ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Dimensional Gravity

We developed a new strategy, based on graph theory concepts, to invert gravity data using an ensemble of simple point masses. Our method consisted of a genetic algorithm with elitism to generate a set of possible solutions. Each estimate was associated to a graph to solve the minimum spanning tree (MST) problem. To produce unique and stable estimates, we restricted the position of the point masses by minimizing the statistical variance of the distances of an MST jointly with the data-misfit function during the iterations of the genetic algorithm. Hence, the 3D spatial distribution of the point masses identified the skeleton of homogeneous gravity sources. In addition, our method also gave an estimation of the anomalous mass of the source. So, together with the anomalous mass, the skeleton could aid other 3D methods with promising geometric a priori parameters. Several tests with different values of regularizing parameter were made to bespeak this new regularizing strategy. The inversion results applied to noise-corrupted synthetic gravity data revealed that, regardless of promising starting models, the estimated distribution of point masses and the anomalous mass offered valuable information about the homogeneous sources in the subsurface. Tests on real data from a portion of Quadrilátero Ferrífero, Minas Gerais state, Brazil, were performed for complementary analysis of the proposed inversion method.

Assessing Model Uncertainty for the Scaling Function Inversion of Potential Fields

Geophysics ◽  
2021 ◽  
pp. 1-39
Author(s):  
Mahak Singh Chauhan ◽  
Ivano Pierri ◽  
Mrinal K. Sen ◽  
Maurizio FEDI
Keyword(s):  
Simulated Annealing Algorithm ◽  
Scaling Function ◽  
Vertical Section ◽  
Gravity Data ◽  
Geometric Model ◽  
Salt Dome ◽  
The Body ◽  
Gravity Inversion ◽  
Geometrical Parameters ◽  
The Scaling Function

We use the very fast simulated annealing algorithm to invert the scaling function along selected ridges, lying in a vertical section formed by upward continuing gravity data to a set of altitudes. The scaling function is formed by the ratio of the field derivative by the field itself and it is evaluated along the lines formed by the zeroes of the horizontal field derivative at a set of altitudes. We also use the same algorithm to invert gravity anomalies only at the measurement altitude. Our goal is analyzing the different models obtained through the two different inversions and evaluating the relative uncertainties. One main difference is that the scaling function inversion is independent on density and the unknowns are the geometrical parameters of the source. The gravity data are instead inverted for the source geometry and the density simultaneously. A priori information used for both the inversions is that the source has a known depth to the top. We examine the results over the synthetic examples of a salt dome structure generated by Talwani’s approach and real gravity datasets over the Mors salt dome and the Decorah (USA) basin. For all these cases, the scaling function inversion yielded models with a better sensitivity to specific features of the sources, such as the tilt of the body, and reduced uncertainty. We finally analyzed the density, which is one of the unknowns for the gravity inversion and it is estimated from the geometric model for the scaling function inversion. The histograms over the density estimated at many iterations show a very concentrated distribution for the scaling function, while the density contrast retrieved by the gravity inversion, according to the fundamental ambiguity density/volume, is widely dispersed, this making difficult to assess its best estimate.

3D stochastic gravity inversion using nonstationary covariances

Geophysics ◽  
2013 ◽  
Vol 78 (2) ◽  
pp. G15-G24 ◽  
Author(s):  
Pejman Shamsipour ◽  
Denis Marcotte ◽  
Michel Chouteau ◽  
Martine Rivest ◽  
Abderrezak Bouchedda
Keyword(s):  
Real Data ◽  
Gravity Inversion ◽  
Data Set ◽  
The Real ◽  
Statistical Homogeneity ◽  
Nonstationary Covariance ◽  
Surface Geology ◽  
Synthetic Models ◽  
Stochastic Gravity

The flexibility of geostatistical inversions in geophysics is limited by the use of stationary covariances, which, implicitly and mostly for mathematical convenience, assumes statistical homogeneity of the studied field. For fields showing sharp contrasts due, for example, to faults or folds, an approach based on the use of nonstationary covariances for cokriging inversion was developed. The approach was tested on two synthetic cases and one real data set. Inversion results based on the nonstationary covariance were compared to the results from the stationary covariance for two synthetic models. The nonstationary covariance better recovered the known synthetic models. With the real data set, the nonstationary assumption resulted in a better match with the known surface geology.

scholarly journals P-wave velocity and density structure beneath Mt. Vesuvius: a magma body in the upper edifice?

2013 ◽  
Vol 56 (4) ◽  
Author(s):  
Paolo Capuano ◽  
Guido Russo ◽  
Roberto Scarpa
Keyword(s):  
High Resolution ◽  
Wave Velocity ◽  
Gravity Data ◽  
High Energy ◽  
P Wave ◽  
Gravity Inversion ◽  
Density Structure ◽  
Resolution Image ◽  
High Resolution Image ◽  
P Wave Velocity

