Bayesian approach to magnetotelluric tensor decomposition

<!--[if gte mso 9]><xml> <o:DocumentProperties> <o:Template>Normal.dotm</o:Template> <o:Revision>0</o:Revision> <o:TotalTime>0</o:TotalTime> <o:Pages>1</o:Pages> <o:Words>210</o:Words> <o:Characters>1198</o:Characters> <o:Company>INGV BO</o:Company> <o:Lines>9</o:Lines> <o:Paragraphs>2</o:Paragraphs> <o:CharactersWithSpaces>1471</o:CharactersWithSpaces> <o:Version>12.0</o:Version> </o:DocumentProperties> <o:OfficeDocumentSettings> <o:AllowPNG /> </o:OfficeDocumentSettings> </xml><![endif]--><!--[if gte mso 9]><xml> <w:WordDocument> <w:Zoom>0</w:Zoom> <w:TrackMoves>false</w:TrackMoves> <w:TrackFormatting /> <w:HyphenationZone>14</w:HyphenationZone> <w:PunctuationKerning /> <w:DrawingGridHorizontalSpacing>18 pt</w:DrawingGridHorizontalSpacing> <w:DrawingGridVerticalSpacing>18 pt</w:DrawingGridVerticalSpacing> <w:DisplayHorizontalDrawingGridEvery>0</w:DisplayHorizontalDrawingGridEvery> <w:DisplayVerticalDrawingGridEvery>0</w:DisplayVerticalDrawingGridEvery> <w:ValidateAgainstSchemas /> <w:SaveIfXMLInvalid>false</w:SaveIfXMLInvalid> <w:IgnoreMixedContent>false</w:IgnoreMixedContent> <w:AlwaysShowPlaceholderText>false</w:AlwaysShowPlaceholderText> <w:Compatibility> <w:BreakWrappedTables /> <w:DontGrowAutofit /> <w:DontAutofitConstrainedTables /> <w:DontVertAlignInTxbx /> </w:Compatibility> </w:WordDocument> </xml><![endif]--><!--[if gte mso 9]><xml> <w:LatentStyles DefLockedState="false" LatentStyleCount="276"> </w:LatentStyles> </xml><![endif]--> <!-- /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {mso-style-parent:""; margin:0cm; margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-fareast-font-family:"Times New Roman"; mso-bidi-font-family:"Times New Roman"; mso-ansi-language:CS; mso-fareast-language:CS;} @page Section1 {size:612.0pt 792.0pt; margin:70.85pt 2.0cm 2.0cm 2.0cm; mso-header-margin:36.0pt; mso-footer-margin:36.0pt; mso-paper-source:0;} div.Section1 {page:Section1;} --> <!--[if gte mso 10]> <mce:style><! /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Tabella normale"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:12.0pt; font-family:"Times New Roman"; mso-ascii-font-family:Cambria; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Cambria; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:"Times New Roman"; mso-bidi-theme-font:minor-bidi;} --> <!--[endif]--> <!--StartFragment--> <p class="MsoNormal"><span lang="CS">Magnetotelluric directional analysis and impedance tensor decomposition are basic tools to validate a local/regional composite electrical model of the underlying structure. Bayesian stochastic methods approach the problem of the parameter estimation and their uncertainty characterization in a fully probabilistic fashion, through the use of posterior model probabilities.We use the standard Groom­Bailey 3­D local/2­D regional composite model in our bayesian approach. We assume that the experimental impedance estimates are contamined with the Gaussian noise and define the likelihood of a particular composite model with respect to the observed data. We use non­informative, flat priors over physically reasonable intervals for the standard Groom­Bailey decomposition parameters. We apply two numerical methods, the Markov chain Monte Carlo procedure based on the Gibbs sampler and a single­component adaptive Metropolis algorithm. From the posterior samples, we characterize the estimates and uncertainties of the individual decomposition parameters by using the respective marginal posterior probabilities. We conclude that the stochastic scheme performs reliably for a variety of models, including the multisite and multifrequency case with up to several hundreds of parameters. Though the Monte Carlo samplers are computationally very intensive, the adaptive Metropolis algorithm increase the speed of the simulations for large­scale problems. </span></p> <!--EndFragment--&gt

3D imaging of the subsurface electrical resistivity structure in West Bohemia/Upper Palatinate covering mofettes and Quaternary volcanic structures by using Magnetotellurics

The region of West Bohemia and Upper Palatinate belongs to the West Bohemian Massif. The study area is situated at the junction of three different Variscan tectonic units and hosts the ENE-WSW trending Ohře Rift as well as many different fault systems. The entire region is characterized by ongoing magmatic processes in the intra-continental lithospheric mantle expressed by a series of phenomena, including e.g. the occurrence of repeated earthquake swarms and massive degassing of mantle derived CO2 in form of mineral springs and mofettes. Ongoing active tectonics is mainly manifested by Cenozoic volcanism represented by different Quaternary volcanic structures. All these phenomena make the Ohře Rift a unique target area for European intra-continental geo-scientific research. With magnetotelluric (MT) measurements we image the subsurface distribution of the electrical resistivity and map possible fluid pathways. Two-dimensional (2D) inversion results by Muñoz et al. (2018) reveal a conductive channel in the vicinity of the earthquake swarm region that extends from the lower crust to the surface forming a pathway for fluids into the region of the mofettes. A second conductive channel is present in the south of their model; however, their 2D inversions allow ambiguous interpretations of this feature. Therefore, we conducted a large 3D MT field experiment extending the study area towards the south. The 3D inversion result matches well with the known geology imaging different fluid/magma reservoirs at crust-mantle depth and mapping possible fluid pathways from the reservoirs to the surface feeding known mofettes and spas. A comparison of 3D and 2D inversion results suggests that the 2D inversion results are considerably characterized by 3D and off-profile structures. In this context, the new results advocate for the swarm earthquakes being located in the resistive host rock surrounding the conductive channels; a finding in line with observations e.g. at the San Andreas Fault, California