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

<p>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<sup>3</sup> 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<sup>3</sup> and 3.3 g/cm<sup>3</sup> 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.</p>

scholarly journals 3D Gravity Inversion on Unstructured Grids

2021 ◽  
Vol 11 (2) ◽  
pp. 722
Author(s):  
Siyuan Sun ◽  
Changchun Yin ◽  
Xiuhe Gao
Keyword(s):  
Objective Function ◽  
Unstructured Grids ◽  
Gravity Data ◽  
Depth Resolution ◽  
Continuous Model ◽  
Gravity Inversion ◽  
Inversion Method ◽  
Model Parameters ◽  
Fuzzy C Means ◽  
Fuzzy C Means Clustering

Compared with structured grids, unstructured grids are more flexible to model arbitrarily shaped structures. However, based on unstructured grids, gravity inversion results would be discontinuous and hollow because of cell volume and depth variations. To solve this problem, we first analyzed the gradient of objective function in gradient-based inversion methods, and a new gradient scheme of objective function is developed, which is a derivative with respect to weighted model parameters. The new gradient scheme can more effectively solve the problem with lacking depth resolution than the traditional inversions, and the improvement is not affected by the regularization parameters. Besides, an improved fuzzy c-means clustering combined with spatial constraints is developed to measure property distribution of inverted models in both spatial domain and parameter domain simultaneously. The new inversion method can yield a more internal continuous model, as it encourages cells and their adjacent cells to tend to the same property value. At last, the smooth constraint inversion, the focusing inversion, and the improved fuzzy c-means clustering inversion on unstructured grids are tested on synthetic and measured gravity data to compare and demonstrate the algorithms proposed in this paper.

Mapping crustal thickness using marine gravity data: Methods and uncertainties

Geophysics ◽  
2014 ◽  
Vol 79 (2) ◽  
pp. G27-G36 ◽  
Author(s):  
Yongliang Bai ◽  
Simon E. Williams ◽  
R. Dietmar Müller ◽  
Zhan Liu ◽  
Maral Hosseinpour
Keyword(s):  
Gravity Anomaly ◽  
Lithospheric Mantle ◽  
Gravity Data ◽  
Sedimentary Cover ◽  
Crustal Thickness ◽  
Alternative Methods ◽  
Gravity Inversion ◽  
Northern Margin ◽  
Marine Gravity ◽  
Moho Depths

Crustal thickness is a critical parameter for understanding the processes of continental rifting and breakup and the evolution of petroleum systems within passive margins. However, direct measurements of crustal thickness are sparse and expensive, highlighting the need for methodologies using gravity anomaly data, jointly with other geophysical data, to estimate crustal thickness. We evaluated alternative gravity inversion methodologies to map crustal thickness variations at rifted continental margins and adjacent oceanic basins, and we tested our methodology in the South China Sea (SCS). Different strategies were investigated to estimate and remove the gravity effect of density variations of sediments and the temperature and pressure variations of the lithospheric mantle from the observed free air gravity anomaly data. Sediment density was calculated using a relationship between sediment thickness, porosity, and density. We found that this method is essential for crustal thickness inversion in the presence of a thick sedimentary cover by comparing the Moho depths obtained from gravity inversion and seismic interpretation in the Yinggehai Basin where sediments are up to 13 km thick; the inversion accuracy depended on the parameters of the exponential equation between porosity and the buried depth. We modeled the lithospheric mantle temperature field based on oceanic crustal age, continental crustal stretching factors, and other boundary conditions. We tested three different methods to calculate the thermal expansion coefficient, which is either held constant or is a linear/polynomial function of temperature, for applying a thermal correction and found that the inversion results were relatively insensitive to alternative methods. We compared inversion results with two recent deep seismic profiles that image the rifted continental edge at the northern margin of the SCS and the continental Liyue Bank (Reed Bank) at the southern margin, and we found that the inversion accuracy was improved considerably by removing sediment, thermal, and pressure gravity effects.

Joint Gramian inversion of geophysical data with different resolution capabilities: case study in Yellowstone

2021 ◽  
Author(s):  
Xiaolei Tu ◽  
Michael S Zhdanov
Keyword(s):  
Joint Inversion ◽  
Gravity Data ◽  
Geophysical Methods ◽  
Structural Similarity ◽  
Geophysical Data ◽  
P Wave ◽  
Model Parameters ◽  
Magmatic System ◽  
Low Velocity ◽  
Velocity Anomaly

Summary Joint inversion of multiphysics data is a practical approach to the integration of geophysical data, which produces models of reduced uncertainty and improved resolution. The development of effective methods of joint inversion requires considering different resolutions of different geophysical methods. This paper presents a new framework of joint inversion of multiphysics data, which is based on a novel formulation of Gramian constraints and mitigates the difference in resolution capabilities of different geophysical methods. Our approach enforces structural similarity between different model parameters through minimizing a structural Gramian term, and it also balances the different resolutions of geophysical methods using a multiscale resampling strategy. The effectiveness of the proposed method is demonstrated by synthetic model study of joint inversion of the P-wave traveltime and gravity data. We apply a novel method based on Gramian constraints and multiscale resampling to jointly invert the gravity and seismic data collected in Yellowstone national Park to image the crustal magmatic system of the Yellowstone. Our results helped to produce a consistent image of the crustal magmatic system of the Yellowstone expressed both in low-density and low-velocity anomaly just beneath the Yellowstone caldera.

Sediment Stripping Correction to Marine Gravity Data

2014 ◽  
Vol 37 (4) ◽  
pp. 419-439 ◽  
Author(s):  
Wenjin Chen ◽  
Robert Tenzer ◽  
Xiang Gu
Keyword(s):  
Gravity Data ◽  
Marine Gravity

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.