<p>A high-resolution image of the compressional wave velocity and density structure in the shallow edifice of Mount Vesuvius has been derived from simultaneous inversion of travel times and hypocentral parameters of local earthquakes and from gravity inversion. The robustness of the tomography solution has been improved by adding to the earthquake data a set of land based shots, used for constraining the travel time residuals. The results give a high resolution image of the P-wave velocity structure with details down to 300-500 m. The relocated local seismicity appears to extend down to 5 km depth below the central crater, distributed into two clusters, and separated by an anomalously high Vp region positioned at around 1 km depth. A zone with high Vp/Vs ratio in the upper layers is interpreted as produced by the presence of intense fluid circulation alternatively to the interpretation in terms of a small magma chamber inferred by petrologic studies. In this shallower zone the seismicity has the minimum energy, whilst most of the high-energy quakes (up to Magnitude 3.6) occur in the cluster located at greater depth. The seismicity appears to be located along almost vertical cracks, delimited by a high velocity body located along past intrusive body, corresponding to remnants of Mt. Somma. In this framework a gravity data inversion has been performed to study the shallower part of the volcano. Gravity data have been inverted using a method suitable for the application to scattered data in presence of relevant topography based on a discretization of the investigated medium performed by establishing an approximation of the topography by a triangular mesh. The tomography results, the retrieved density distribution, and the pattern of relocated seismicity exclude the presence of significant shallow magma reservoirs close to the central conduit. These should be located at depth higher than that of the base of the hypocenter volume, as evidenced by previous studies.</p>

scholarly journals EyeMMV toolbox: An eye movement post-analysis tool based on a two-step spatial dispersion threshold for fixation identification

2014 ◽  
Vol 7 (1) ◽  
Author(s):  
Vassilios Krassanakis ◽  
Vassiliki Filippakopoulou ◽  
Byron Nakos
Keyword(s):  
Eye Movement ◽  
Spatial Dispersion ◽  
Computer Software ◽  
Movement Analysis ◽  
Source Analysis ◽  
Analysis Tool ◽  
Identification Algorithm ◽  
Strongly Correlated ◽  
Scripting Language ◽  
Visualization Techniques

Eye movement recordings and their analysis constitute an effective way to examine visual perception. There is a special need for the design of computer software for the performance of data analysis. The present study describes the development of a new toolbox, called EyeMMV (Eye Movements Metrics & Visualizations), for post experimental eye movement analysis. The detection of fixation events is performed with the use of an introduced algorithm based on a two-step spatial dispersion threshold. Furthermore, EyeMMV is designed to support all well-known eye tracking metrics and visualization techniques. The results of fixation identification algorithm are compared with those of an algorithm of dispersion-type with a moving window, imported in another open source analysis tool. The comparison produces outputs that are strongly correlated. The EyeMMV software is developed using the scripting language of MATLAB and the source code is distributed through GitHub under the third version of GNU General Public License (link: https://github.com/krasvas/EyeMMV).

Architecture and dynamics of the magmatic system feeding the 2018 offshore Mayotte eruption from satellite gravity data

2021 ◽  
Author(s):  
Hélène Le Mével ◽  
Craig A. Miller ◽  
Yan Zhan
Keyword(s):  
Gravity Data ◽  
System Structure ◽  
Constant Thickness ◽  
Gravity Inversion ◽  
Model Parameters ◽  
Low Density ◽  
Submarine Eruption ◽  
Magmatic System ◽  
Magma Flow ◽  
Marine Gravity

&lt;p&gt;In May 2018, a submarine eruption started offshore Mayotte (Comoros archipelago, Indian Ocean), and was first detected as a series of earthquake swarms. Since then, at least 6.4 km&lt;sup&gt;3&lt;/sup&gt; of lava has erupted from a newly mapped volcanic edifice (MAYOBS campaigns), about 50 km east of Mayotte island. Since the onset of the eruption, GNSS stations on the island have recorded subsidence (up to 17 cm) and eastward displacement (up to 23 cm). We combine marine gravity data derived from satellite altimetry with finite element models to examine the magmatic system structure and its dynamics. First, we calculate the Mantle Bouguer Anomaly (MBA) by taking into account the gravitational effect of the bathymetry and the Moho interfaces, assuming a crust of constant thickness of 17.5 km and correction densities of 2.8 g/cm&lt;sup&gt;3&lt;/sup&gt; and 3.3 g/cm&lt;sup&gt;3&lt;/sup&gt; for the crust and mantle, respectively. We then invert the MBA to determine the anomalous density structures within the lithosphere, using the mixed Lp-norm inversion and Gauss-Newton optimization implemented in the SimPEG framework. The gravity inversion reveals two zones of low density, east of Mayotte island. The first is located NE of Petite Terre island between ~15 and 35 km depth, and the second is located further east, south of La Jumelle seamounts and extends from ~25 to 35 km depth. We interpret these low density regions as regions of partial melt stored in the lithosphere and estimate the volume of stored magma. Finally, we use the newly imaged low density bodies to constrain the magma reservoir geometry and simulate magma flow from this reservoir to the eruptive vent in a 3D, time-dependent, numerical model. The model parameters are adjusted by minimizing the misfit between the modeled surface displacement and that measured at the 6 GPS sites, between May 2018 and 2020. The deformation modeling reveals the temporal evolution of the magma flux during the eruption, and the resulting stress distribution in the crust explains the patterns of recorded seismicity. Together with the existing seismic and geodetic studies, the gravity data analysis and FEM models bring new constraints on the architecture of the magma plumbing system and the magmatic processes behind the largest submarine eruption ever documented.&lt;/p&gt;

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