The Crust and Upper Mantle Structure of the Iranian Plateau from Joint Waveform Tomography Imaging of Body and Surface Waves

Wednesday, 17 December 2014
Steven W Roecker, Rensselaer Polytechnic Inst, Troy, NY, United States, Keith F Priestley, University of Cambridge, Cambridge, United Kingdom and Mohammad Tatar, International Institute of Earthquake Engineering and Seismology, Tehran, Iran
The Iranian Plateau forms a broad zone of deformation between the colliding Arabian and Eurasian plates. The convergence is accommodated in the Zagros Mountains of SW Iran, the Alborz Mountains of northern Iran, and the Kopeh Dagh Mountains of NE Iran. These deforming belts are separated by relatively aseismic depressions such as the Lut Block. It has been suggested that the Arabia-Eurasia collision is similar to the Indo-Eurasia collision but at a early point of development and therefore, it may provide clues to our understanding of the earlier stages of the continent-continent collision process. We present results of the analysis of seismic data collected along two NE-SW trending transects across the Iranian Plateau. The first profile extends from near Bushere on the Persian Gulf coast to near to the Iran-Turkmenistan border north of Mashad, and consists of seismic recordings along the SW portion of the line in 2000-2001 and recording along the NE portion of the line in 2003 and 2006-2008. The second profile extends from near the Iran-Iraq border near the Dezfel embayment to the south Caspian Sea coast north of Tehran. We apply the combined 2.5D finite element waveform tomography algorithm of Baker and Roecker [2014] to jointly invert teleseismic body and surface waves to determine the elastic wavespeed structures of these areas. The joint inversion of these different types of waves affords similar types of advantages that are common to combined surface wave dispersion/receiver function inversions in compensating for intrinsic weaknesses in horizontal and vertical resolution capabilities. We compare results recovered from a finite difference approach to document the effects of various assumptions related to their application, such as the inclusion of topography, on the models recovered. We also apply several different inverse methods, starting with simple gradient techniques to the more sophisticated pseudo-Hessian or L-BFGS approach, and find that the latter are generally more robust. Modeling of receiver functions and surface wave dispersion prior to the analysis is shown to be an efficacious way to generate starting models for this analysis.