Inversion Of Surface Wave Phase Velocity Using New Genetic Algorithm Technique For Geotechnical Site Investigation
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Date
2011-05
Authors
La, Hamimu
Journal Title
Journal ISSN
Volume Title
Publisher
Universiti Sains Malaysia
Abstract
The inverse procedure of surface wave phase velocity is a complicated
problem for linear inversion approach because of its multi-model and highly nonlinear
nature. Therefore the use of genetic algorithm (GA) optimization technique
which is one of nonlinear optimization methods is an appropriate choice to solve
surface wave inversion problem having high nonlinearity and multimodality. A novel
inversion procedure of GA (NIPGA) suggested in this study was presented an
effective technique for surface wave phase velocity inversion. This procedure
adopted standard inversion procedure of GA (SIPGA) inserting a new loop scheme
for updating the search limits of model parameters i.e., shear wave velocity (Vs) and
thickness (H). Inversion codes of NIPGA developed under Visual Compact
FORTRAN Version 6.6 were successfully applied to the synthetic and field phase
velocity inversions.
Two different synthetic profiles representing the high velocity layer (HVL)
and low velocity layer (LVL) cases were used. These profiles are considered to
simulate situation commonly encountered in geotechnical site investigation.
Effective Rayleigh wave and multimode Love wave phase velocities are synthesized
from these profiles using full P-SV waveform reflectivity and full SH waveform
reflectivity, respectively. The phase velocities are then inverted using codes of
NIPGA with three different approaches, namely single inversion of the effective
Rayleigh wave phase velocity, single inversion of multimode Love wave phase
velocities and joint inversion of them. To assess the accuracy of each inversion approach, differences between the true and inverted shear wave velocity profile are quantified in terms of shear wave
velocity error, ES. Our numerical modeling showed that the shear wave velocity
errors of the joint inversion approach based on NIPGA codes are relatively smaller
than the single inversion approach. These errors indicate that the accuracy of shear
wave velocity reversal can be improved by jointly inverting of Rayleigh wave and
Love wave phase velocities.
Description
Keywords
Surface wave phase velocity , use of genetic algorithm