• Geophysics and Geophysical Exploration
• /
• v.2 no.1
• /
• pp.43-53
• /
• 1999

Numerical modeling and inversion for electromagnetic exploration methods are essential to understand behaviour of electromagnetic fields in complex subsurface. In this study, a finite element method was adopted as a numerical scheme for the 2.5-dimensional forward problem. And a finite element equation considering linear conductivity variation was proposed, when 2.5-dimensional differential equation to couple eletric and magnetic field was implemented. Model parameters were investigated for near-field with large source effects and far-field with responses dominantly by homogeneous half-space. Numerical responses by this study were compared with analytic solutions in homogeneous half-space. Blocky inversion model was modified to be applied to the forward calculation in this study and it was also adopted in the inversion algorithm. Resolution for isolated bodies were investigated to confirm possibility and limitation of inversion for electromagnetic exploration data.

• Geophysics and Geophysical Exploration
• /
• v.12 no.1
• /
• pp.99-104
• /
• 2009

We propose a waveform inversion method for SH-wave data obtained in a shallow seismic refraction survey, to determine a 2D inhomogeneous S-wave profile of shallow soils. In this method, a 2.5D equation is used to simulate SH-wave propagation in 2D media. The equation is solved with the staggered grid finite-difference approximation to the 4th-order in space and 2nd-order in time, to compute a synthetic wave. The misfit, defined using differences between calculated and observed waveforms, is minimised with a hybrid heuristic search method. We parameterise a 2D subsurface structural model with blocks with different depth boundaries, and S-wave velocities in each block. Numerical experiments were conducted using synthetic SH-wave data with white noise for a model having a blind layer and irregular interfaces. We could reconstruct a structure including a blind layer with reasonable computation time from surface seismic refraction data.