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On joint modelling of electrical conductivity and other geophysical and petrological observables to infer the structure of the lithosphere and underlying upper mantle

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2017

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Springer
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Fullea, J. On Joint Modelling of Electrical Conductivity and Other Geophysical and Petrological Observables to Infer the Structure of the Lithosphere and Underlying Upper Mantle. Surv Geophys 38, 963–1004 (2017). https://doi.org/10.1007/s10712-017-9432-4

Abstract

This review paper focuses on joint modelling and interpretation of electromagnetic data and other geophysical and petrological observables. In particular, integrated geophysical-petrological modelling approaches, where the electrical conductivity and other physical properties of rocks are required to be linked by the common subsurface thermochemical conditions within a self-consistent thermodynamic framework, are reviewed. The paper gives an overview of the main geophysical electromagnetic techniques/data sets employed in lithospheric and mantle imaging including recent advances using satellite data, and an up-to-date summary of the most relevant laboratory experiments regarding the electrical conductivity of upper mantle minerals for various temperature-pressure-water conditions. The sensitivity of electrical conductivity and other geophysical parameters (density, seismic velocities) of mantle rocks to changes in temperature and composition are presented based on a Monte Carlo method parameter exploration. Finally, a case study in Central Tibet is presented where both seismological (long-period surface wave phase velocities) and electromagnetic (magnetotelluric) data-simultaneously including the constraints offered by topography, surface heat flow and mantle xenoliths-have been integrated. The modelling is based on a self-consistent petrological-geophysical thermodynamic framework where mantle properties are calculated as a function of temperature, pressure, and composition. The Tibetan case study offers an excellent opportunity to illustrate the different and complementary sensitivities of the various data sets used and to show how integrated thermochemical models of the lithosphere can help understand settings with a complex tectonic evolution.

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