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 Disjoint interval bound constraints using the alternating direction method of multipliers (ADMM) for geologically constrained inversion: Application to gravity data

Geophysics ◽  
2020 ◽  
pp. 1-45
Author(s):  
Vitaliy Ogarko ◽  
Jérémie Giraud ◽  
Roland Martin ◽  
Mark Jessell
Keyword(s):  
Gravity Data ◽  
Alternating Direction Method ◽  
Rock Properties ◽  
Model Parameters ◽  
Method Of Multipliers ◽  
Geological Modeling ◽  
Bound Constraints ◽  
Data Inversion ◽  
Alternating Direction ◽  
Geological Information

To reduce uncertainties in reconstructed images, geological information must be introduced in a numerically robust and stable way during the geophysical data inversion procedure. In the context of potential (gravity) data inversion, it is important to bound the physical properties by providing probabilistic information on the number of lithologies and ranges of values of possibly existing related rock properties (densities). For this purpose, we introduce a generalization of bounding constraints for geophysical inversion based on the alternating direction method of multipliers (ADMM). The flexibility of the proposed technique enables us to take into account petrophysical information as well as probabilistic geological modeling, when it is available. The algorithm introduces a priori knowledge in terms of physically acceptable bounds of model parameters based on the nature of the modeled lithofacies in the region under study. Instead of introducing only one interval of geologically acceptable values for each parameter representing a set of rock properties, we define sets of disjoint intervals using the available geological information. Different sets of intervals are tested, such as quasi-discrete (or narrow) intervals as well as wider intervals provided by geological information obtained from probabilistic geological modeling. Narrower intervals can be used as soft constraints encouraging quasi-discrete inversions. The algorithm is first applied to a synthetic 2D case for proof-of-concept validation and then to the 3D inversion of gravity data collected in the Yerrida basin (Western Australia). Numerical convergence tests show the robustness and stability of the bound constraints we apply, which is not always trivial for constrained inversions. This technique can be a more reliable uncertainty reduction method as well as an alternative to other petrophysically or geologically constrained inversions based on more classical “clustering” or Gaussian-mixture approaches.

scholarly journals Lineament Extraction using Gravity Data in the Citarum Watershed

2021 ◽  
Vol 53 (1) ◽  
Author(s):  
Gumilar Utamas Nugraha ◽  
Karit Lumban Goal ◽  
Lina Handayani ◽  
Rachmat Fajar Lubis
Keyword(s):  
Gravity Data ◽  
Bouguer Anomaly ◽  
High Density ◽  
Low Density ◽  
Residual Value ◽  
Satellite Gravity ◽  
Structural Weakness ◽  
Major Trend ◽  
Lineament Extraction ◽  
Butterworth Filters

Lineament is one of the most important features showing subsurface elements or structural weakness such as faults. This study aims to identify subsurface lineament patterns using automatic lineament in Citarum watershed with gravity data. Satellite gravity data were used to generate a sub-surface lineament. Satellite gravity data corrected using Bouguer and terrain correction to obtain a complete Bouguer anomaly value. Butterworth filters were used to separate regional and residual anomaly from the complete Bouguer anomaly value. Residual anomaly gravity data used to analyze sub-surface lineament. Lineament generated using Line module in PCI Geomatica to obtain sub-surface lineament from gravity residual value. The orientations of lineaments and fault lines were created by using rose diagrams. The main trends observed in the lineament map could be recognized in these diagrams, showing a strongly major trend in NW-SE, and the subdominant directions were in N-S. Area with a high density of lineament located at the Southern part of the study area. High-density lineament might be correlated with fractured volcanic rock upstream of the Citarum watershed, meanwhile, low-density lineament is associated with low-density sediment. The high-density fracture might be associated with intensive tectonics and volcanism.

Inversion and uncertainty estimation of gravity data using simulated annealing: An application over Lake Vostok, East Antarctica

Geophysics ◽  
2005 ◽  
Vol 70 (1) ◽  
pp. J1-J12 ◽  
Author(s):  
Lopamudra Roy ◽  
Mrinal K. Sen ◽  
Donald D. Blankenship ◽  
Paul L. Stoffa ◽  
Thomas G. Richter
Keyword(s):  
Simulated Annealing ◽  
Gravity Data ◽  
A Priori ◽  
Model Space ◽  
Uncertainty Estimation ◽  
East Antarctica ◽  
Airborne Gravity ◽  
Model Parameters ◽  
Data Set ◽  
Lake Vostok

Interpretation of gravity data warrants uncertainty estimation because of its inherent nonuniqueness. Although the uncertainties in model parameters cannot be completely reduced, they can aid in the meaningful interpretation of results. Here we have employed a simulated annealing (SA)–based technique in the inversion of gravity data to derive multilayered earth models consisting of two and three dimensional bodies. In our approach, we assume that the density contrast is known, and we solve for the coordinates or shapes of the causative bodies, resulting in a nonlinear inverse problem. We attempt to sample the model space extensively so as to estimate several equally likely models. We then use all the models sampled by SA to construct an approximate, marginal posterior probability density function (PPD) in model space and several orders of moments. The correlation matrix clearly shows the interdependence of different model parameters and the corresponding trade-offs. Such correlation plots are used to study the effect of a priori information in reducing the uncertainty in the solutions. We also investigate the use of derivative information to obtain better depth resolution and to reduce underlying uncertainties. We applied the technique on two synthetic data sets and an airborne-gravity data set collected over Lake Vostok, East Antarctica, for which a priori constraints were derived from available seismic and radar profiles. The inversion results produced depths of the lake in the survey area along with the thickness of sediments. The resulting uncertainties are interpreted in terms of the experimental geometry and data error.

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