Implications of the observations scarcity on the gravity data inversion within volcanic areas. Ciomadul volcano

Author(s):  
Lucian Besutiu ◽  
Luminita Zlagnean ◽  
Anca Isac ◽  
Dragomir Romanescu

<p>RATIONALE</p><p>Gravity investigation of volcanoes is difficult due to their usual location in rugged topographic areas, where lack of access hardly offers possibility for adequate observations coverage.</p><p>In the absence of appropriate constraints this might have important consequences on the interpretation of the survey results.</p><p>BACKGROUND</p><p>Located in the inner part of the bending zone of East Carpathians, Romania, Ciomadul volcano represents the end member of the Neogene to Quaternary volcanism in the Carpathian - Pannonian Region. This cluster of dacitic domes last erupted about 30 ka ago, and there are authors claiming it might become active, based on indirect evidence on the presence of a magma chamber in the upper crust beneath it.</p><p>Inversion of relatively recent acquired gravity data outlined an extended mass deficit below central volcano initially interpreted as a magma chamber, in apparent agreement with previous MTS works unveiling an electrical resistivity low beneath volcano. The gradual decrease of density towards the inner (hotter?) part of the source seems to be consistent with hypothesis of a cooling body.</p><p>However, the overall geometry and in-depth extent of the density zone with values corresponding to volcanic rocks is not consistent with accepted structural models for such volcanoes, mainly developed on the topography.</p><p>Besides, the extreme density values predicted were never encountered on samples collected from outcrops, and according to literature there is no increase in temperature able to provide the density lowering shown by inversion.</p><p>Finally, the idea of magma chamber at relatively shallow depths may be hardly accepted because it would generate strong geothermal manifestations at the surface (e.g. geysers), nowhere encountered.</p><p>APPROACH & RESULTS</p><p>For better understanding/interpreting the inversion results, limitations of the approach were studied by computing/inverting the gravity effect of synthetic sources. Fluid-filled vertical volcano conduits of variable size/content (but always dimensioned bellow the sampling step of the gravity signal provided by the survey coverage) were subject to study.</p><p>The research showed that inversion was not able to accurately predict the parameters of the source in any simulation. Basic 2D geometry of the volcano conduit with step density change along the edges is replaced by a 3D broadly extended body with gradual decrease of density towards its inner part. The larger the cavity, the smaller densities may occur. Some densities outside the source model range are also predicted, and a pseudo-mass excess may be inappropriately generated above the upper end of the conduit.</p><p>CONSEQUENCES</p><p>Following the simulations, the density model of Ciomadul volcano was fully revised by using an iterative 3D forward modelling. The new model unveils peculiarities of a largely developed plumbing system, partly open to magma access, but does not support any longer the hypothesis of a magma reservoir in the upper crust beneath Ciomadul.</p><p>SPECULATIONS</p><p>Given the above-mentioned aspects, we may assume that former solution of the MT data inversion was also biased by data scarcity that inherently led to the integration of local effects of several narrow fluid-filled conduits into a unique electrical resistivity anomaly interpreted as a magma chamber.</p>

Geophysics ◽  
2020 ◽  
pp. 1-45
Author(s):  
Vitaliy Ogarko ◽  
Jérémie Giraud ◽  
Roland Martin ◽  
Mark Jessell

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.


2015 ◽  
Vol 173 (4) ◽  
pp. 1223-1241 ◽  
Author(s):  
Vassilios N. Grigoriadis ◽  
Ilias N. Tziavos ◽  
Grigorios N. Tsokas ◽  
Alexandros Stampolidis

2021 ◽  
Vol 2 (2) ◽  
pp. 196-200
Author(s):  
Vladislav A. Okunev ◽  
Andrey Yu. Sobolev

The article presents an alternative geoelectric model of the near-borehole space for electromagnetic logging data inversion in the class of models with a smooth and piecewise linear distribution of the electrical resistivity. We used ready-made ATLAS MPhM calculation modules, a library for python developed at the IPGG SB RAS.


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