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A 3D S‐velocity model has been determined from fundamental‐mode Rayleigh‐wave analysis in a wide period band (from 5 s to 175 s), to attain the characterization of the geologic structures existing in the Bay of Bengal, from 0 to 300 km depth. This model is presented by means of S‐velocity maps. In these maps, the S‐velocity in the depth range from 0 to 10 km is principally affected by the distribution of the sediment deposits. The S‐velocity generally increases with depth, showing the lowest values for shallow depths in which are present unconsolidated sediments. The S‐velocity mapping also allows the clear differentiation between the 85E Ridge and the 90E Ridge. The lower S‐velocity determined for the 85E Ridge compared with its adjacent region suggests that this ridge is less dense than its adjacent region. The existence of compensation beneath both ridges also is definitively confirmed in the Moho map performed in this study. The lower S‐velocities determined for the regions of the Andaman Sea and the northernmost part of the Bay of Bengal, in the depth range from 15 to 40 km, are associated to the existence of a thick crust beneath this regions. The results obtained in the present study confirm that the crust beneath the Bay of Bengal is in general thin crust. Although the controversy about the nature of the crust beneath the Bay of Bengal (is it oceanic or continental?) still persist, the results of the present study show that both hypotheses (oceanic crust and continental crust) are reasonable. The 3D S‐velocity model shows that the huge sediment load located at the northernmost part of the Bay of Bengal has originated at the thickening of the crust and the lithosphere, whereas the asthenosphere is almost unaffected by this load. This model also shows that the subduction of the Indian Plate below the Burma Plate, at the east of the Sunda Trench, also has produced a thickening of the crust and the lithosphere, but the asthenosphere is almost not affected by this effect. Finally, the dependency of the S‐velocity with the age of the lithosphere and the asthenosphere is shown very clearly for the lithosphere whereas it is only slight visible for the asthenosphere.
A 3D S‐velocity model has been determined from fundamental‐mode Rayleigh‐wave analysis in a wide period band (from 5 s to 175 s), to attain the characterization of the geologic structures existing in the Bay of Bengal, from 0 to 300 km depth. This model is presented by means of S‐velocity maps. In these maps, the S‐velocity in the depth range from 0 to 10 km is principally affected by the distribution of the sediment deposits. The S‐velocity generally increases with depth, showing the lowest values for shallow depths in which are present unconsolidated sediments. The S‐velocity mapping also allows the clear differentiation between the 85E Ridge and the 90E Ridge. The lower S‐velocity determined for the 85E Ridge compared with its adjacent region suggests that this ridge is less dense than its adjacent region. The existence of compensation beneath both ridges also is definitively confirmed in the Moho map performed in this study. The lower S‐velocities determined for the regions of the Andaman Sea and the northernmost part of the Bay of Bengal, in the depth range from 15 to 40 km, are associated to the existence of a thick crust beneath this regions. The results obtained in the present study confirm that the crust beneath the Bay of Bengal is in general thin crust. Although the controversy about the nature of the crust beneath the Bay of Bengal (is it oceanic or continental?) still persist, the results of the present study show that both hypotheses (oceanic crust and continental crust) are reasonable. The 3D S‐velocity model shows that the huge sediment load located at the northernmost part of the Bay of Bengal has originated at the thickening of the crust and the lithosphere, whereas the asthenosphere is almost unaffected by this load. This model also shows that the subduction of the Indian Plate below the Burma Plate, at the east of the Sunda Trench, also has produced a thickening of the crust and the lithosphere, but the asthenosphere is almost not affected by this effect. Finally, the dependency of the S‐velocity with the age of the lithosphere and the asthenosphere is shown very clearly for the lithosphere whereas it is only slight visible for the asthenosphere.
A combination of magnetotelluric (MT) measurements on the surface and in boreholes (without metal casing) can be expected to enhance resolution and reduce the ambiguity in models of electrical resistivity derived from MT surface measurements alone. In order to quantify potential improvement in inversion models and to aid design of electromagnetic (EM) borehole sensors, we considered two synthetic 2D models containing ore bodies down to 3000 m depth (the first with two dipping conductors in resistive crystalline host rock and the second with three mineralisation zones in a sedimentary succession exhibiting only moderate resistivity contrasts). We computed 2D inversion models from the forward responses based on combinations of surface impedance measurements and borehole measurements such as (1) skin-effect transfer functions relating horizontal magnetic fields at depth to those on the surface, (2) vertical magnetic transfer functions relating vertical magnetic fields at depth to horizontal magnetic fields on the surface and (3) vertical electric transfer functions relating vertical electric fields at depth to horizontal magnetic fields on the surface. Whereas skin-effect transfer functions are sensitive to the resistivity of the background medium and 2D anomalies, the vertical magnetic and electric field transfer functions have the disadvantage that they are comparatively insensitive to the resistivity of the layered background medium. This insensitivity introduces convergence problems in the inversion of data from structures with strong 2D resistivity contrasts. Hence, we adjusted the inversion approach to a three-step procedure, where (1) (2) this inversion model from surface impedances is used as the initial model for a joint inversion of surface impedances and skin-effect transfer functions and (3) the joint inversion model derived from the surface impedances and skin-effect transfer functions is used as the initial model for the inversion of the surface impedances, skin-effect transfer functions and vertical magnetic and electric transfer functions. For both synthetic examples, the inversion models resulting from surface and borehole measurements have higher similarity to the true models than models computed exclusively from surface measurements. However, the most prominent improvements were obtained for the first example, in which a deep small-sized ore body is more easily distinguished from a shallow main ore body penetrated by a borehole and the extent of the shadow zone (a conductive artefact) underneath the main conductor is strongly reduced. Formal model error and resolution analysis demonstrated that predominantly the skin-effect transfer functions improve model resolution at depth below the sensors and at distance of $ 300-1000 m laterally off a borehole, whereas the vertical electric and magnetic transfer functions improve resolution along the borehole and in its immediate vicinity. Furthermore, we studied the signal levels at depth and provided specifications of borehole magnetic and elect...
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