Open AccessAn inverse technique for retrieving higher mode phase velocity and mantle structure
Author(s) -
Stutzmann Eléonore,
Montagner JeanPaul
Publication year - 1993
Publication title -
geophysical journal international
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.302
H-Index - 168
eISSN - 1365-246X
pISSN - 0956-540X
DOI - 10.1111/j.1365-246x.1993.tb04659.x
Subject(s) - seismogram , geology , inversion (geology) , earth structure , spectral line , geodesy , inverse transform sampling , synthetic data , seismology , geophysics , surface wave , optics , physics , algorithm , mathematics , astronomy , tectonics
SUMMARY We present a new inverse method for retrieving the mantle structure, using the fundamental and higher modes surface waves. The fundamental mode is only sensitive to structures down to 400‐500 km but higher modes have a depth resolution down to 1000‐1500 km. So, they are well suited to the study of the transition zone between 400 and 1000 km depth. A data set of seismograms corresponding to events all located in a small area and recorded at a single station is selected. The inversion of the seismograms is divided into two steps. First, the difference between the real spectra and the sum of the higher modes synthetic spectra is inverted for retrieving the phase velocities of the first higher modes. In a second step, these phase velocities are inverted at depth in order to retrieve the average mantle structure between the receiver and the epicentral area. This structure is modelled as a transversely isotropic medium with a vertical symmetry axis. Because of the non‐linearity of the problem, it is necessary to iterate the procedure and to recalculate the Earth eigenfunctions and the new synthetic spectra at each iteration. Numerical tests on synthetic data have been performed and they demonstrate that we have a good resolution at depth down to 1500 km. Some results obtained on real data recorded on GEOSCOPE network are also presented. This method can now be applied systematically to real data.